diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json
index 3991ac95bb..aeffdd7da4 100644
--- a/nasa_cmr_catalog.json
+++ b/nasa_cmr_catalog.json
@@ -90,19 +90,6 @@
         "description": "We collected surface seawater samples using trace clean 1L Nalgene bottles on the end of a long bamboo pole.   We will analyse these samples for trace elements.  Iron is the element of highest interest to our group.  We will determine dissolved iron and total dissolvable iron concentrations.    Samples collected from 7 sites:   Sites 1, 2, 3, 4 were a transect perpendicular to the edge of the iceberg to try and determine if there is a iron concentration gradient relative to the iceberg.   Sites 4, 5, 6 were along the edge of the iceberg to determine if there is any spatial variability along the iceberg edge.  Site 7 was away from the iceberg to determine what the iron concentration is in the surrounding waters not influenced by the iceberg.",
         "license": "not-provided"
     },
-    {
-        "id": "2019 Mali CropType Training Data.v1",
-        "title": "2019 Mali CropType Training Data",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "-6.9444015, 12.8185552, -6.5890481, 13.3734391",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412344-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412344-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/2019 Mali CropType Training Data.v1",
-        "description": " This dataset produced by the NASA Harvest team includes crop types labels from ground referencing matched with time-series of Sentinel-2 imagery during the growing season. Ground reference data are collected using an ODK app. Crop types include Maize, Millet, Rice and Sorghum. Labels are vectorized over the Sentinel-2 grid, and provided as raster files. Funding for this dataset is provided by Lutheran World Relief, Bill & Melinda Gates Foundation, and University of Maryland NASA Harvest program.",
-        "license": "not-provided"
-    },
     {
         "id": "39480",
         "title": "1988 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve",
@@ -337,45 +324,6 @@
         "description": "The \"Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)\" is a fixed grid map (in stereographic projection) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between \u201339.5\u00b0C and +87\u00b0C with a radiometric resolution of 0.5\u00b0C. A value of \u201340\u00b0C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/",
         "license": "not-provided"
     },
-    {
-        "id": "A Fusion Dataset for Crop Type Classification in Germany.v1",
-        "title": "A Fusion Dataset for Crop Type Classification in Germany",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "13.6339485, 52.4179888, 14.3529903, 52.8494418",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412484-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412484-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/A Fusion Dataset for Crop Type Classification in Germany.v1",
-        "description": " This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Brandenburg, Germany. There are nine crop types in this dataset from years 2018 and 2019: Wheat, Rye, Barley, Oats, Corn, Oil Seeds, Root Crops, Meadows, Forage Crops. The 2018 labels from one of the tiles are provided for training, and the 2019 labels from a neighboring tile will be used for scoring in the competition.   Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection.   The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license.  ",
-        "license": "not-provided"
-    },
-    {
-        "id": "A Fusion Dataset for Crop Type Classification in Western Cape, South Africa.v1",
-        "title": "A Fusion Dataset for Crop Type Classification in Western Cape, South Africa",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "20.5212157, -34.413256, 21.043415, -33.9796334",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412697-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412697-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/A Fusion Dataset for Crop Type Classification in Western Cape, South Africa.v1",
-        "description": " This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Western Cape, South Africa. There are five crop types from the year 2017: Wheat, Barely, Canola, Lucerne/Medics, Small grain grazing. The AOI is split to three tiles. Two tiles are provided as training labels, and one tile will be used for scoring in the competition.   Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection.   The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license.   The Western Cape Department of Agriculture (WCDoA) vector data are supplied via Radiant Earth Foundation with limited distribution rights. Data supplied by the WCDoA may not be distributed further or used for commercial purposes. The vector data supplied are intended strictly for use within the scope of this remote sensing competition - for the purpose of academic research to our mutual benefit. The data is intended for research purposes only and the WCDoA cannot be held responsible for any errors or omissions which may occur in the data. ",
-        "license": "not-provided"
-    },
-    {
-        "id": "A crop type dataset for consistent land cover classification in Central Asia.v1",
-        "title": "A crop type dataset for consistent land cover classification in Central Asia",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "60.2013297, 37.4241018, 72.3539419, 41.8252151",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412666-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412666-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/A crop type dataset for consistent land cover classification in Central Asia.v1",
-        "description": "Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture relies heavily on irrigation. Here, remote sensing is valuable to map crop types, but its quality depends on consistent ground-truth data. Yet, in the ASB, such data is missing. Addressing this issue, we collected thousands of polygons on crop types, 97.7% of which in Uzbekistan and the remaining in Tajikistan. We collected 8,196 samples between 2015 and 2018, 213 in 2011 and 26 in 2008. Our data compiles samples for 40 crop types and is dominated by \u201ccotton\u201d (40%) and \u201cwheat\u201d, (25%). These data were meticulously validated using expert knowledge and remote sensing data and relied on transferable, open-source workflows that will assure the consistency of future sampling campaigns.",
-        "license": "not-provided"
-    },
     {
         "id": "AAOT.v0",
         "title": "Acqua Alta Oceanographic Tower (AAOT)",
@@ -454,32 +402,6 @@
         "description": "This data set contains geotagged images collected over Alaska and Western Canada. The images were taken by the NASA Digital Mapping Camera, paired with the Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of NASA's Terrestrial Ecology Program campaign, the Arctic-Boreal Vulnerability Experiment (ABoVE).",
         "license": "not-provided"
     },
-    {
-        "id": "ABoVE_ASCENDS_XCO2_2050.v1",
-        "title": "ABoVE/ASCENDS: Active Sensing of CO2, CH4, and Water Vapor, Alaska and Canada, 2017",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "2017-07-20",
-        "end_date": "2017-08-08",
-        "bbox": "-165.68, 34.59, -98.1, 71.28",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2264340976-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2264340976-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/ABoVE_ASCENDS_XCO2_2050.v1",
-        "description": "This dataset provides in situ airborne measurements of atmospheric carbon dioxide (CO2), methane (CH4), and water vapor concentrations, plus air temperature, pressure, relative humidity, and wind speed values over Alaska and the Yukon and Northwest Territories of Canada during 2017-07-20 to 2017-08-08. Measurements were taken onboard a DC-8 aircraft during this Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) airborne deployment over portions of the Arctic-Boreal Vulnerability Experiment (ABoVE) domain. CO2 and CH4 were measured with NASA's Atmospheric Vertical Observations of CO2 in the Earth's Troposphere (AVOCET) instrument. Water vapor and relative humidity were measured with Diode Laser Hydrometer. Measurements of column-averaged dry-air mixing ratio CO2 measurements (XCO2) were taken with the CO2 Sounder Lidar instrument. The airborne CO2 Sounder is a pulsed, multi-wavelength Integrated Path Differential Absorption lidar. It estimates XCO2 in the nadir path from the aircraft to the scattering surface by measuring the shape of the 1572.33 nm CO2 absorption line. The data were collected in order to capture the spatial and temporal dynamics of the northern high latitude carbon cycle as part of ABoVE and are provided in ICARTT file format.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ABoVE_Concise_Experiment_Plan_1617.v1.1",
-        "title": "A Concise Experiment Plan for the Arctic-Boreal Vulnerability Experiment",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "2014-01-01",
-        "end_date": "2021-12-31",
-        "bbox": "-176.12, 39.42, -66.92, 81.61",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2162145735-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162145735-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/ABoVE_Concise_Experiment_Plan_1617.v1.1",
-        "description": "This document presents the Concise Experiment Plan for NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) to serve as a guide to the Program as it identifies the research to be conducted under this study. Research for ABoVE will link field-based, process-level studies with geospatial data products derived from airborne and satellite remote sensing, providing a foundation for improving the analysis and modeling capabilities needed to understand and predict ecosystem responses and societal implications. The ABoVE Concise Experiment Plan (ACEP) outlines the conceptual basis for the Field Campaign and expresses the compelling rationale explaining the scientific and societal importance of the study. It presents both the science questions driving ABoVE research as well as the top-level requirements for a study design to address them.",
-        "license": "not-provided"
-    },
     {
         "id": "ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data.v1",
         "title": "ACCLIP WB-57 Aerosol and Cloud Remotely Sensed Data",
@@ -506,19 +428,6 @@
         "description": "ACCLIP_Aerosol_AircraftInSitu_WB57_Data is the in-situ aerosol data collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Particle Analysis by Laser Mass Spectrometry - Next Generation (PALMS-NG), Single Particle Soot Photometer (SP2), Nucleation-Mode Aerosol Size Spectrometer (N-MASS), Printed Optical Particle Spectrometer (POPS), and the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.",
         "license": "not-provided"
     },
-    {
-        "id": "ACCLIP_AircraftInSitu_WB57_Water_Data.v1",
-        "title": "ACCLIP WB-57 Aircraft Water In-situ Data",
-        "catalog": "LARC_ASDC",
-        "state_date": "2022-07-14",
-        "end_date": "2022-09-14",
-        "bbox": "-180, 16.6, 180, 61.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609920136-LARC_ASDC.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609920136-LARC_ASDC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_AircraftInSitu_WB57_Water_Data.v1",
-        "description": "ACCLIP_AircraftInSitu_WB57_Water_Data is the in-situ water data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Chicago Water Isotope Spectrometer  (ChiWIS) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.",
-        "license": "not-provided"
-    },
     {
         "id": "ACCLIP_Cloud_AircraftInSitu_WB57_Data.v1",
         "title": "ACCLIP WB-57 Aircraft In-situ Cloud Data",
@@ -532,32 +441,6 @@
         "description": "ACCLIP_Cloud_AircraftInSitu_WB57_Data is the in-situ cloud data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Cloud, Aerosol, and Precipitation Spectrometer (CAPS) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.",
         "license": "not-provided"
     },
-    {
-        "id": "ACCLIP_MetNav_AircraftInSitu_WB57_Data.v1",
-        "title": "ACCLIP WB-57 Meteorological and Navigational Data",
-        "catalog": "LARC_ASDC",
-        "state_date": "2022-07-14",
-        "end_date": "2022-09-14",
-        "bbox": "-180, 16.6, 180, 61.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2566338281-LARC_ASDC.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2566338281-LARC_ASDC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_MetNav_AircraftInSitu_WB57_Data.v1",
-        "description": "ACCLIP_MetNav_AircraftInSitu_WB57_Data is the in-situ meteorology and navigational data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Meteorological Measurement System (MMS) and Diode Laser Hygrometer (DLH) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ACCLIP_Model_WB57_Data.v1",
-        "title": "ACCLIP WB-57 Aircraft Model Data",
-        "catalog": "LARC_ASDC",
-        "state_date": "2022-07-14",
-        "end_date": "2022-09-14",
-        "bbox": "-180, 16.6, 180, 61.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609869612-LARC_ASDC.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609869612-LARC_ASDC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_Model_WB57_Data.v1",
-        "description": "ACCLIP_Model_WB57_Data contains modeled meteorological, chemical, and aerosol data along the flight tracks of the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.",
-        "license": "not-provided"
-    },
     {
         "id": "ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1",
         "title": "ACCLIP WB-57 Aircraft In-situ Trace Gas Data",
@@ -571,45 +454,6 @@
         "description": "ACCLIP_TraceGas_AircraftInSitu_WB57_Data is the in-situ trace gas data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Airborne Carbon Oxide Sulfide Spectrometer (ACOS), Carbon monOxide Measurement from Ames (COMA), Laser Induced Fluorescence - Nitrogen Oxide (LIF-NO), In Situ Airborne Formaldehyde (ISAF), Carbon Oxide Laser Detector 2 (COLD 2), and the NOAA UAS O3 Photometer (UASO3) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.",
         "license": "not-provided"
     },
-    {
-        "id": "ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1",
-        "title": "ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data Version 1",
-        "catalog": "LARC_ASDC",
-        "state_date": "2017-10-18",
-        "end_date": "2020-11-20",
-        "bbox": "-130, 25, -100, 45",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1",
-        "description": "ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_AirHARP_Data) are remotely sensed measurements collected by the Airborne Hyper Angular Rainbow Polarimeter (AirHARP) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which is a valuable resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1",
-        "title": "ACEPOL Airborne Spectrometer for Planetary Exploration (AirSPEX) Remotely Sensed Data Version 1",
-        "catalog": "LARC_ASDC",
-        "state_date": "2017-10-19",
-        "end_date": "2017-11-09",
-        "bbox": "-130, 25, -100, 45",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1",
-        "description": "ACEPOL_AircraftRemoteSensing_AirSPEX_Data are remotely sensed measurements collected by the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ACEPOL_AircraftRemoteSensing_CPL_Data.v1",
-        "title": "ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data Version 1",
-        "catalog": "LARC_ASDC",
-        "state_date": "2017-10-19",
-        "end_date": "2017-11-09",
-        "bbox": "-130, 25, -100, 45",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588308-LARC_ASDC.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588308-LARC_ASDC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACEPOL_AircraftRemoteSensing_CPL_Data.v1",
-        "description": "ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.",
-        "license": "not-provided"
-    },
     {
         "id": "ACIDD.v0",
         "title": "Across the Channel Investigating Diel Dynamics project",
@@ -948,45 +792,6 @@
         "description": "This data set contains geotagged images collected over Gabon, Africa. The images were taken by the NASA Digital Mapping Camera paired with the Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of a NASA campaign, in collaboration with the European Space Agency (ESA) mission AfriSAR.",
         "license": "not-provided"
     },
-    {
-        "id": "AG100.v003",
-        "title": "ASTER Global Emissivity Dataset, 100 meter, HDF5 V003",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-01-01",
-        "end_date": "2008-12-31",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000362-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000362-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AG100.v003",
-        "description": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate spectral resolution TRANsmittance (MODTRAN 5.2 radiative transfer model). This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG100 data are available globally at spatial resolution of 100 meters.    The National Aeronautics and Space Administration\u2019s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.  ",
-        "license": "not-provided"
-    },
-    {
-        "id": "AG1km.v003",
-        "title": "ASTER Global Emissivity Dataset, 1 kilometer, HDF5 V003",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-01-01",
-        "end_date": "2008-12-31",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000380-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000380-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AG1km.v003",
-        "description": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate Spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model. This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG1KM data are available globally at spatial resolution of 1 kilometer.    The National Aeronautics and Space Administration\u2019s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.",
-        "license": "not-provided"
-    },
-    {
-        "id": "AG5KMMOH.v041",
-        "title": "ASTER Global Emissivity Dataset, Monthly, 0.05 deg, HDF5 V041",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-03-01",
-        "end_date": "2015-12-31",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1344831606-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1344831606-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AG5KMMOH.v041",
-        "description": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is a collection of monthly files (see known issues for gaps) for each year of global emissivity. The ASTER GED data products are generated for 2000 through 2015 using the ASTER Temperature Emissivity Separation (TES) algorithm atmospheric correction method. This algorithm method uses Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheric Profiles product (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) and the MODerate spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model along with the snow cover data from the standard monthly MODIS/Terra snow cover monthly global 0.05 degree product (MOD10CM) (https://doi.org/10.5067/MODIS/MOD10CM.006), and vegetation information from the MODIS monthly gridded NDVI product (MOD13C2) (https://doi.org/10.5067/MODIS/MOD13C2.006). ASTER GED Monthly V041 data products are offered in Hierarchical Data Format 5 (HDF5).    The National Aeronautics and Space Administration\u2019s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.",
-        "license": "not-provided"
-    },
     {
         "id": "AIRABRAD.v005",
         "title": "AIRS/Aqua L1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005 (AIRABRAD) at GES DISC",
@@ -1494,58 +1299,6 @@
         "description": "The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).    The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan\u2019s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo.     The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated.     The geographic coverage of the ASTER GDEM extends from 83\u00b0 North to 83\u00b0 South. Each tile is distributed in NetCDF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area.     Each ASTGTM_NUMNC file indicates the number of scenes that were processed for each pixel and the source of the data.. The corresponding ASTGTM_NC data product contains a DEM file, which provides elevation information.     While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications.     Improvements/Changes from Previous Versions   \u2022 Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3.  \u2022 Separation of rivers from lakes in the water body processing.   \u2022 Minimum water body detection size decreased from 1 km2 to 0.2 km2. ",
         "license": "not-provided"
     },
-    {
-        "id": "ASTWBD.v001",
-        "title": "ASTER Global Water Bodies Database V001",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-03-01",
-        "end_date": "2013-11-30",
-        "bbox": "-180, -83, 180, 82",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734433-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734433-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/ASTWBD.v001",
-        "description": "The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.     The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces.    To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required.     The geographic coverage of the ASTWBD extends from 83\u00b0N to 83\u00b0S. Each tile is distributed in GeoTIFF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each data product is provided as a zipped file that contains an attribute file with the water body classification information and a DEM file, which provides elevation information in meters. ",
-        "license": "not-provided"
-    },
-    {
-        "id": "ASTWBD_ATTNC.v001",
-        "title": "ASTER Global Water Bodies Database Attributes NetCDF V001",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-03-01",
-        "end_date": "2013-11-30",
-        "bbox": "-180, -83, 180, 82",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734760-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734760-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/ASTWBD_ATTNC.v001",
-        "description": "The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.     The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces.    To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required.     The geographic coverage of the ASTWBD extends from 83\u00b0N to 83\u00b0S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_ATTNC file contains an attribute file with the water body classification information. The corresponding  ASTWBD_NC data product DEM file, which provides elevation information in meters.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ASTWBD_NC.v001",
-        "title": "ASTER Global Water Bodies Database NetCDF V001",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-03-01",
-        "end_date": "2013-11-30",
-        "bbox": "-180, -83, 180, 82",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734501-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734501-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/ASTWBD_NC.v001",
-        "description": "The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.     The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces.    To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required.     The geographic coverage of the ASTWBD extends from 83\u00b0N to 83\u00b0S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_NC data product DEM file, which provides elevation information in meters. The corresponding ASTWBD_ATTNC file contains an attribute file with the water body classification information.",
-        "license": "not-provided"
-    },
-    {
-        "id": "AST_L1A.v003",
-        "title": "ASTER L1A Reconstructed Unprocessed Instrument Data V003",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-03-04",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C14758250-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C14758250-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_L1A.v003",
-        "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1A (AST_L1A) contains reconstructed, instrument digital numbers (DNs) derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). Additionally, geometric correction coefficients and radiometric calibration coefficients are calculated and appended to the metadata, but not applied. The spatial resolution is 15 m (VNIR), 30 m (SWIR), and 90 m (TIR) with a temporal coverage of 2000 to present.     Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article.    Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427.  ",
-        "license": "not-provided"
-    },
     {
         "id": "AST_L1AE.v003",
         "title": "ASTER Expedited L1A Reconstructed Unprocessed Instrument Data V003",
@@ -1559,149 +1312,6 @@
         "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1A Reconstructed Unprocessed Instrument Data (AST_L1AE) global product contains reconstructed, unprocessed instrument digital data derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). This data product is similar to the (AST_L1A) (http://doi.org/10.5067/ASTER/AST_L1A.003) with a few notable exceptions. These include:  * The AST_L1AE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments.  * The registration quality of the AST_L1AE is likely to be lower than the AST_L1A, and may vary from scene to scene.  * The AST_L1AE data product does not contain the VNIR 3B (aft-viewing) Band.  * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor.  * The AST_L1AE data product is only available for download 30 days after acquisition. It is then removed and reprocessed into an AST_L1A product.",
         "license": "not-provided"
     },
-    {
-        "id": "AST_L1BE.v003",
-        "title": "ASTER Expedited L1B Registered Radiance at the Sensor V003",
-        "catalog": "LPDAAC_ECS",
-        "state_date": "2000-03-04",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179460406-LPDAAC_ECS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179460406-LPDAAC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_L1BE.v003",
-        "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1B Registered Radiance at the Sensor global data product is radiometrically calibrated and geometrically co-registered. Application of intra-telescope and inter-telescope registration corrections for all bands are relative to the reference band for each telescope: Visible  and Near Infrared (VNIR) Band 2, Shortwave Infrared (SWIR) Band 6, and Thermal Infrared (TIR) Band 11. The Expedited Level 1B data product is similar to the (AST_L1B) (https://doi.org/10.5067/ASTER/AST_L1B.003) with a few notable exceptions. These include:  * The AST_L1BE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments.  * The registration quality of the AST_L1BE is likely to be lower than the AST_L1B, and may vary from scene to scene.  * The AST_L1BE dataset does not contain the VNIR 3B (aft-viewing) Band.  * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL02.v005",
-        "title": "ATLAS/ICESat-2 L1B Converted Telemetry Data V005",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153572246-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153572246-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL02.v005",
-        "description": "This data set (ATL02) contains science unit-converted, time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system\u2013level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and the Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL02.v006",
-        "title": "ATLAS/ICESat-2 L1B Converted Telemetry Data V006",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL02.v006",
-        "description": "This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL03.v005",
-        "title": "ATLAS/ICESat-2 L2A Global Geolocated Photon Data V005",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153572325-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153572325-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL03.v005",
-        "description": "This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL03.v006",
-        "title": "ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL03.v006",
-        "description": "This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL04.v005",
-        "title": "ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V005",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153572406-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153572406-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL04.v005",
-        "description": "ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL04.v006",
-        "title": "ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL04.v006",
-        "description": "ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL09.v005",
-        "title": "ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V005",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153574732-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153574732-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL09.v005",
-        "description": "This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL09.v006",
-        "title": "ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL09.v006",
-        "description": "This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL13.v005",
-        "title": "ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V005",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153575088-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153575088-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL13.v005",
-        "description": "This data set (ATL13) contains along-track surface water products for inland water bodies.  Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).",
-        "license": "not-provided"
-    },
-    {
-        "id": "ATL13.v006",
-        "title": "ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006",
-        "catalog": "NSIDC_CPRD",
-        "state_date": "2018-10-13",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL13.v006",
-        "description": "This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).",
-        "license": "not-provided"
-    },
     {
         "id": "ATSMIGEO.v002",
         "title": "MISR Geometric Parameters subset for the ARCTAS region V002",
@@ -1871,32 +1481,6 @@
         "description": "Measurements in the Gulf Stream off the East Coast of the US in 2001",
         "license": "not-provided"
     },
-    {
-        "id": "AgriFieldNet Competition Dataset.v1",
-        "title": "AgriFieldNet Competition Dataset",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "76.2448319, 18.9414403, 88.0460054, 28.3269976",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412563-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412563-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/AgriFieldNet Competition Dataset.v1",
-        "description": "This dataset contains crop types of agricultural fields in four states of Uttar Pradesh, Rajasthan, Odisha and Bihar in northern India. There are 13 different classes in the dataset including Fallow land and 12 crop types of Wheat, Mustard, Lentil, Green pea, Sugarcane, Garlic, Maize, Gram, Coriander, Potato, Bersem, and Rice. The dataset is split to train and test collections as part of the AgriFieldNet India Competition. Ground reference data for this dataset is collected by IDinsight\u2019s [Data on Demand](https://www.idinsight.org/services/data-on-demand/) team. Radiant Earth Foundation carried out the training dataset curation and publication. This training dataset is generated through a grant from the Enabling Crop Analytics at Scale ([ECAAS](https://cropanalytics.net/)) Initiative funded by [The Bill & Melinda Gates Foundation](https://www.gatesfoundation.org/) and implemented by [Tetra Tech](https://www.tetratech.com/).",
-        "license": "not-provided"
-    },
-    {
-        "id": "BigEarthNet.v1",
-        "title": "BigEarthNet",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "-9.0002335, 36.9569567, 31.5984391, 68.021682",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412035-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412035-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/BigEarthNet.v1",
-        "description": "BigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe were initially selected. All the tiles were atmospherically corrected by the Sentinel-2 Level 2A product generation and formatting tool (sen2cor). Then, they were divided into 590,326 non-overlapping image patches. Each image patch was annotated by the multiple land-cover classes (i.e., multi-labels) that were provided from the CORINE Land Cover database of the year 2018 (CLC 2018).",
-        "license": "not-provided"
-    },
     {
         "id": "C1_PANA_STUC00GTD.v1",
         "title": "Cartosat-1 PANA Standard Products",
@@ -2248,45 +1832,6 @@
         "description": "The Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) NASA Level-2 (L2) Cloud Mask is one of two continuity products designed to sustain the long-term records of both Moderate Resolution Imaging Spectroradiometer (MODIS) and VIIRS heritages. CLDMSK_L2_VIIRS_SNPP is the shortname for the SNPP VIIRS incarnation of the Cloud Mask continuity product derived from the MODIS-VIIRS cloud mask (MVCM) algorithm, which itself is based on the MODIS (MOD35) algorithm. MVCM describes a continuity algorithm that is central to both MODIS data (from Terra and Aqua missions) and VIIRS data (from SNPP and Joint Polar Satellite System missions). Please bear in mind that the term MVCM does not appear as an attribute within the product\u2019s metadata. Implemented to consistently handle MODIS and VIIRS inputs, the SNPP VIIRS collection-1 products use calibration-adjusted NASA VIIRS L1B as inputs. The nominal spatial resolution of the SNPP VIIRS L2 Cloud mask is 750 meters.",
         "license": "not-provided"
     },
-    {
-        "id": "COARE_cm_er2.mas.v1",
-        "title": "MODIS Airborne Simulator (MAS) Measurements Taken Onboard the NASA ER-2 During the TOGA COARE Intensive Observing Period.",
-        "catalog": "LAADS",
-        "state_date": "1993-01-03",
-        "end_date": "1993-03-04",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1625703857-LAADS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1625703857-LAADS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/COARE_cm_er2.mas.v1",
-        "description": "The MODIS Airborne Simulator (MAS) Measurements, taken onboard the NASA ER-2 during the TOGA COARE Intensive Observing Period, are available upon request from NASA LAADS. Browse products are available at https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/mas/. The ER-2 navigation data are available from the same site in sub directory nasa_er2/nav. Browse imagery of the data may be viewed from the MAS Homepage at: https://mas.arc.nasa.gov/data/deploy_html/toga_home.html. MAS Level 1B data are available on 8500 density 8mm tape from TOGA COARE User Services at the Goddard DAAC.  Each tape contains all the flight lines for one MAS flight (one day). The number of flight lines varies, but is generally between 10 and 20. The volume of data varies, but is generally 1 to 3 gigabytes per flight.  Detailed instructions for reading MAS tapes is contained in MAS_Usr_Guide.ps. To obtain the data on tape, contact the DAAC User Services Office.  For help with NASA TOGA COARE data residing at the GSFC DAAC, contact Pat Hrubiak at hrubiak@daac.gsfc.nasa.gov.   BACK GROUND: TOGA COARE was a multidisciplinary, international research effort that investigated the scientific phenomena associated with the interaction between the atmosphere and the ocean in the warm pool region of the western Pacific. The field experiment phase of the program took place from 1 November 1992 through 28 February 1993 and involved the deployment of oceanographic ships and buoys, several ship and land based Doppler radars, multiple low and high level aircraft equipped with Doppler radar and other airborne sensors, as well as a variety of surface based instruments for in situ observations. The NASA component of TOGA COARE, while contributing directly to over all COARE objectives, emphasized scientific objectives associated with the Tropical Rainfall Measuring Mission (TRMM) and NASA's cloud and radiation program.  AIRCRAFT INFORMATION: The NASA ER-2 is a high altitude, single pilot aircraft based at Ames Research Center, Moffett Field, CA, and deployed globally in support of a variety of atmospheric research projects. It has a maximum altitude of 70,000 feet (21 km), a range of 3000 nautical miles, a maximum flight duration of 8 hours (nominal 6.5 hours) and a top speed of 410 knots true air speed. The aircraft accommodates about 2700 pounds (1200 kg) of payload.  For the TOGA COARE campaign, the ER-2 payload consisted of a variety of radiometers, a lidar, a conductivity probe and a camera.   FLIGHT INFORMATION: The following table relates MAS data files to ER-2 and DC-8 flight numbers and to the UTC dates for the 13 mission flights of the NASA/TOGA COARE campaign and 2 additional flights of the ER-2 on which MAS data was acquired. The objectives (Obj) column is included for the convenience of the user; the mission objective defaulted to radiation (Rad) unless convection (Con) was forecast in the target area. Date (UTC) ER-2 Flight DC-8 Flight MAS TapeID Obj-Jan 11-12  93-053  93-01-06 93-053 RadJan 17-18 93-054 93-01-07 93-054 Con Jan 18-19 93-055 93-01-08 93-055 Con Jan 25-26 93-056 93-01-09 93-056 RadJan 28-29 93-057 93-057 Jan 31-Feb 1 93-058 93-01-10 93-058 Rad Feb 2 93-059 93-059 Feb 4 93-060 93-01-11 93-060 Con Feb 6 93-01-12 Con Feb 7 93-061 93-061 Feb 8-9 93-062 93-01-13 93-062 Con Feb 10-11 93-063 93-01-14 93-063 Con Feb 17-18 93-01-15 93-064 Con Feb 19-20 93-064 93-064 Feb 20-21 93-065 93-01-16 93-065 Con Feb 22-23 93-066 93-01-17 Con Feb 23-24 93-067 93-01-18 Rad.   INSTRUMENT INFORMATION: The MODIS Airborne Simulator is a visible/infrared imaging radiometer that was mounted, for this campaign, in the right aft wing pod of the ER-2 aircraft. Through cross track scanning to the aircraft direction of flight, the MAS instrument builds a continuous sequence image of the atmosphere surface features under the aircraft. Wavelength channels of the instrument are selected for specific cloud and surface remote sensing applications. Also the channels are those which will be incorporated in measurements by the space borne MODIS instrument. The MAS instrument acquires eleven simultaneous wavelengths with 100 meters or better resolution at the surface.   Principles of Operation: The MAS Spectrometer acquires high spatial resolution imagery in the wavelength range 0.55 to 14.3 microns. A total of 50 spectral bands are available in this range, and currently the digitize is configured before each mission to record in any 12 of these bands during flight. For all pre-1994 MAS missions, the 12-channel digitize was configured with four 10-bit channels and seven 8-bit channels. The MAS spectrometer is mated to a scanner sub-assembly which collects image data with an IFOV of 2.5 mrad, giving a ground resolution of 50 meters from 20,000 meters altitude,and a cross track scan width of 85.92 degrees. A 50 channel digitizer which records all 50 spectral bands at 12 bit resolution became operational in January 1995.   DATA ORGANIZATION Data Format: The archive tapes are created by writing each output data file (1 straight-line flight track) to tape in fixed-length blocks of 16384 bytes, in time ascending order. One end-of-file (EOF) mark is written at the end of the data blocks for each file, and an extra EOF is written at the end of the data on the tape.  The last block of each file has good data at the start of the block and unused bytes (filled with null characters) at the end. Information on the length of the file is encoded in the header when the file is created. No file name,protection, or ownership information is written onto the archive tape. All information necessary to identify the file is stored in the file itself.  Documentation:  In addition to this document, please obtain Volume 3, MODIS Airborne Simulator Level 1B Data Users Guide, resident in this directory in postscript file MAS_Usr_Guide.ps.   Browse Products: There are 2 GIF image files per flight line, named 93ddd??v.gif and 93ddd??i.gif, where 93 is the year, ddd the Julian day of the flight, ?? the flight line number, and v or i, indicating respectively visible (VIS) or Infrared (IR) imagery. Images from each flight, accompanied by a flight statistics summary file, reside in a sub directory named with the date of the flight (02feb93) under mas/images.",
-        "license": "not-provided"
-    },
-    {
-        "id": "CSU Synthetic Attribution Benchmark Dataset.v1",
-        "title": "CSU Synthetic Attribution Benchmark Dataset",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "-179.5, -89.5, 179.5, 89.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781411899-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781411899-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/CSU Synthetic Attribution Benchmark Dataset.v1",
-        "description": "This is a synthetic dataset that can be used by users that are interested in benchmarking methods of explainable artificial intelligence (XAI) for geoscientific applications. The dataset is specifically inspired from a climate forecasting setting (seasonal timescales) where the task is to predict regional climate variability given global climate information lagged in time. The dataset consists of a synthetic input X (series of 2D arrays of random fields drawn from a multivariate normal distribution) and a synthetic output Y (scalar series) generated by using a nonlinear function F: R^d -> R.<br><br>The synthetic input aims to represent temporally independent realizations of anomalous global fields of sea surface temperature, the synthetic output series represents some type of regional climate variability that is of interest (temperature, precipitation totals, etc.) and the function F is a simplification of the climate system.<br><br>Since the nonlinear function F that is used to generate the output given the input is known, we also derive and provide the attribution of each output value to the corresponding input features. Using this synthetic dataset users can train any AI model to predict Y given X and then implement XAI methods to interpret it. Based on the \u201cground truth\u201d of attribution of F the user can assess the faithfulness of any XAI method.<br><br>NOTE: the spatial configuration of the observations in the NetCDF database file conform to the planetocentric coordinate system (89.5N - 89.5S, 0.5E - 359.5E), where longitude is measured in the positive heading east from the prime meridian.",
-        "license": "not-provided"
-    },
-    {
-        "id": "CV4A Kenya Crop Type Competition.v1",
-        "title": "CV4A Kenya Crop Type Competition",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "34.0220685, 0.1670219, 34.38443, 0.7160466",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412688-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412688-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/CV4A Kenya Crop Type Competition.v1",
-        "description": "This dataset was produced as part of the [Crop Type Detection competition](https://zindi.africa/competitions/iclr-workshop-challenge-2-radiant-earth-computer-vision-for-crop-recognition) at the [Computer Vision for Agriculture (CV4A) Workshop](https://www.cv4gc.org/cv4a2020/) at the ICLR 2020 conference. The objective of the competition was to create a machine learning model to classify fields by crop type from images collected during the growing season by the Sentinel-2 satellites. <br><br> The ground reference data were collected by the PlantVillage team, and Radiant Earth Foundation curated the training dataset after inspecting and selecting more than 4,000 fields from the original ground reference data. The dataset has been split into training and test sets (3,286 in the train and 1,402 in the test). <br><br> The dataset is cataloged in four tiles. These tiles are smaller than the original Sentinel-2 tile that has been clipped and chipped to the geographical area that labels have been collected. <br><br> Each tile has a) 13 multi-band observations throughout the growing season. Each observation includes 12 bands from Sentinel-2 L2A product, and a cloud probability layer. The twelve bands are [B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12]. The cloud probability layer is a product of the Sentinel-2 atmospheric correction algorithm (Sen2Cor) and provides an estimated cloud probability (0-100%) per pixel. All of the bands are mapped to a common 10 m spatial resolution grid.; b) A raster layer indicating the crop ID for the fields in the training set; and c) A raster layer indicating field IDs for the fields (both training and test sets). Fields with a crop ID of 0 are the test fields.",
-        "license": "not-provided"
-    },
     {
         "id": "CWIC_REG.v1.0",
         "title": "Radarsat-2 Scenes, Natural Resources Canada",
@@ -2339,32 +1884,6 @@
         "description": "Measurements made in the Arctic Ocean by the RV Catlin in 2011.",
         "license": "not-provided"
     },
-    {
-        "id": "Chesapeake Land Cover.v1",
-        "title": "Chesapeake Land Cover",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "-80.8092703, 36.5643108, -74.2529408, 43.9973515",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412641-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412641-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/Chesapeake Land Cover.v1",
-        "description": "This dataset contains high-resolution aerial imagery from the USDA NAIP program, high-resolution land cover labels from the Chesapeake Conservancy, low-resolution land cover labels from the USGS NLCD 2011 dataset, low-resolution multi-spectral imagery from Landsat 8, and high-resolution building footprint masks from Microsoft Bing, formatted to accelerate machine learning research into land cover mapping. The Chesapeake Conservancy spent over 10 months and $1.3 million creating a consistent six-class land cover dataset covering the Chesapeake Bay watershed. While the purpose of the mapping effort by the Chesapeake Conservancy was to create land cover data to be used in conservation efforts, the same data can be used to train machine learning models that can be applied over even wider areas.",
-        "license": "not-provided"
-    },
-    {
-        "id": "Cloud to Street - Microsoft flood dataset.v1",
-        "title": "Cloud to Street - Microsoft flood dataset",
-        "catalog": "MLHUB",
-        "state_date": "2020-01-01",
-        "end_date": "2023-01-01",
-        "bbox": "-96.631888, -25.250962, 141.118143, 48.745167",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412798-MLHUB.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412798-MLHUB.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/MLHUB/collections/Cloud to Street - Microsoft flood dataset.v1",
-        "description": "The C2S-MS Floods Dataset is a dataset of global flood events with labeled Sentinel-1 & Sentinel-2 pairs. There are 900 sets (1800 total) of near-coincident Sentinel-1 and Sentinel-2 chips (512 x 512 pixels) from 18 global flood events. Each chip contains a water label for both Sentinel-1 and Sentinel-2, as well as a cloud/cloud shadow mask for Sentinel-2. The dataset was constructed by Cloud to Street in collaboration with and funded by the Microsoft Planetary Computer team.",
-        "license": "not-provided"
-    },
     {
         "id": "DLG100K",
         "title": "1:100,000-scale Digital Line Graphs (DLG) from the U.S. Geological Survey",
@@ -2950,58 +2469,6 @@
         "description": "Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Geometric Parameters subset for the GoMACCS region V002 contains the Geometric Parameters which measure the sun and view angles at the reference ellipsoid.",
         "license": "not-provided"
     },
-    {
-        "id": "Global_Litter_Carbon_Nutrients_1244.v1",
-        "title": "A Global Database of Litterfall Mass and Litter Pool Carbon and Nutrients",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1827-01-01",
-        "end_date": "1997-12-31",
-        "bbox": "-156.7, -54.5, 176.2, 72.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784385713-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784385713-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/Global_Litter_Carbon_Nutrients_1244.v1",
-        "description": "Measurement data of aboveground litterfall and littermass and litter carbon, nitrogen, and nutrient concentrations were extracted from 685 original literature sources and compiled into a comprehensive database to support the analysis of global patterns of carbon and nutrients in litterfall and litter pools. Data are included from sources dating from 1827 to 1997. The reported data include the literature reference, general site information (description, latitude, longitude, and elevation), site climate data (mean annual temperature and precipitation), site vegetation characteristics (management, stand age, ecosystem and vegetation-type codes), annual quantities of litterfall (by class, kg m-2 yr-1), litter pool mass (by class and litter layer, kg m-2), and concentrations of nitrogen (N), phosphorus (P), and base cations for the litterfall (g m-2 yr-1) and litter pool components (g m-2).  The investigators intent was to compile a comprehensive data set of individual direct field measurements as reported by researchers. While the primary emphasis was on acquiring C data, measurements of N, P, and base cations were also obtained, although the database is sparse for elements other than C and N. Each of the 1,497 records in the database represents a measurement site. Replicate measurements were averaged according to conventions described in Section 5 and recorded for each site in the database. The sites were at 575 different locations. ",
-        "license": "not-provided"
-    },
-    {
-        "id": "Global_Microbial_Biomass_C_N_P_1264.v1",
-        "title": "A Compilation of Global Soil Microbial Biomass Carbon, Nitrogen, and Phosphorus Data",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1977-11-16",
-        "end_date": "2012-06-01",
-        "bbox": "-180, -90, 177.9, 79",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863966-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863966-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/Global_Microbial_Biomass_C_N_P_1264.v1",
-        "description": "This data set provides the concentrations of soil microbial biomass carbon (C), nitrogen (N) and phosphorus (P), soil organic carbon, total nitrogen, and total phosphorus at biome and global scales. The data were compiled from a comprehensive survey of publications from the late 1970s to 2012 and include 3,422 data points from 315 papers. These data are from soil samples collected primarily at 0-15 cm depth with some from 0-30 cm. In addition, data were compiled for soil microbial biomass concentrations from soil profile samples to depths of 100 cm. Sampling site latitude and longitude were available for the majority of the samples that enabled assembling additional soil properties, site characteristics, vegetation distributions, biomes, and long-term climate data from several global sources of soil, land-cover, and climate data. These site attributes are included with the microbial biomass data. This data set contains two *.csv files of the soil microbial biomass C, N, P data. The first provides all compiled results emphasizing the full spatial extent of the data, while the second is a subset that provides only data from a series of profile samples emphasizing the vertical distribution of microbial biomass concentrations.There is a companion file, also in .csv format, of the references for the surveyed publications. A reference_number relates the data to the respective publication.The concentrations of soil microbial biomass, in combination with other soil databases, were used to estimate the global storage of soil microbial biomass C and N in 0-30 cm and 0-100 cm soil profiles. These storage estimates were combined with a spatial map of 12 major biomes (boreal forest, temperate coniferous forest, temperate broadleaf forest, tropical and subtropical forests, mixed forest, grassland, shrub, tundra, desert, natural wetland, cropland, and pasture) at 0.05-degree by 0.5-degree spatial resolution. The biome map and six estimates of C and N storage and C:N ration in soil microbial biomass are provided in a single netCDF format file. ",
-        "license": "not-provided"
-    },
-    {
-        "id": "Global_Phosphorus_Hedley_Fract_1230.v1",
-        "title": "A Global Database of Soil Phosphorus Compiled from Studies Using Hedley Fractionation",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1985-01-01",
-        "end_date": "2010-12-31",
-        "bbox": "-117.86, -42.5, 117.6, 63.23",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863440-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863440-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/Global_Phosphorus_Hedley_Fract_1230.v1",
-        "description": "This data set provides concentrations of soil phosphorus (P) compiled from the peer-reviewed literature that cited the Hedley fractionation method (Hedley and Stewart, 1982). This database contains estimates of different forms of naturally occurring soil phosphorus, including labile inorganic P, organic P, occluded P, secondary mineral P, apatite P, and total P, based on the analyses of the various Hedley soil fractions.The recent literature survey (Yang and Post, 2011) was restricted to studies of natural, unfertilized, and uncultivated soils since 1995. Ninety measurements of soil P fractions were identified. These were added to the 88 values from soils in natural ecosystems that Cross and Schlesinger (1995) had compiled. Cross and Schlesinger provided a comprehensive survey on Hedley P data prior to 1995. Measurement data are provided for studies published from 1985 through 2010. In addition to the Hedley P fraction measurement data Yang and Post (2011) also compiled information on soil order, soil pH, organic carbon and nitrogen content, as well as the geographic location (longitude and latitude) of the measurement sites. ",
-        "license": "not-provided"
-    },
-    {
-        "id": "Global_RTSG_Flux_1078.v1",
-        "title": "A Global Database of Gas Fluxes from Soils after Rewetting or Thawing, Version 1.0",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1956-01-01",
-        "end_date": "2009-12-31",
-        "bbox": "-149.63, -36.45, 160.52, 74.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863284-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863284-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/Global_RTSG_Flux_1078.v1",
-        "description": "This database contains information compiled from published studies on gas flux from soil following rewetting or thawing. The resulting database includes 222 field and laboratory observations focused on rewetting of dry soils, and 116 field laboratory observations focused on thawing of frozen soils studies conducted from 1956 to 2010. Fluxes of carbon dioxide, methane, nitrous oxide, nitrogen oxide, and ammonia (CO2, CH4, N2O, NO and NH3) were compiled from the literature and the flux rates were normalized for ease of comparison. Field observations of gas flux following rewetting of dry soils include events caused by natural rainfall, simulated rainfall in natural ecosystems, and irrigation in agricultural lands. Similarly, thawing of frozen soils include field observations of natural thawing, simulated freezing-thawing events (i.e., thawing of simulated frozen soil by snow removal), and thawing of seasonal ice in temperate and high latitude regions (Kim et al., 2012). Reported parameters include experiment type, location, site type, vegetation, climate, soil properties, rainfall, soil moisture, soil gas flux after wetting and thawing, peak soil gas flux properties, and the corresponding study references. There is one comma-delimited data file. ",
-        "license": "not-provided"
-    },
     {
         "id": "GreenBay.v0",
         "title": "2010 Measurements made in Green Bay, Wisconsin",
@@ -3262,19 +2729,6 @@
         "description": "The Level 2C wind product of the Aeolus mission provides ECMWF analysis horizontal wind vectors at the geolocations of assimilated L2B HLOS wind components.  The L2C can therefore be described as an Aeolus-assisted horizontal wind vector product. The L2C is a distinct product, however the L2C and L2B share a common Earth Explorer file template, with the L2C being a superset of the L2B.  The L2C consists of extra datasets appended to the L2B product with information which are relevant to the data assimilation of the L2B winds.",
         "license": "not-provided"
     },
-    {
-        "id": "LAI_Woody_Plants_1231.v1",
-        "title": "A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1932-01-01",
-        "end_date": "2011-12-31",
-        "bbox": "-164.78, -54.2, 175.62, 78.42",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784385653-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784385653-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/LAI_Woody_Plants_1231.v1",
-        "description": "This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources.",
-        "license": "not-provided"
-    },
     {
         "id": "LGB_10m_traverse.v1",
         "title": "10 m firn temperature data: LGB traverses 1990-95",
@@ -3288,32 +2742,6 @@
         "description": "The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. Ten metre depth (10 m) firn temperatures, as a proxy indicator of annual mean surface temperature at a site, were recorded approximately every 30 km along the 2014 km main traverse route from LGB00 (68.6543 S, 61.1201 E) near Mawson Station, to LGB72 (69.9209 S, 76.4933 E) near Davis Station.  10 m depth firn temperatures were recorded manually in field notebooks and the data transferred to spreadsheet files (MS Excel).  Summary data (30 km spatial resolution) can be obtained from CRC Research Note No.09 'Surface Mass Balance and Snow Surface Properties from the Lambert Glacier Basin Traverses 1990-94'.  This work was completed as part of ASAC projects 3 and 2216.  Some of this data have been stored in a very old format.  The majority of files have been updated to current formats, but some files (kaleidograph files in particular) were not able to be modified due to a lack of appropriate software.  However, these files are simply figures, and can be regenerated from the raw data (also provided).  The fields in this dataset are:  Latitutde Longitude Height Cane Distance Elevation Density Mass Accumulation Year Delta Oxygen-18 Grain Size Ice Crusts Depth Hoar",
         "license": "not-provided"
     },
-    {
-        "id": "Leaf_Carbon_Nutrients_1106.v1",
-        "title": "A Global Database of Carbon and Nutrient Concentrations of Green and Senesced Leaves",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1970-01-01",
-        "end_date": "2009-12-31",
-        "bbox": "-159.7, -50, 176.9, 68.5",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383820-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383820-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/Leaf_Carbon_Nutrients_1106.v1",
-        "description": "This data set provides carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations in green and senesced leaves. Vegetation characteristics reported include species growth habit, leaf area, mass, and mass loss with senescence. The data were compiled from 86 selected studies in 31 countries, and resulted in approximately 1,000 data points for both green and senesced leaves from woody and non-woody vegetation as described in Vergutz et al (2012). The studies were conducted from 1970-2009. There are two comma-delimited data files with this data set.",
-        "license": "not-provided"
-    },
-    {
-        "id": "Leaf_Photosynthesis_Traits_1224.v1",
-        "title": "A Global Data Set of Leaf Photosynthetic Rates, Leaf N and P, and Specific Leaf Area",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1993-01-01",
-        "end_date": "2010-12-31",
-        "bbox": "-122.4, -43.2, 176.13, 58.42",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784384781-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784384781-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/Leaf_Photosynthesis_Traits_1224.v1",
-        "description": "This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file.",
-        "license": "not-provided"
-    },
     {
         "id": "Level_2A_aerosol_cloud_optical_products",
         "title": "Aeolus L2A Aerosol/Cloud optical product",
@@ -3379,19 +2807,6 @@
         "description": "The combined MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product\u2019s short-name.  The \u201cCOSP\u201d acronym in its short-name stands for  Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. This product is an aggregation of combined MODIS Level-2 inputs from both the Terra and Aqua incarnations (MOD35/MOD06 and MYD35/MYD06, respectively), and employs an aggregation methodology consistent with the MOD08 and MYD08 products.  Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters).",
         "license": "not-provided"
     },
-    {
-        "id": "MCD06COSP_M3_MODIS.v6.1",
-        "title": "MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid",
-        "catalog": "LAADS",
-        "state_date": "2002-07-01",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1888024429-LAADS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1888024429-LAADS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/MCD06COSP_M3_MODIS.v6.1",
-        "description": "The combined MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product\u2019s short-name.  The \u201cCOSP\u201d acronym in its short-name stands for  Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. The L3 monthly product is derived by aggregating the daily-produced Aqua+Terra/MODIS D3 Cloud Properties product (MCD06COSP_D3_MODIS).  Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters).",
-        "license": "not-provided"
-    },
     {
         "id": "MCD14DL_C5_NRT.v005",
         "title": "MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT",
@@ -3548,19 +2963,6 @@
         "description": "The new Collection 6.1 (C61) MYD04_3K product is an improved version based on algorithm changes in Dark Target (DT) Aerosol retrieval over urban areas and uncertainty estimates for Deep Blue (DB) Aerosol retrievals.  The MODIS level-2 atmospheric aerosol product provides retrieved ambient aerosol optical properties, quality assurance, and other parameters, globally over ocean and land. In Collection 5, and earlier collections, there was only one aerosol product (MOD04_L2) at 10km (at nadir) spatial resolution. Starting from C6, the Dark Target (DT) Aerosol algorithm team provided a new 3 km spatial resolution product (MOD04_3k) intended for the air quality community.  The MOD04_3K product is based on the same algorithm and Look up Tables as the standard Dark Target aerosol product. Because of finer resolution, subtle differences are made in selecting pixels for retrieval and in determining QA. The only differences between the existing 10km algorithm and the 3km algorithm are: 1) the size of the pixel-arrays defining each retrieval box (6x6 retrieval boxes of 36 pixels at 0.5km resolution for 3km algorithm as oppose to 20x20 retrieval boxes of 400 pixels at 0.5km resolution for 10km product); 2) the minimum percentage of good pixels required for a retrieval (a minimum of 5 pixels over ocean and 6 pixels over land instead of a minimum of 10 pixels over ocean or 12 pixels over land for 10km product retrieval); 3) the 10km algorithm attempts a poor quality retrieval while 3km algorithm does not. Everything else is same in two products.  For more information on C6.1 changes and updates, visit the MODIS Atmosphere website at: https://modis-atmosphere.gsfc.nasa.gov/documentation/collection-61",
         "license": "not-provided"
     },
-    {
-        "id": "MYD04_L2.v6.1",
-        "title": "MODIS/Aqua Aerosol 5-Min L2 Swath 10km",
-        "catalog": "LAADS",
-        "state_date": "2002-07-04",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1443533683-LAADS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1443533683-LAADS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/MYD04_L2.v6.1",
-        "description": "The MODIS/Aqua Aerosol 5-Min L2 Swath 10km product (MYD04_L2) provides full global coverage of aerosol properties from the Dark Target (DT) and Deep Blue (DB) algorithms. The DT algorithm is applied over ocean and dark land (e.g., vegetation), while the DB algorithm now covers the entire land areas including both dark and bright surfaces. Both results are provided on a 10x10 pixel scale (10 km at nadir). Each MYD04_L2 product file covers a five-minute time interval. The output grid is 135 pixels in width by 203 pixels in length. Every tenth file has an output grid size of 135 by 204 pixels. MYD04_L2 product files are stored in Hierarchical Data Format (HDF-EOS).    The new Collection 6.1 (C61) MYD04_L2 product is an improved version based on algorithm changes in Dark Target (DT) Aerosol retrieval over urban areas and uncertainty estimates for Deep Blue (DB) Aerosol retrievals.    The MODIS level-2 atmospheric aerosol product provides retrieved ambient aerosol optical properties, quality assurance, and other parameters, globally over ocean and land. In Collection 5 and in earlier collections, there was only one aerosol product (MYD04_L2) at 10km (at nadir) spatial resolution. Starting from C6, the Dark Target (DT) Aerosol algorithm team provided a new 3 km spatial resolution product (MYD04_3k) intended for the air quality community.      For more information visit the MODIS Atmosphere website at:  https://modis-atmos.gsfc.nasa.gov/products/aerosol    And, for C6.1 changes and updates, visit:  https://modis-atmosphere.gsfc.nasa.gov/documentation/collection-61",
-        "license": "not-provided"
-    },
     {
         "id": "MYD04_L2.v6.1NRT",
         "title": "MODIS/Aqua Aerosol 5-Min L2 Swath 10km - NRT",
@@ -3600,19 +3002,6 @@
         "description": "The MODIS/Aqua Aerosol Optical Thickness Daily L3 Global 0.05-Deg CMA Near Real Time (NRT), short name MYD09CMA, is a daily level 3 global product. It is in linear latitude and longitude (Plate Carre) projection with a 0.05Deg spatial resolution. This product is derived from MYD09IDN, MYD09IDT and MYD09IDS for each orbit by compositing the data on the basis of minimum band 3 (459 - 479 nm band) values (after excluding pixels flagged for clouds and high solar zenith angles).",
         "license": "not-provided"
     },
-    {
-        "id": "MYDCSR_B.v6.1",
-        "title": "MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands",
-        "catalog": "LAADS",
-        "state_date": "2002-07-04",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1444160046-LAADS.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1444160046-LAADS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/MYDCSR_B.v6.1",
-        "description": "The MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands (MYDCSR_B) product consists of 1-degree zonal mean clear-sky biases (observed minus calculated radiance differences) and associated statistics for bands 31 and 33-36 for each day from the previous eight-day period. Zonal means (5-zone moving averages) are created from the eight-day, 25-km radiance differences for daytime land, nighttime land, and ocean data separately. Day and night land data are combined south of -60 degrees latitude due to poor clear-sky sampling and the difficulty of discriminating between clear and cloudy conditions in this region. The zonal mean biases are utilized to correct clear-sky radiance calculations in the cloud top pressure (CO2 slicing) algorithm. The files are in Hierarchical Data Format (HDF).",
-        "license": "not-provided"
-    },
     {
         "id": "MYDGB0.v6.1NRT",
         "title": "MODIS/Aqua 5-minute GBAD data in L0 format - NRT",
@@ -4185,19 +3574,6 @@
         "description": "This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14\u00b0N 144\u00b0E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington.",
         "license": "not-provided"
     },
-    {
-        "id": "SRDB_V5_1827.v5",
-        "title": "A Global Database of Soil Respiration Data, Version 5.0",
-        "catalog": "ORNL_CLOUD",
-        "state_date": "1961-01-01",
-        "end_date": "2017-12-31",
-        "bbox": "-163.71, -78.02, 175.9, 81.8",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864433-ORNL_CLOUD.json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864433-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections/SRDB_V5_1827.v5",
-        "description": "The Soil Respiration Database (SRDB) is a near-universal compendium of published soil respiration (Rs) data. The database encompasses published studies that report at least one of the following data measured in the field (not laboratory): annual soil respiration, mean seasonal soil respiration, a seasonal or annual partitioning of soil respiration into its source fluxes, soil respiration temperature response (Q10), or soil respiration at 10 degrees C. The SRDB's orientation is to seasonal and annual fluxes, not shorter-term or chamber-specific measurements, and the database is dominated by temperate, well-drained forest measurement locations. Version 5 (V5) is the compilation of 2,266 published studies with measurements taken between 1961-2017. V5 features more soil respiration data published in Russian and Chinese scientific literature for better global spatio-temporal coverage and improved global climate-space representation. The database is also restructured to have better interoperability with other datasets related to carbon-cycle science.",
-        "license": "not-provided"
-    },
     {
         "id": "SeaWiFS_L2_GAC_OC.vR2022.0",
         "title": "OrbView-2 SeaWiFS Regional Global Area Coverage (GAC) Ocean Color (OC) Data, version R2022.0",
diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv
index 37b943b9b3..790eca2a9e 100644
--- a/nasa_cmr_catalog.tsv
+++ b/nasa_cmr_catalog.tsv
@@ -6,7 +6,6 @@ id	title	catalog	state_date	end_date	bbox	url	description	license
 12_hourly_interpolated_surface_air_pressure_from_buoys	12 Hourly Interpolated Surface Air Pressure from Buoys	SCIOPS	1979-01-01	2007-11-30	-180, 70, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.json	Optimally interpolated atmospheric surface pressure over the Arctic Ocean Basin. Temporal format - twice daily (0Z and 12Z) Spatial format - 2 degree latitude x 10 degree longitude - latitude: 70 N - 90 N - longitude: 0 E - 350 E	not-provided
 14c_of_soil_co2_from_ipy_itex_cross_site_comparison	14C of soil CO2 from IPY ITEX Cross Site Comparison	SCIOPS	2008-01-16	2008-01-21	-157.4, -36.9, 147.29, 71.3	https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.json	Study sites: Toolik Lake Field Station Alaska, USA 68.63 N, 149.57 W; Atqasuk, Alaska USA 70.45 N, 157.40 W; Barrow, Alaska, USA 71.30 N, 156.67 W; Latnjajaure, Sweden 68.35 N, 18.50 E; Falls Creek, Australia: Site 2-unburned 36.90 S 147.29 E; Site 3-burned 36.89 S 147.28 E. Additional sites will be added summer 2008, but the exact sites are not finalized. Purpose: Collect soil CO2 for analysis of radiocarbon to evaluate the age of the carbon respired in controls and warmed plots from across the ITEX network.  Treatments: control and ITEX OTC warming experiment (1994-2007). Design: 5 replicates of each treatment at dry site and moist site. Sampling frequency: Once per peak season.	not-provided
 200708_CEAMARC_CASO_TRACE_ELEMENT_SAMPLES.v1	2007-08 CEAMARC-CASO VOYAGE TRACE ELEMENT SAMPLING AROUND AN ICEBERG	AU_AADC	2008-01-01	2008-03-20	139.01488, -67.07104, 150.06479, -42.88246	https://cmr.earthdata.nasa.gov/search/concepts/C1214305618-AU_AADC.json	We collected surface seawater samples using trace clean 1L Nalgene bottles on the end of a long bamboo pole.   We will analyse these samples for trace elements.  Iron is the element of highest interest to our group.  We will determine dissolved iron and total dissolvable iron concentrations.    Samples collected from 7 sites:   Sites 1, 2, 3, 4 were a transect perpendicular to the edge of the iceberg to try and determine if there is a iron concentration gradient relative to the iceberg.   Sites 4, 5, 6 were along the edge of the iceberg to determine if there is any spatial variability along the iceberg edge.  Site 7 was away from the iceberg to determine what the iron concentration is in the surrounding waters not influenced by the iceberg.	not-provided
-2019 Mali CropType Training Data.v1	2019 Mali CropType Training Data	MLHUB	2020-01-01	2023-01-01	-6.9444015, 12.8185552, -6.5890481, 13.3734391	https://cmr.earthdata.nasa.gov/search/concepts/C2781412344-MLHUB.json	 This dataset produced by the NASA Harvest team includes crop types labels from ground referencing matched with time-series of Sentinel-2 imagery during the growing season. Ground reference data are collected using an ODK app. Crop types include Maize, Millet, Rice and Sorghum. Labels are vectorized over the Sentinel-2 grid, and provided as raster files. Funding for this dataset is provided by Lutheran World Relief, Bill & Melinda Gates Foundation, and University of Maryland NASA Harvest program.	not-provided
 39480	1988 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve	NOAA_NCEI	1988-11-24	1988-11-24	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2102656753-NOAA_NCEI.json	Aerial photographs taken by NOAA's National Geodetic Survey during 1988 were mosaicked and orthorectified by the Biogeography Branch.   The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and extends beyond the park boundaries approximately 0.5 - 4.0 km.	not-provided
 39481	1988 Seagrass and Mangrove Habitats of the Salt River Bay National Historical Park and Ecological Preserve	NOAA_NCEI	1988-11-24	1988-11-24	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2102656462-NOAA_NCEI.json	Habitat maps were created as part of a larger ecological assessment conducted by NOAA's National Ocean Service (NOS), Biogeography Branch, for Salt River Bay National Historic Park and Ecological Preserve (National Park Service).Aerial photographs were obtained for 1988 from the National Geodetic Survey, and were orthorectified by the Biogeography Branch.  A classification scheme was set up with 20 benthic habitat types, 19 land cover types, and 13 mangrove habitat types.  For this map of seagrass and mangrove habitats during 1988 only the 3 seagrass, and 14 mangrove classification categories were used.  These were mapped directly into a GIS system through visual interpretation of orthorectified aerial photographs.	not-provided
 39482	1992 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve	NOAA_NCEI	1992-01-31	1992-01-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2102656472-NOAA_NCEI.json	Aerial photographs taken by NOAA's National Geodetic Survey during 1992 were mosaicked and orthorectified by the Biogeography Branch. The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and in some areas extends beyond the park boundaries up to 2 km.	not-provided
@@ -25,27 +24,16 @@ id	title	catalog	state_date	end_date	bbox	url	description	license
 7ae5a791-b667-4838-9733-a44e4cf2d715	Cartosat-1 (IRS-P5) - Panchromatic Images (PAN) - Europe, Stereographic	FEDEO	2007-01-05		-25, 30, 45, 80	https://cmr.earthdata.nasa.gov/search/concepts/C2207458042-FEDEO.json	Indian Remote Sensing satellites (IRS) are a series of Earth Observation satellites, built, launched and maintained by Indian Space Research Organisation. The IRS series provides many remote sensing services to India and international ground stations. The satellite has two panchromatic cameras that were especially designed for in flight stereo viewing.	not-provided
 802569b8-fb56-4d78-a2e8-3e4549ff475b	AVHRR - Sea Surface Temperature (SST) - Europe	FEDEO	1994-08-01		-35, 47.5, 51, 73	https://cmr.earthdata.nasa.gov/search/concepts/C2207458053-FEDEO.json	The AVHRR Mulitchannel Sea Surface Temperature Map (MCSST) was the first result of DLR's AVHRR pathfinder activities. The goal of the product is to provide the user with actual Sea Surface Temperature (SST) maps in a defined format easy to access with the highest possible reliability on the thematic quality. After a phase of definition, the operational production chain was launched in March 1993 covering the entire Mediterranean Sea and the Black Sea. Since then, daily, weekly, and monthly data sets have been available until September 13, 1994, when the AVHRR on board the NOAA-11 spacecraft failed. The production of daily, weekly and monthly SST maps was resumed in February, 1995, based on NOAA-14 AVHRR data. The NOAA-14 AVHRR sensor became some technical difficulties, so the generation was stopped on October 3, 2001. Since March 2002, NOAA-16 AVHRR SST maps are available again. With the beginning of January 2004, the data of AVHRR on board of NOAA-16 exhibited some anormal features showing strips in the scenes. Facing the “bar coded” images of NOAA16-AVHRR which occurred first in September 2003, continued in January 2004 for the second time and appeared in April 2004 again, DFD has decided to stop the reception of NOAA16 data on April 6th, 2004, and to start the reception of NOAA-17 data on this day. On April 7th, 2004, the production of all former NOAA16-AVHRR products as e.g. the SST composites was successully established. NOAA-17 is an AM sensor which passes central Europe about 2 hours earlier than NOAA-16 (about 10:00 UTC instead of 12:00 UTC for NOAA-16). In spring 2007, the communication system of NOAA-17 has degraded or is operating with limitations. Therefore, DFD has decided to shift the production of higher level products (NDVI, LST and SST) from NOAA-17 to NOAA-18 in April 2007. In order to test the performance of our processing chains, we processed simultaneously all NOAA-17 and NOAA-18 data from January 1st, 2007 till March 29th, 2007. All products are be available via EOWEB. Please remember that NOAA-18 is a PM sensor which passes central Europe about 1.5 hours later than NOAA-17 (about 11:30 UTC instead of 10:00 UTC for NOAA17). The SST product is intended for climate modelers, oceanographers, and all geo science-related disciplines dealing with ocean surface parameters. In addition, SST maps covering the North Atlantic, the Baltic Sea, the North Sea and the Western Atlantic equivalent to the Mediterranean MCSST maps are available since August 1994. The most important aspects of the MCSST maps are a) correct image registration and b) reasonable cloud screening to ensure that only cloud free pixels are taken for the later processing and compositing c) for deriving MCSST, only channel 4 and 5 are used.. The SST product consists of one 8 bit channel. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/	not-provided
 936b319d-5253-425d-bd29-4b6ebce067ff	AVHRR - Land Surface Temperature (LST) - Europe, Nighttime	FEDEO	1998-02-23		-24, 28, 57, 78	https://cmr.earthdata.nasa.gov/search/concepts/C2207458046-FEDEO.json	"The ""Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)"" is a fixed grid map (in stereographic projection) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between –39.5°C and +87°C with a radiometric resolution of 0.5°C. A value of –40°C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/"	not-provided
-A Fusion Dataset for Crop Type Classification in Germany.v1	A Fusion Dataset for Crop Type Classification in Germany	MLHUB	2020-01-01	2023-01-01	13.6339485, 52.4179888, 14.3529903, 52.8494418	https://cmr.earthdata.nasa.gov/search/concepts/C2781412484-MLHUB.json	 This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Brandenburg, Germany. There are nine crop types in this dataset from years 2018 and 2019: Wheat, Rye, Barley, Oats, Corn, Oil Seeds, Root Crops, Meadows, Forage Crops. The 2018 labels from one of the tiles are provided for training, and the 2019 labels from a neighboring tile will be used for scoring in the competition.   Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection.   The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license.  	not-provided
-A Fusion Dataset for Crop Type Classification in Western Cape, South Africa.v1	A Fusion Dataset for Crop Type Classification in Western Cape, South Africa	MLHUB	2020-01-01	2023-01-01	20.5212157, -34.413256, 21.043415, -33.9796334	https://cmr.earthdata.nasa.gov/search/concepts/C2781412697-MLHUB.json	 This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Western Cape, South Africa. There are five crop types from the year 2017: Wheat, Barely, Canola, Lucerne/Medics, Small grain grazing. The AOI is split to three tiles. Two tiles are provided as training labels, and one tile will be used for scoring in the competition.   Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection.   The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license.   The Western Cape Department of Agriculture (WCDoA) vector data are supplied via Radiant Earth Foundation with limited distribution rights. Data supplied by the WCDoA may not be distributed further or used for commercial purposes. The vector data supplied are intended strictly for use within the scope of this remote sensing competition - for the purpose of academic research to our mutual benefit. The data is intended for research purposes only and the WCDoA cannot be held responsible for any errors or omissions which may occur in the data. 	not-provided
-A crop type dataset for consistent land cover classification in Central Asia.v1	A crop type dataset for consistent land cover classification in Central Asia	MLHUB	2020-01-01	2023-01-01	60.2013297, 37.4241018, 72.3539419, 41.8252151	https://cmr.earthdata.nasa.gov/search/concepts/C2781412666-MLHUB.json	Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture relies heavily on irrigation. Here, remote sensing is valuable to map crop types, but its quality depends on consistent ground-truth data. Yet, in the ASB, such data is missing. Addressing this issue, we collected thousands of polygons on crop types, 97.7% of which in Uzbekistan and the remaining in Tajikistan. We collected 8,196 samples between 2015 and 2018, 213 in 2011 and 26 in 2008. Our data compiles samples for 40 crop types and is dominated by “cotton” (40%) and “wheat”, (25%). These data were meticulously validated using expert knowledge and remote sensing data and relied on transferable, open-source workflows that will assure the consistency of future sampling campaigns.	not-provided
 AAOT.v0	Acqua Alta Oceanographic Tower (AAOT)	OB_DAAC	1999-08-03		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360084-OB_DAAC.json	Measurements made by the Acqua Alta Oceanographic Tower (AAOT), an Italian installation off the coast of Venice in the Adriatic Sea from 1999 to 2002.	not-provided
 AAS_4156_Macquarie_Island_Emerald_Lake.v1	12,000 year record of sea spray and minerogenic input from Emerald Lake, Macquarie Island	AU_AADC	2012-07-01	2019-06-30	158.77441, -54.77772, 158.94951, -54.4828	https://cmr.earthdata.nasa.gov/search/concepts/C2102891784-AU_AADC.json	Reconstructed sea spray and minerogenic data for a 12,000 year lake sediment record from Emerald Lake, Macquarie Island. Proxies are based on biological (diatoms) and geochemical (micro x-ray fluorescence and hyperspectral imaging) indicators. Data correspond to the figures in: Saunders et al. 2018 Holocene dynamics of the Southern Hemisphere westerly winds and possible links to CO2 outgassing. Nature Geoscience 11:650-655. doi.org/10.1038/s41561-018-0186-5. Detailed supplementary information: https://static-content.springer.com/esm/art%3A10.1038%2Fs41561-018-0186-5/MediaObjects/41561_2018_186_MOESM1_ESM.pdf  Abstract: The Southern Hemisphere westerly winds (SHW) play an important role in regulating the capacity of the Southern Ocean carbon sink. They modulate upwelling of carbon-rich deep water and, with sea ice, determine the ocean surface area available for air–sea gas exchange. Some models indicate that the current strengthening and poleward shift of these winds will weaken the carbon sink. If correct, centennial- to millennial-scale reconstructions of the SHW intensity should be linked with past changes in atmospheric CO2, temperature and sea ice. Here we present a 12,300-year reconstruction of wind strength based on three independent proxies that track inputs of sea-salt aerosols and minerogenic particles accumulating in lake sediments on sub-Antarctic Macquarie Island. Between about 12.1 thousand years ago (ka) and 11.2 ka, and since about 7 ka, the wind intensities were above their long-term mean and corresponded with increasing atmospheric CO2. Conversely, from about 11.2 to 7.2 ka, the wind intensities were below their long-term mean and corresponded with decreasing atmospheric CO2. These observations are consistent with model inferences of enhanced SHW contributing to the long-term outgassing of CO2 from the Southern Ocean.	not-provided
 AAS_4156_Macquarie_Island_unnamed_lake.v1	2000 year record of environmental change from an unnamed lake on Macquarie Island	AU_AADC	2012-07-01	2019-06-30	158.74969, -54.78485, 158.96118, -54.47004	https://cmr.earthdata.nasa.gov/search/concepts/C2102891849-AU_AADC.json	Age-depth and geochemical data for a 2000 year lake sediment record from an unnamed lake on Macquarie Island. The lake is the small lake to the west of Major Lake, on the edge of the Macquarie Island plateau. The chronology is based on lead-210 (last ca. 100 years) and radiocarbon (extending to ca. 2000 years). Geochemistry is based on micro x-ray fluroescence, and carbon, nitrogen and sulphur contents. Grain size and water content were also measured.  Data correspond to the publication: Saunders et al. in prep.Southern Hemisphere westerly wind variability in the sub-Antarctic and relationships to mid-latitude precipitation for the last 2000 years	not-provided
 ABLVIS1B.v1	ABoVE LVIS L1B Geolocated Return Energy Waveforms V001	NSIDC_ECS	2017-06-29	2017-07-17	-158, 48, -104, 72	https://cmr.earthdata.nasa.gov/search/concepts/C1513105920-NSIDC_ECS.json	This data set contains return energy waveform data over Alaska and Western Canada measured by the NASA Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of NASA's Terrestrial Ecology Program campaign, the Arctic-Boreal Vulnerability Experiment (ABoVE).	not-provided
 ABLVIS2.v1	ABoVE LVIS L2 Geolocated Surface Elevation Product V001	NSIDC_ECS	2017-06-29	2017-07-17	-158, 48, -104, 72	https://cmr.earthdata.nasa.gov/search/concepts/C1513105984-NSIDC_ECS.json	This data set contains surface elevation data over Alaska and Western Canada measured by the NASA Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of NASA's Terrestrial Ecology Program campaign, the Arctic-Boreal Vulnerability Experiment (ABoVE).	not-provided
 ABOLVIS1A.v1	ABoVE LVIS L1A Geotagged Images V001	NSIDC_ECS	2017-06-29	2017-07-17	-158, 48, -104, 72	https://cmr.earthdata.nasa.gov/search/concepts/C1673546369-NSIDC_ECS.json	This data set contains geotagged images collected over Alaska and Western Canada. The images were taken by the NASA Digital Mapping Camera, paired with the Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of NASA's Terrestrial Ecology Program campaign, the Arctic-Boreal Vulnerability Experiment (ABoVE).	not-provided
-ABoVE_ASCENDS_XCO2_2050.v1	ABoVE/ASCENDS: Active Sensing of CO2, CH4, and Water Vapor, Alaska and Canada, 2017	ORNL_CLOUD	2017-07-20	2017-08-08	-165.68, 34.59, -98.1, 71.28	https://cmr.earthdata.nasa.gov/search/concepts/C2264340976-ORNL_CLOUD.json	This dataset provides in situ airborne measurements of atmospheric carbon dioxide (CO2), methane (CH4), and water vapor concentrations, plus air temperature, pressure, relative humidity, and wind speed values over Alaska and the Yukon and Northwest Territories of Canada during 2017-07-20 to 2017-08-08. Measurements were taken onboard a DC-8 aircraft during this Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) airborne deployment over portions of the Arctic-Boreal Vulnerability Experiment (ABoVE) domain. CO2 and CH4 were measured with NASA's Atmospheric Vertical Observations of CO2 in the Earth's Troposphere (AVOCET) instrument. Water vapor and relative humidity were measured with Diode Laser Hydrometer. Measurements of column-averaged dry-air mixing ratio CO2 measurements (XCO2) were taken with the CO2 Sounder Lidar instrument. The airborne CO2 Sounder is a pulsed, multi-wavelength Integrated Path Differential Absorption lidar. It estimates XCO2 in the nadir path from the aircraft to the scattering surface by measuring the shape of the 1572.33 nm CO2 absorption line. The data were collected in order to capture the spatial and temporal dynamics of the northern high latitude carbon cycle as part of ABoVE and are provided in ICARTT file format.	not-provided
-ABoVE_Concise_Experiment_Plan_1617.v1.1	A Concise Experiment Plan for the Arctic-Boreal Vulnerability Experiment	ORNL_CLOUD	2014-01-01	2021-12-31	-176.12, 39.42, -66.92, 81.61	https://cmr.earthdata.nasa.gov/search/concepts/C2162145735-ORNL_CLOUD.json	This document presents the Concise Experiment Plan for NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) to serve as a guide to the Program as it identifies the research to be conducted under this study. Research for ABoVE will link field-based, process-level studies with geospatial data products derived from airborne and satellite remote sensing, providing a foundation for improving the analysis and modeling capabilities needed to understand and predict ecosystem responses and societal implications. The ABoVE Concise Experiment Plan (ACEP) outlines the conceptual basis for the Field Campaign and expresses the compelling rationale explaining the scientific and societal importance of the study. It presents both the science questions driving ABoVE research as well as the top-level requirements for a study design to address them.	not-provided
 ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data.v1	ACCLIP WB-57 Aerosol and Cloud Remotely Sensed Data	LARC_ASDC	2022-07-14	2022-09-14	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2655162569-LARC_ASDC.json	ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data is the cloud and aerosol remote sensing data from the Roscoe lidar collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
 ACCLIP_Aerosol_AircraftInSitu_WB57_Data.v1	ACCLIP WB-57 Aircraft In-Situ Aerosol Data	LARC_ASDC	2022-07-14	2022-09-14	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2609962127-LARC_ASDC.json	ACCLIP_Aerosol_AircraftInSitu_WB57_Data is the in-situ aerosol data collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Particle Analysis by Laser Mass Spectrometry - Next Generation (PALMS-NG), Single Particle Soot Photometer (SP2), Nucleation-Mode Aerosol Size Spectrometer (N-MASS), Printed Optical Particle Spectrometer (POPS), and the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
-ACCLIP_AircraftInSitu_WB57_Water_Data.v1	ACCLIP WB-57 Aircraft Water In-situ Data	LARC_ASDC	2022-07-14	2022-09-14	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2609920136-LARC_ASDC.json	ACCLIP_AircraftInSitu_WB57_Water_Data is the in-situ water data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Chicago Water Isotope Spectrometer  (ChiWIS) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
 ACCLIP_Cloud_AircraftInSitu_WB57_Data.v1	ACCLIP WB-57 Aircraft In-situ Cloud Data	LARC_ASDC	2022-07-14	2022-09-01	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2609947245-LARC_ASDC.json	ACCLIP_Cloud_AircraftInSitu_WB57_Data is the in-situ cloud data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Cloud, Aerosol, and Precipitation Spectrometer (CAPS) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
-ACCLIP_MetNav_AircraftInSitu_WB57_Data.v1	ACCLIP WB-57 Meteorological and Navigational Data	LARC_ASDC	2022-07-14	2022-09-14	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2566338281-LARC_ASDC.json	ACCLIP_MetNav_AircraftInSitu_WB57_Data is the in-situ meteorology and navigational data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Meteorological Measurement System (MMS) and Diode Laser Hygrometer (DLH) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
-ACCLIP_Model_WB57_Data.v1	ACCLIP WB-57 Aircraft Model Data	LARC_ASDC	2022-07-14	2022-09-14	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2609869612-LARC_ASDC.json	ACCLIP_Model_WB57_Data contains modeled meteorological, chemical, and aerosol data along the flight tracks of the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
 ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1	ACCLIP WB-57 Aircraft In-situ Trace Gas Data	LARC_ASDC	2022-07-14	2022-09-14	-180, 16.6, 180, 61.5	https://cmr.earthdata.nasa.gov/search/concepts/C2566342407-LARC_ASDC.json	ACCLIP_TraceGas_AircraftInSitu_WB57_Data is the in-situ trace gas data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Airborne Carbon Oxide Sulfide Spectrometer (ACOS), Carbon monOxide Measurement from Ames (COMA), Laser Induced Fluorescence - Nitrogen Oxide (LIF-NO), In Situ Airborne Formaldehyde (ISAF), Carbon Oxide Laser Detector 2 (COLD 2), and the NOAA UAS O3 Photometer (UASO3) is featured in this collection. Data collection for this product is complete.    ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate.    The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.	not-provided
-ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1	ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data Version 1	LARC_ASDC	2017-10-18	2020-11-20	-130, 25, -100, 45	https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.json	ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_AirHARP_Data) are remotely sensed measurements collected by the Airborne Hyper Angular Rainbow Polarimeter (AirHARP) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which is a valuable resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.	not-provided
-ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1	ACEPOL Airborne Spectrometer for Planetary Exploration (AirSPEX) Remotely Sensed Data Version 1	LARC_ASDC	2017-10-19	2017-11-09	-130, 25, -100, 45	https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.json	ACEPOL_AircraftRemoteSensing_AirSPEX_Data are remotely sensed measurements collected by the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.	not-provided
-ACEPOL_AircraftRemoteSensing_CPL_Data.v1	ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data Version 1	LARC_ASDC	2017-10-19	2017-11-09	-130, 25, -100, 45	https://cmr.earthdata.nasa.gov/search/concepts/C1758588308-LARC_ASDC.json	ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.	not-provided
 ACIDD.v0	Across the Channel Investigating Diel Dynamics project	OB_DAAC	2017-12-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360091-OB_DAAC.json	The ACIDD (Across the Channel Investigating Diel Dynamics) project, in the Santa Barbara Channel, was initially designed to characterize daily variations in phytoplankton populations, but with the Thomas Fire in the Santa Barbara Hills December 2017, this project evolved into a study to characterize the effects of smoke and ash on the mixed layer in the Santa Barbara Channel.	not-provided
 ACOS_L2S.v7.3	ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC	GES_DISC	2009-04-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.json	"Version 7.3 is the current version of the data set. Version 3.5 is no longer available and has been superseded by Version 7.3.  This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch,  ""ACOS"" data are still produced and improved, using approaches applied to the OCO-2 spectra.  The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3.  The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process.  Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings.   Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation.   An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag.   Lastly, users should continue to carefully observe and weigh information from three important flags:         ""warn_level"" - Provides a value that summarizes each sounding's acceptability to a larger set of quality filters. A high warn level predicts that the sounding would fail most data filters applied to it. A low warn level suggests that the sounding would pass most quality filters that might be applied.         ""sounding_qual_flag"" - quality of input data provided to the retrieval processing            ""outcome_flag"" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated)            ""master_quality_flag"" - four possible values: ""Good"", ""Caution"" and ""Bad"", and ""Failed"", as determined from other flags in the L2 productThe short name for this data type is ACOS_L2S."	not-provided
 ACOS_L2S.v9r	ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V9r (ACOS_L2S) at GES DISC	GES_DISC	2009-04-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.json	"Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r.  This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch,  ""ACOS"" data are still produced and improved, using approaches applied to the OCO-2 spectra.  The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3.  The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process.  Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings.   Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation.   An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag.   Lastly, users should continue to carefully observe and weigh information from three important flags:          ""sounding_qual_flag"" - quality of input data provided to the retrieval processing            ""outcome_flag"" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated)              "	not-provided
@@ -72,9 +60,6 @@ AERIALDIGI	Aircraft Scanners	USGS_LTA	1987-10-06		-180, 24, -60, 72	https://cmr.
 AFLVIS1B.v1	AfriSAR LVIS L1B Geolocated Return Energy Waveforms V001	NSIDC_ECS	2016-02-20	2016-03-08	8, -2, 12, 1	https://cmr.earthdata.nasa.gov/search/concepts/C1549378019-NSIDC_ECS.json	This data set contains return energy waveform data over Gabon, Africa. The measurements were taken by the NASA Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of a NASA campaign, in collaboration with the European Space Agency (ESA) mission AfriSAR.	not-provided
 AFLVIS2.v1	AfriSAR LVIS L2 Geolocated Surface Elevation Product V001	NSIDC_ECS	2016-02-20	2016-03-08	8, -2, 12, 1	https://cmr.earthdata.nasa.gov/search/concepts/C1549378743-NSIDC_ECS.json	This data set contains surface elevation data over Gabon, Africa. The measurements were taken by the NASA Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of a NASA campaign, in collaboration with the European Space Agency (ESA) mission AfriSAR.	not-provided
 AFOLVIS1A.v1	AfriSAR LVIS L1A Geotagged Images V001	NSIDC_ECS	2016-02-20	2016-03-08	8, -2, 12, 1	https://cmr.earthdata.nasa.gov/search/concepts/C1932134853-NSIDC_ECS.json	This data set contains geotagged images collected over Gabon, Africa. The images were taken by the NASA Digital Mapping Camera paired with the Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of a NASA campaign, in collaboration with the European Space Agency (ESA) mission AfriSAR.	not-provided
-AG100.v003	ASTER Global Emissivity Dataset, 100 meter, HDF5 V003	LPDAAC_ECS	2000-01-01	2008-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1000000362-LPDAAC_ECS.json	Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate spectral resolution TRANsmittance (MODTRAN 5.2 radiative transfer model). This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG100 data are available globally at spatial resolution of 100 meters.    The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.  	not-provided
-AG1km.v003	ASTER Global Emissivity Dataset, 1 kilometer, HDF5 V003	LPDAAC_ECS	2000-01-01	2008-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1000000380-LPDAAC_ECS.json	Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate Spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model. This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG1KM data are available globally at spatial resolution of 1 kilometer.    The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.	not-provided
-AG5KMMOH.v041	ASTER Global Emissivity Dataset, Monthly, 0.05 deg, HDF5 V041	LPDAAC_ECS	2000-03-01	2015-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1344831606-LPDAAC_ECS.json	Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is a collection of monthly files (see known issues for gaps) for each year of global emissivity. The ASTER GED data products are generated for 2000 through 2015 using the ASTER Temperature Emissivity Separation (TES) algorithm atmospheric correction method. This algorithm method uses Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheric Profiles product (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) and the MODerate spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model along with the snow cover data from the standard monthly MODIS/Terra snow cover monthly global 0.05 degree product (MOD10CM) (https://doi.org/10.5067/MODIS/MOD10CM.006), and vegetation information from the MODIS monthly gridded NDVI product (MOD13C2) (https://doi.org/10.5067/MODIS/MOD13C2.006). ASTER GED Monthly V041 data products are offered in Hierarchical Data Format 5 (HDF5).    The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.	not-provided
 AIRABRAD.v005	AIRS/Aqua L1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005 (AIRABRAD) at GES DISC	GES_DISC	2002-05-21		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.json	"The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AMSU-A instrument is co-aligned with AIRS so that successive blocks of 3 x 3 AIRS footprints are contained within one AMSU-A footprint. AMSU-A is primarily a temperature sounder that provides atmospheric information in the presence of clouds, which can be used to correct the AIRS infrared measurements for the effects of clouds. This is possible because non-precipitating clouds are for the most part transparent to microwave radiation, in contrast to visible and infrared radiation which are strongly scattered and absorbed by clouds. AMSU-A1 has 13 channels from 50 - 90 GHz and AMSU-A2 has 2 channels from 23 - 32 GHz. The AIRABRAD_005 products are stored in files (often referred to as ""granules"") that contain 6 minutes of data, 30 footprints across track by 45 lines along track."	not-provided
 AIRSAR_INT_JPG.v1	AIRSAR_ALONGTRACK_INTERFEROMETRY_JPG	ASF	1998-10-25	2004-03-05	-172.880269, -27.388834, -49.704356, 69.25925	https://cmr.earthdata.nasa.gov/search/concepts/C1213921626-ASF.json	AIRSAR along-track interferometric browse product JPG	not-provided
 AIRSAR_POL_3FP.v1	AIRSAR_POLSAR_3_FREQ_POLARIMETRY	ASF	1990-03-02	2004-03-21	-172.880269, -27.388834, -49.704356, 69.25925	https://cmr.earthdata.nasa.gov/search/concepts/C1213921661-ASF.json	AIRSAR three-frequency polarimetric frame product	not-provided
@@ -114,22 +99,7 @@ AST14DEM.v003	ASTER Digital Elevation Model V003	LPDAAC_ECS	2000-03-06		-180, -8
 ASTGTM.v003	ASTER Global Digital Elevation Model V003	LPCLOUD	2000-03-01	2013-11-30	-180, -83, 180, 82	https://cmr.earthdata.nasa.gov/search/concepts/C1711961296-LPCLOUD.json	The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).    The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo.     The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated.     The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in GeoTIFF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area.     Provided in the ASTER GDEM product are layers for DEM and number of scenes (NUM). The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data.    While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications.     Improvements/Changes from Previous Versions   • Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3.  • Separation of rivers from lakes in the water body processing.   • Minimum water body detection size decreased from 1 km2 to 0.2 km2. 	not-provided
 ASTGTM_NC.v003	ASTER Global Digital Elevation Model NetCDF V003	LPCLOUD	2000-03-01	2013-11-30	-180, -83, 180, 82	https://cmr.earthdata.nasa.gov/search/concepts/C2439422590-LPCLOUD.json	The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).  The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo.   The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated.   The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in NetCDF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area.   Each ASTGTM_NC data product contains a DEM file, which provides elevation information. The corresponding ASTGTM_NUMNC file indicates the number of scenes that were processed for each pixel and the source of the data.  While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications.   Improvements/Changes from Previous Versions  • Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3. • Separation of rivers from lakes in the water body processing.  • Minimum water body detection size decreased from 1 km2 to 0.2 km2.  	not-provided
 ASTGTM_NUMNC.v003	ASTER Global Digital Elevation Model Attributes NetCDF V003	LPCLOUD	2000-03-01	2013-11-30	-180, -83, 180, 82	https://cmr.earthdata.nasa.gov/search/concepts/C2439429778-LPCLOUD.json	The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).    The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo.     The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated.     The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in NetCDF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area.     Each ASTGTM_NUMNC file indicates the number of scenes that were processed for each pixel and the source of the data.. The corresponding ASTGTM_NC data product contains a DEM file, which provides elevation information.     While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications.     Improvements/Changes from Previous Versions   • Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3.  • Separation of rivers from lakes in the water body processing.   • Minimum water body detection size decreased from 1 km2 to 0.2 km2. 	not-provided
-ASTWBD.v001	ASTER Global Water Bodies Database V001	LPDAAC_ECS	2000-03-01	2013-11-30	-180, -83, 180, 82	https://cmr.earthdata.nasa.gov/search/concepts/C1575734433-LPDAAC_ECS.json	The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.     The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces.    To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required.     The geographic coverage of the ASTWBD extends from 83°N to 83°S. Each tile is distributed in GeoTIFF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each data product is provided as a zipped file that contains an attribute file with the water body classification information and a DEM file, which provides elevation information in meters. 	not-provided
-ASTWBD_ATTNC.v001	ASTER Global Water Bodies Database Attributes NetCDF V001	LPDAAC_ECS	2000-03-01	2013-11-30	-180, -83, 180, 82	https://cmr.earthdata.nasa.gov/search/concepts/C1575734760-LPDAAC_ECS.json	The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.     The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces.    To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required.     The geographic coverage of the ASTWBD extends from 83°N to 83°S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_ATTNC file contains an attribute file with the water body classification information. The corresponding  ASTWBD_NC data product DEM file, which provides elevation information in meters.	not-provided
-ASTWBD_NC.v001	ASTER Global Water Bodies Database NetCDF V001	LPDAAC_ECS	2000-03-01	2013-11-30	-180, -83, 180, 82	https://cmr.earthdata.nasa.gov/search/concepts/C1575734501-LPDAAC_ECS.json	The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information.     The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces.    To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required.     The geographic coverage of the ASTWBD extends from 83°N to 83°S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_NC data product DEM file, which provides elevation information in meters. The corresponding ASTWBD_ATTNC file contains an attribute file with the water body classification information.	not-provided
-AST_L1A.v003	ASTER L1A Reconstructed Unprocessed Instrument Data V003	LPDAAC_ECS	2000-03-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C14758250-LPDAAC_ECS.json	The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1A (AST_L1A) contains reconstructed, instrument digital numbers (DNs) derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). Additionally, geometric correction coefficients and radiometric calibration coefficients are calculated and appended to the metadata, but not applied. The spatial resolution is 15 m (VNIR), 30 m (SWIR), and 90 m (TIR) with a temporal coverage of 2000 to present.     Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article.    Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427.  	not-provided
 AST_L1AE.v003	ASTER Expedited L1A Reconstructed Unprocessed Instrument Data V003	LPDAAC_ECS	2000-03-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C179460405-LPDAAC_ECS.json	The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1A Reconstructed Unprocessed Instrument Data (AST_L1AE) global product contains reconstructed, unprocessed instrument digital data derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). This data product is similar to the (AST_L1A) (http://doi.org/10.5067/ASTER/AST_L1A.003) with a few notable exceptions. These include:  * The AST_L1AE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments.  * The registration quality of the AST_L1AE is likely to be lower than the AST_L1A, and may vary from scene to scene.  * The AST_L1AE data product does not contain the VNIR 3B (aft-viewing) Band.  * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor.  * The AST_L1AE data product is only available for download 30 days after acquisition. It is then removed and reprocessed into an AST_L1A product.	not-provided
-AST_L1BE.v003	ASTER Expedited L1B Registered Radiance at the Sensor V003	LPDAAC_ECS	2000-03-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C179460406-LPDAAC_ECS.json	The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1B Registered Radiance at the Sensor global data product is radiometrically calibrated and geometrically co-registered. Application of intra-telescope and inter-telescope registration corrections for all bands are relative to the reference band for each telescope: Visible  and Near Infrared (VNIR) Band 2, Shortwave Infrared (SWIR) Band 6, and Thermal Infrared (TIR) Band 11. The Expedited Level 1B data product is similar to the (AST_L1B) (https://doi.org/10.5067/ASTER/AST_L1B.003) with a few notable exceptions. These include:  * The AST_L1BE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments.  * The registration quality of the AST_L1BE is likely to be lower than the AST_L1B, and may vary from scene to scene.  * The AST_L1BE dataset does not contain the VNIR 3B (aft-viewing) Band.  * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor.	not-provided
-ATL02.v005	ATLAS/ICESat-2 L1B Converted Telemetry Data V005	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2153572246-NSIDC_CPRD.json	This data set (ATL02) contains science unit-converted, time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system–level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and the Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.	not-provided
-ATL02.v006	ATLAS/ICESat-2 L1B Converted Telemetry Data V006	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.json	This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.	not-provided
-ATL03.v005	ATLAS/ICESat-2 L2A Global Geolocated Photon Data V005	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2153572325-NSIDC_CPRD.json	This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.	not-provided
-ATL03.v006	ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.json	This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.	not-provided
-ATL04.v005	ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V005	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2153572406-NSIDC_CPRD.json	ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	not-provided
-ATL04.v006	ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.json	ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	not-provided
-ATL09.v005	ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V005	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2153574732-NSIDC_CPRD.json	This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	not-provided
-ATL09.v006	ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.json	This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	not-provided
-ATL13.v005	ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V005	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2153575088-NSIDC_CPRD.json	This data set (ATL13) contains along-track surface water products for inland water bodies.  Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).	not-provided
-ATL13.v006	ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006	NSIDC_CPRD	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.json	This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).	not-provided
 ATSMIGEO.v002	MISR Geometric Parameters subset for the ARCTAS region V002	LARC	2008-04-02	2008-07-24	-157, 54, -110, 71	https://cmr.earthdata.nasa.gov/search/concepts/C1000000541-LARC.json	This file contains the Geometric Parameters subset for the ARCTAS region which measures the sun and view angles at the reference ellipsoid	not-provided
 AU_DySno_NRT_R02.v2	NRT AMSR2 Unified L3 Global Daily 25 km EASE-Grid Snow Water Equivalent V2	LANCEAMSR2	2021-04-15		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2052622563-LANCEAMSR2.json	The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument on the Global Change Observation Mission - Water 1 (GCOM-W1) provides global passive microwave measurements of terrestrial, oceanic, and atmospheric parameters for the investigation of global water and energy cycles.  Near real-time (NRT) products are generated within 3 hours of the last observations in the file, by the Land Atmosphere Near real-time Capability for EOS (LANCE) at the AMSR Science Investigator-led Processing System (AMSR SIPS), which is collocated with the Global Hydrology Resource Center (GHRC) DAAC.  The NRT AMSR2 Unified L3 Global Daily Snow Water Equivalent data set contains snow water equivalent (SWE) data and quality assurance flags mapped to Northern and Southern Hemisphere 25 km Equal-Area Scalable Earth Grids (EASE-Grids).  Data are stored in HDF-EOS5 format and are available via HTTP from the EOSDIS LANCE system at https://lance.nsstc.nasa.gov/amsr2-science/data/level3/daysnow/.  If data latency is not a primary concern, please consider using science quality products.  Science products are created using the best available ancillary, calibration and ephemeris information.  Science quality products are an internally consistent, well-calibrated record of the Earth's geophysical properties to support science.	not-provided
 AU_Land_NRT_R02.v2	NRT AMSR2 Unified L2B Half-Orbit 25 km EASE-Grid Surface Soil Moisture Beta V2	LANCEAMSR2	2018-04-11		-180, -89.24, 180, 89.24	https://cmr.earthdata.nasa.gov/search/concepts/C1514684539-LANCEAMSR2.json	The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument on the Global Change Observation Mission - Water 1 (GCOM-W1) provides global passive microwave measurements of terrestrial, oceanic, and atmospheric parameters for the investigation of global water and energy cycles.  Near real-time (NRT) products are generated within 3 hours of the last observations in the file, by the Land Atmosphere Near real-time Capability for EOS (LANCE) at the AMSR Science Investigator-led Processing System (AMSR SIPS), which is collocated with the Global Hydrology Resource Center (GHRC) DAAC.  The GCOM-W1 NRT AMSR2 Unified L2B Half-Orbit 25 km EASE-Grid Surface Soil Moisture product is a daily measurement of surface soil moisture produced by two retrieval algorithms using resampled Tb (Level-1R) data provided by JAXA: the Normalized Polarization Difference (NPD) algorithm developed by JPL and the Single Channel Algorithm (SCA) developed by USDA.  Ancillary data include time, geolocation, and quality assessment.  Data are stored in HDF-EOS5 and netCDF4 formats and are available via HTTPS from the EOSDIS LANCE system at https://lance.nsstc.nasa.gov/amsr2-science/data/level2/land/.  If data latency is not a primary concern, please consider using science quality products.  Science products are created using the best available ancillary, calibration and ephemeris information.  Science quality products are an internally consistent, well-calibrated record of the Earth's geophysical properties to support science.  The AMSR SIPS produces AMSR2 standard science quality data products and they are available at the NSIDC DAAC.  Note:  This is the same algorithm that generates the corresponding standard science products in the AMSR SIPS.  With this beta release, we are generating NRT products in both HDF-EOS5 and netCDF with CF metadata. Version 2 corrects these issues from the previous release: a boundary condition error that resulted in the failure of a small number of version 1 product files and an error in the number of low resolution scans processed which caused only the first half of each scan to be processed.	not-provided
@@ -143,8 +113,6 @@ AU_SI6_NRT_R04.v4	NRT AMSR2 Unified L3 Daily 6.25 km Polar Gridded 89 GHz Bright
 AVHRR_GLOBAL_10-DAY_COMPOSITES	AVHRR 1-km Global Land 10-Day Composites	USGS_LTA	1992-04-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1220566288-USGS_LTA.json	The Advanced Very High Resolution Radiometer (AVHRR) 1-km Global  Land  10-Day Composites data set project is a component of the National Aeronautics and Space Administration (NASA) AVHRR Pathfinder  Program. The project is a collaborative effort between the National Oceanic  and Atmospheric Administration (NOAA), NASA, the U.S. Geological Survey  (USGS), the European Space Agency (ESA), Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), and 30 international ground receiving stations.  The project represents an international effort to archive and distribute the 1-km AVHRR composites of the entire global land surface to scientific  researchers and to the general public.  The data set is comprised of a time series of global 10-day normalized difference vegetation index composites.  The composites are generated from radiometrically calibrated, atmospherically corrected, and geometrically corrected daily AVHRR observations. The time series begins in April 1992 and continues for specific time periods.	not-provided
 AVHRR_ORBITAL_SEGMENTS	AVHRR 1-km Orbital Segments	USGS_LTA	1992-04-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1220566340-USGS_LTA.json	       The Advanced Very High Resolution Radiometer (AVHRR) 1-km Orbital        Segments data set is a component of the National Aeronautics and        Space Administration (NASA) AVHRR Pathfinder Program and contains        global coverage of land masses at 1-kilometer resolution.         The data set is the result of an international effort to acquire,        process, and distribute AVHRR data of the entire global land surface        to meet the needs of the international science community.  The         orbital segments are comprised of raw AVHRR scenes consisting of        5-channel, 10-bit, AVHRR data at 1.1-km resolution at nadir.  The raw        data are used to produce vegetation index composites; to support fire         detection and cloud screening activities; to support research in        atmospheric correction; to develop algorithms; and to support a host of        research activities that may require the inclusion of raw AVHRR data. 	not-provided
 Active_Fluorescence_2001.v0	Active fluorescence measurements in the Gulf Stream in 2001	OB_DAAC	2001-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360093-OB_DAAC.json	Measurements in the Gulf Stream off the East Coast of the US in 2001	not-provided
-AgriFieldNet Competition Dataset.v1	AgriFieldNet Competition Dataset	MLHUB	2020-01-01	2023-01-01	76.2448319, 18.9414403, 88.0460054, 28.3269976	https://cmr.earthdata.nasa.gov/search/concepts/C2781412563-MLHUB.json	This dataset contains crop types of agricultural fields in four states of Uttar Pradesh, Rajasthan, Odisha and Bihar in northern India. There are 13 different classes in the dataset including Fallow land and 12 crop types of Wheat, Mustard, Lentil, Green pea, Sugarcane, Garlic, Maize, Gram, Coriander, Potato, Bersem, and Rice. The dataset is split to train and test collections as part of the AgriFieldNet India Competition. Ground reference data for this dataset is collected by IDinsight’s [Data on Demand](https://www.idinsight.org/services/data-on-demand/) team. Radiant Earth Foundation carried out the training dataset curation and publication. This training dataset is generated through a grant from the Enabling Crop Analytics at Scale ([ECAAS](https://cropanalytics.net/)) Initiative funded by [The Bill & Melinda Gates Foundation](https://www.gatesfoundation.org/) and implemented by [Tetra Tech](https://www.tetratech.com/).	not-provided
-BigEarthNet.v1	BigEarthNet	MLHUB	2020-01-01	2023-01-01	-9.0002335, 36.9569567, 31.5984391, 68.021682	https://cmr.earthdata.nasa.gov/search/concepts/C2781412035-MLHUB.json	BigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe were initially selected. All the tiles were atmospherically corrected by the Sentinel-2 Level 2A product generation and formatting tool (sen2cor). Then, they were divided into 590,326 non-overlapping image patches. Each image patch was annotated by the multiple land-cover classes (i.e., multi-labels) that were provided from the CORINE Land Cover database of the year 2018 (CLC 2018).	not-provided
 C1_PANA_STUC00GTD.v1	Cartosat-1 PANA Standard Products	ISRO	2005-08-05		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1293271378-ISRO.json	This is High resolution satellite carries two PAN sensors with 2.5m resolution and fore-aft stereo capability. The payload is designed to cater to applications in cartography, terrain modeling, cadastral mapping etc.  Standard products are full scene (path-row) based geo-referenced as well as geo-orthokit  products.	not-provided
 C1_PANF_STUC00GTD.v1	Cartosat-1 PANF Standard Products	ISRO	2005-08-05		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1293271427-ISRO.json	This is High resolution satellite carries two PAN sensors with 2.5m resolution and fore-aft stereo capability. The payload is designed to cater to applications in cartography, terrain modeling, cadastral mapping etc.  Standard products are full scene (path-row) based geo-referenced as well as geo-orthokit  products.	not-provided
 CDDIS_GNSS_products_IGS20.v1	CDDIS GNSS ITRF2020 IGS products (IGS20)	CDDIS	1983-01-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2433571719-CDDIS.json	These data-derived products are the International GNSS Service (IGS) Analysis Centers' (AC) contribution to the International Terrestrial Reference Frame (ITRF) 2020.	not-provided
@@ -172,15 +140,10 @@ CIESIN_SEDAC_ESI_2005.v2005.00	2005 Environmental Sustainability Index (ESI)	SED
 CIESIN_SEDAC_USPAT_USUEXT2015.v1.00	2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods	SEDAC	2015-01-01	2015-12-31	-180, -56, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C1648035940-SEDAC.json	The 2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods data set models urban settlements in the Continental United States (CONUS) as of 2015. When applied to the combination of daytime spectral and nighttime lights satellite data, the machine learning methods achieved high accuracy at an intermediate-resolution of 500 meters at large spatial scales. The input data for these models were two types of satellite imagery: Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Light (NTL) data from the Day/Night Band (DNB), and Moderate Resolution Imaging Spectroradiometer (MODIS) corrected daytime Normalized Difference Vegetation Index (NDVI). Although several machine learning methods were evaluated, including Random Forest (RF), Gradient Boosting Machine (GBM), Neural Network (NN), and the Ensemble of RF, GBM, and NN (ESB), the highest accuracy results were achieved with NN, and those results were used to delineate the urban extents in this data set.	not-provided
 CLDMSK_L2_VIIRS_NOAA20_NRT.v1	VIIRS/NOAA-20 Cloud Mask L2 6-Min Swath 750m (NRT)	ASIPS	2020-10-08		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2003160566-ASIPS.json	The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) NASA Level-2 (L2) Cloud Mask is one of two continuity products designed to sustain the long-term records of both Moderate Resolution Imaging Spectroradiometer (MODIS) and VIIRS heritages. CLDMSK_L2_VIIRS_NOAA20_NRT is the shortname for the NOAA-20 VIIRS Near Real-time incarnation of the Cloud Mask continuity product derived from the MODIS-VIIRS cloud mask (MVCM) algorithm, which itself is based on the MODIS (MOD35) algorithm. MVCM describes a continuity algorithm that is central to both MODIS data (from Terra and Aqua missions) and VIIRS data (from SNPP and Joint Polar Satellite System missions). Please bear in mind that the term MVCM does not appear as an attribute within the product’s metadata. Implemented to consistently handle MODIS and VIIRS inputs, the NOAA-20 VIIRS collection-1 products use calibration-adjusted NASA VIIRS L1B as inputs. The nominal spatial resolution of the NOAA-20 VIIRS L2 Cloud mask is 750 meters.	not-provided
 CLDMSK_L2_VIIRS_SNPP_NRT.v1	VIIRS/SNPP Cloud Mask L2 6-Min Swath 750m (NRT)	ASIPS	2019-04-18		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1607563719-ASIPS.json	The Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) NASA Level-2 (L2) Cloud Mask is one of two continuity products designed to sustain the long-term records of both Moderate Resolution Imaging Spectroradiometer (MODIS) and VIIRS heritages. CLDMSK_L2_VIIRS_SNPP is the shortname for the SNPP VIIRS incarnation of the Cloud Mask continuity product derived from the MODIS-VIIRS cloud mask (MVCM) algorithm, which itself is based on the MODIS (MOD35) algorithm. MVCM describes a continuity algorithm that is central to both MODIS data (from Terra and Aqua missions) and VIIRS data (from SNPP and Joint Polar Satellite System missions). Please bear in mind that the term MVCM does not appear as an attribute within the product’s metadata. Implemented to consistently handle MODIS and VIIRS inputs, the SNPP VIIRS collection-1 products use calibration-adjusted NASA VIIRS L1B as inputs. The nominal spatial resolution of the SNPP VIIRS L2 Cloud mask is 750 meters.	not-provided
-COARE_cm_er2.mas.v1	MODIS Airborne Simulator (MAS) Measurements Taken Onboard the NASA ER-2 During the TOGA COARE Intensive Observing Period.	LAADS	1993-01-03	1993-03-04	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1625703857-LAADS.json	The MODIS Airborne Simulator (MAS) Measurements, taken onboard the NASA ER-2 during the TOGA COARE Intensive Observing Period, are available upon request from NASA LAADS. Browse products are available at https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/mas/. The ER-2 navigation data are available from the same site in sub directory nasa_er2/nav. Browse imagery of the data may be viewed from the MAS Homepage at: https://mas.arc.nasa.gov/data/deploy_html/toga_home.html. MAS Level 1B data are available on 8500 density 8mm tape from TOGA COARE User Services at the Goddard DAAC.  Each tape contains all the flight lines for one MAS flight (one day). The number of flight lines varies, but is generally between 10 and 20. The volume of data varies, but is generally 1 to 3 gigabytes per flight.  Detailed instructions for reading MAS tapes is contained in MAS_Usr_Guide.ps. To obtain the data on tape, contact the DAAC User Services Office.  For help with NASA TOGA COARE data residing at the GSFC DAAC, contact Pat Hrubiak at hrubiak@daac.gsfc.nasa.gov.   BACK GROUND: TOGA COARE was a multidisciplinary, international research effort that investigated the scientific phenomena associated with the interaction between the atmosphere and the ocean in the warm pool region of the western Pacific. The field experiment phase of the program took place from 1 November 1992 through 28 February 1993 and involved the deployment of oceanographic ships and buoys, several ship and land based Doppler radars, multiple low and high level aircraft equipped with Doppler radar and other airborne sensors, as well as a variety of surface based instruments for in situ observations. The NASA component of TOGA COARE, while contributing directly to over all COARE objectives, emphasized scientific objectives associated with the Tropical Rainfall Measuring Mission (TRMM) and NASA's cloud and radiation program.  AIRCRAFT INFORMATION: The NASA ER-2 is a high altitude, single pilot aircraft based at Ames Research Center, Moffett Field, CA, and deployed globally in support of a variety of atmospheric research projects. It has a maximum altitude of 70,000 feet (21 km), a range of 3000 nautical miles, a maximum flight duration of 8 hours (nominal 6.5 hours) and a top speed of 410 knots true air speed. The aircraft accommodates about 2700 pounds (1200 kg) of payload.  For the TOGA COARE campaign, the ER-2 payload consisted of a variety of radiometers, a lidar, a conductivity probe and a camera.   FLIGHT INFORMATION: The following table relates MAS data files to ER-2 and DC-8 flight numbers and to the UTC dates for the 13 mission flights of the NASA/TOGA COARE campaign and 2 additional flights of the ER-2 on which MAS data was acquired. The objectives (Obj) column is included for the convenience of the user; the mission objective defaulted to radiation (Rad) unless convection (Con) was forecast in the target area. Date (UTC) ER-2 Flight DC-8 Flight MAS TapeID Obj-Jan 11-12  93-053  93-01-06 93-053 RadJan 17-18 93-054 93-01-07 93-054 Con Jan 18-19 93-055 93-01-08 93-055 Con Jan 25-26 93-056 93-01-09 93-056 RadJan 28-29 93-057 93-057 Jan 31-Feb 1 93-058 93-01-10 93-058 Rad Feb 2 93-059 93-059 Feb 4 93-060 93-01-11 93-060 Con Feb 6 93-01-12 Con Feb 7 93-061 93-061 Feb 8-9 93-062 93-01-13 93-062 Con Feb 10-11 93-063 93-01-14 93-063 Con Feb 17-18 93-01-15 93-064 Con Feb 19-20 93-064 93-064 Feb 20-21 93-065 93-01-16 93-065 Con Feb 22-23 93-066 93-01-17 Con Feb 23-24 93-067 93-01-18 Rad.   INSTRUMENT INFORMATION: The MODIS Airborne Simulator is a visible/infrared imaging radiometer that was mounted, for this campaign, in the right aft wing pod of the ER-2 aircraft. Through cross track scanning to the aircraft direction of flight, the MAS instrument builds a continuous sequence image of the atmosphere surface features under the aircraft. Wavelength channels of the instrument are selected for specific cloud and surface remote sensing applications. Also the channels are those which will be incorporated in measurements by the space borne MODIS instrument. The MAS instrument acquires eleven simultaneous wavelengths with 100 meters or better resolution at the surface.   Principles of Operation: The MAS Spectrometer acquires high spatial resolution imagery in the wavelength range 0.55 to 14.3 microns. A total of 50 spectral bands are available in this range, and currently the digitize is configured before each mission to record in any 12 of these bands during flight. For all pre-1994 MAS missions, the 12-channel digitize was configured with four 10-bit channels and seven 8-bit channels. The MAS spectrometer is mated to a scanner sub-assembly which collects image data with an IFOV of 2.5 mrad, giving a ground resolution of 50 meters from 20,000 meters altitude,and a cross track scan width of 85.92 degrees. A 50 channel digitizer which records all 50 spectral bands at 12 bit resolution became operational in January 1995.   DATA ORGANIZATION Data Format: The archive tapes are created by writing each output data file (1 straight-line flight track) to tape in fixed-length blocks of 16384 bytes, in time ascending order. One end-of-file (EOF) mark is written at the end of the data blocks for each file, and an extra EOF is written at the end of the data on the tape.  The last block of each file has good data at the start of the block and unused bytes (filled with null characters) at the end. Information on the length of the file is encoded in the header when the file is created. No file name,protection, or ownership information is written onto the archive tape. All information necessary to identify the file is stored in the file itself.  Documentation:  In addition to this document, please obtain Volume 3, MODIS Airborne Simulator Level 1B Data Users Guide, resident in this directory in postscript file MAS_Usr_Guide.ps.   Browse Products: There are 2 GIF image files per flight line, named 93ddd??v.gif and 93ddd??i.gif, where 93 is the year, ddd the Julian day of the flight, ?? the flight line number, and v or i, indicating respectively visible (VIS) or Infrared (IR) imagery. Images from each flight, accompanied by a flight statistics summary file, reside in a sub directory named with the date of the flight (02feb93) under mas/images.	not-provided
-CSU Synthetic Attribution Benchmark Dataset.v1	CSU Synthetic Attribution Benchmark Dataset	MLHUB	2020-01-01	2023-01-01	-179.5, -89.5, 179.5, 89.5	https://cmr.earthdata.nasa.gov/search/concepts/C2781411899-MLHUB.json	This is a synthetic dataset that can be used by users that are interested in benchmarking methods of explainable artificial intelligence (XAI) for geoscientific applications. The dataset is specifically inspired from a climate forecasting setting (seasonal timescales) where the task is to predict regional climate variability given global climate information lagged in time. The dataset consists of a synthetic input X (series of 2D arrays of random fields drawn from a multivariate normal distribution) and a synthetic output Y (scalar series) generated by using a nonlinear function F: R^d -> R.<br><br>The synthetic input aims to represent temporally independent realizations of anomalous global fields of sea surface temperature, the synthetic output series represents some type of regional climate variability that is of interest (temperature, precipitation totals, etc.) and the function F is a simplification of the climate system.<br><br>Since the nonlinear function F that is used to generate the output given the input is known, we also derive and provide the attribution of each output value to the corresponding input features. Using this synthetic dataset users can train any AI model to predict Y given X and then implement XAI methods to interpret it. Based on the “ground truth” of attribution of F the user can assess the faithfulness of any XAI method.<br><br>NOTE: the spatial configuration of the observations in the NetCDF database file conform to the planetocentric coordinate system (89.5N - 89.5S, 0.5E - 359.5E), where longitude is measured in the positive heading east from the prime meridian.	not-provided
-CV4A Kenya Crop Type Competition.v1	CV4A Kenya Crop Type Competition	MLHUB	2020-01-01	2023-01-01	34.0220685, 0.1670219, 34.38443, 0.7160466	https://cmr.earthdata.nasa.gov/search/concepts/C2781412688-MLHUB.json	This dataset was produced as part of the [Crop Type Detection competition](https://zindi.africa/competitions/iclr-workshop-challenge-2-radiant-earth-computer-vision-for-crop-recognition) at the [Computer Vision for Agriculture (CV4A) Workshop](https://www.cv4gc.org/cv4a2020/) at the ICLR 2020 conference. The objective of the competition was to create a machine learning model to classify fields by crop type from images collected during the growing season by the Sentinel-2 satellites. <br><br> The ground reference data were collected by the PlantVillage team, and Radiant Earth Foundation curated the training dataset after inspecting and selecting more than 4,000 fields from the original ground reference data. The dataset has been split into training and test sets (3,286 in the train and 1,402 in the test). <br><br> The dataset is cataloged in four tiles. These tiles are smaller than the original Sentinel-2 tile that has been clipped and chipped to the geographical area that labels have been collected. <br><br> Each tile has a) 13 multi-band observations throughout the growing season. Each observation includes 12 bands from Sentinel-2 L2A product, and a cloud probability layer. The twelve bands are [B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12]. The cloud probability layer is a product of the Sentinel-2 atmospheric correction algorithm (Sen2Cor) and provides an estimated cloud probability (0-100%) per pixel. All of the bands are mapped to a common 10 m spatial resolution grid.; b) A raster layer indicating the crop ID for the fields in the training set; and c) A raster layer indicating field IDs for the fields (both training and test sets). Fields with a crop ID of 0 are the test fields.	not-provided
 CWIC_REG.v1.0	Radarsat-2 Scenes, Natural Resources Canada	CCMEO	2008-04-27		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2204659831-CCMEO.json	The collection represents browse images and metadata for systematically georeferenced Radarsat-2 Synthetic Aperture Radar(SAR) satellite scenes. The browse scenes are not geometrically enhanced using ground control points, but are systematically corrected using sensor parameters. Full resolution precision geocoded scenes(corrected using ground control points) which correspond to the browse images can be ordered from MacDonald Dettwiler and Associates Ltd., Vancouver, Canada. Metadata discovery is achieved using the online catalog http://neodf.nrcan.gc.ca OR by using the CWIC OGC CSW service URL : http://cwic.csiss.gmu.edu/cwicv1/discovery. The imaging frequency is C Band SAR : 5405.0000 MHz. RADARSAT-2 is in a polar, sun-synchronous orbit with a period of approximately 101 minutes. The RADARSAT-2 orbit will be maintained at +\/- 1 km in across track direction. This orbit maintenance is suitable for InSAR data collection. The geo-location accuracy of RADARSAT-2 products varies with product type. It is currently estimated at +\/- 30 m for Standard beam products.  The revisit period for RADARSAT-2 depends on the beam mode, incidence angle and geographic location of the area of interest. In general, revisit is more frequent at the poles than the equator and the wider swath modes have higher revisit than t he narrow swath modes.	not-provided
 CWIC_REG_RCM.v1.0	RCM (Radarsat Constellation Mission ) Products, Natural Resources Canada	CCMEO	2019-06-12	2026-06-12	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2204659595-CCMEO.json	The collection represents products and metadata for georeferenced Radarsat Constellation Mission ( RCM ) satellite scenes. Metadata discovery and product ordering is achieved using the online catalog https://www.eodms-sgdot.nrcan-rncan.gc.ca/index-en.html OR by using the CWIC OpenSearch OSDD : http://cwic.csiss.gmu.edu/cwicv1/discovery. 	not-provided
 CWIC_REG_Radarsat-1.v1.0	Radarsat-1 Scenes, Natural Resources Canada	CCMEO	1996-01-11	2013-03-29	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2204658925-CCMEO.json	The collection represents browse images and metadata for systematically georeferenced Radarsat-1 Synthetic Aperture Radar(SAR) satellite scenes. The browse scenes are not geometrically enhanced using ground control points, but are systematically corrected using sensor parameters. Full resolution precision geocoded scenes(corrected using ground control points) which correspond to the browse images can be ordered from MacDonald Dettwiler and Associates Ltd., Vancouver, Canada. Metadata discovery is achieved using the online catalog https://neodf.nrcan.gc.ca/neodf_cat3 OR by using the CWIC OGC CSW service URL : http://cwic.csiss.gmu.edu/cwicv1/discovery.  Radarsat-1 operates at 5.3 GHz. (C-Band). It is in a sun-synchronous orbit. Image resolution is in the range 8-100 meters.	not-provided
 Catlin_Arctic_Survey.v0	2011 R/V Catlin cruise in the Arctic Ocean	OB_DAAC	2011-03-17		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360181-OB_DAAC.json	Measurements made in the Arctic Ocean by the RV Catlin in 2011.	not-provided
-Chesapeake Land Cover.v1	Chesapeake Land Cover	MLHUB	2020-01-01	2023-01-01	-80.8092703, 36.5643108, -74.2529408, 43.9973515	https://cmr.earthdata.nasa.gov/search/concepts/C2781412641-MLHUB.json	This dataset contains high-resolution aerial imagery from the USDA NAIP program, high-resolution land cover labels from the Chesapeake Conservancy, low-resolution land cover labels from the USGS NLCD 2011 dataset, low-resolution multi-spectral imagery from Landsat 8, and high-resolution building footprint masks from Microsoft Bing, formatted to accelerate machine learning research into land cover mapping. The Chesapeake Conservancy spent over 10 months and $1.3 million creating a consistent six-class land cover dataset covering the Chesapeake Bay watershed. While the purpose of the mapping effort by the Chesapeake Conservancy was to create land cover data to be used in conservation efforts, the same data can be used to train machine learning models that can be applied over even wider areas.	not-provided
-Cloud to Street - Microsoft flood dataset.v1	Cloud to Street - Microsoft flood dataset	MLHUB	2020-01-01	2023-01-01	-96.631888, -25.250962, 141.118143, 48.745167	https://cmr.earthdata.nasa.gov/search/concepts/C2781412798-MLHUB.json	The C2S-MS Floods Dataset is a dataset of global flood events with labeled Sentinel-1 & Sentinel-2 pairs. There are 900 sets (1800 total) of near-coincident Sentinel-1 and Sentinel-2 chips (512 x 512 pixels) from 18 global flood events. Each chip contains a water label for both Sentinel-1 and Sentinel-2, as well as a cloud/cloud shadow mask for Sentinel-2. The dataset was constructed by Cloud to Street in collaboration with and funded by the Microsoft Planetary Computer team.	not-provided
 DLG100K	1:100,000-scale Digital Line Graphs (DLG) from the U.S. Geological Survey	USGS_LTA	1987-06-19		-126, 24, -66, 49	https://cmr.earthdata.nasa.gov/search/concepts/C1220566434-USGS_LTA.json	Digital line graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 1:100,000-scale 30- by 60-minute  quadrangle maps. If these maps are not available, Bureau of Land Management planimetric maps at a scale of 1: 100,000 are used. Intermediate-scale DLG's are sold in five categories: (1)  Public Land Survey System; (2) boundaries (3) transportation; (4)  hydrography; and (5) hypsography.  All DLG data distributed by the USGS are DLG - Level 3 (DLG-3), which means the data contain a full range of attribute codes, have full topological structuring, and have passed certain quality-control checks. 	not-provided
 EARTH_LAND_USGS_AMES_AIR_PHOTOS	Aerial Photographs (from AMES Pilot Land Data System); USGS EDC, Sioux Falls	USGS_LTA	1970-01-01		-180, 20, -60, 50	https://cmr.earthdata.nasa.gov/search/concepts/C1220566371-USGS_LTA.json	"The aerial photography inventoried by the Pilot Land Data System  (PLDS) at NASA AMES Research Center has been transferred to the USGS EROS  Data Center.  The photos were obtained from cameras mounted on high and  medium altitude aircraft based at the NASA Ames Research Center.  Several  cameras with varying focal lengths, lenses and film formats are used, but  the Wild RC-10 camera with a focal length of 152 millimeters and a 9 by 9  inch film format is most common.  The positive transparencies are typically  used for ancillary ground checks in conjunctions with digital processing for  the same sites.  The aircraft flights, specifically requested by scientists  performing approved research, often simultaneously collect data using other  sensors on        board (e.g. Thematic Mapper Simulators (TMS) and Thermal Infrared  Multispectral Scanners).  High altitude color infrared photography is used  regularly by government agencies for such applications as crop yield forecasting,  timber inventory and defoliation assessment, water resource management,  land use surveys, water pollution monitoring, and natural disaster  assessment.  To order, specify the latitude and longitude of interest.  You will  then be given a list of photos available for that location.  In some cases,  ""flight books"" are available at EDC that describe the nature of the mission  during which the photos were taken and other attribute information.  The  customer service personnel have access to these books for those photo sets  for which the books exist."	not-provided
 ECO_L1B_ATT.v002	ECOSTRESS Swath Attitude and Ephemeris Instantaneous L1B Global V002	LPCLOUD	2018-07-09		-180, -54, 180, 54	https://cmr.earthdata.nasa.gov/search/concepts/C2076117996-LPCLOUD.json	The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data globally as well as key biomes and agricultural zones around the world and selected FLUXNET (http://fluxnet.fluxdata.org/about/) validation sites. A map of the acquisition coverage can be found on the ECOSTRESS website (https://ecostress.jpl.nasa.gov/science).  The ECOSTRESS Swath Attitude and Ephemeris Instantaneous Level 1B Global (ECO_L1B_ATT) Version 2 data product provides both corrected and uncorrected attitude quaternions and spacecraft ephemeris data obtained from the ISS. The data are provided in 1 second intervals, and each product file contains vectors from the duration of the orbit.   The ECO_L1B_ATT Version 2 data product contains layers of attitude and ephemeris data generated by the ISS, which are used to start the geolocation process. These layers also include Earth-centered inertial (ECI) position and velocity, and associated time elements distributed in HDF5 format.    Known Issues: *Cannot perform spatial query on ECO_L1B_ATT in NASA Earthdata Search: ECO_L1B_ATT does not contain spatial attributes, so granules cannot be searched by geographic location. Users should search for ECO_L1B_ATT data products by orbit number instead.  *Data acquisition gap: ECOSTRESS was launched on June 29, 2018, and moved to autonomous science operations on August 20, 2018, following a successful in-orbit checkout period. On September 29, 2018, ECOSTRESS experienced an anomaly with its primary mass storage unit (MSU). ECOSTRESS has a primary and secondary MSU (A and B). On December 5, 2018, the instrument was switched to the secondary MSU and science operations resumed. On March 14, 2019, the secondary MSU experienced a similar anomaly, temporarily halting science acquisitions. On May 15, 2019, a new data acquisition approach was implemented, and science acquisitions resumed.  *Data acquisition: ECOSTRESS has now successfully returned to 5-band mode after being in 3-band mode since 2019. This feature was successfully enabled following a Data Processing Unit firmware update (version 4.1) to the payload on April 28, 2023. To better balance contiguous science data scene variables, 3-band collection is currently being interleaved with 5-band acquisitions over the orbital day/night periods.	not-provided
@@ -226,10 +189,6 @@ GGD632.v1	Active-Layer and Permafrost Temperatures, Soendre Stroemfjord, Greenla
 GISS-CMIP5.v1	GISS ModelE2 contributions to the CMIP5 archive	NCCS	0850-01-01	2100-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542315069-NCCS.json	We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.	not-provided
 GMAO-CMIP5.v1	GMAO Decadal Analysis & Prediction for CMIP5	NCCS	1961-01-01	2019-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542704969-NCCS.json	Studies of change and variations on decadal timescales are essential for planning satellite missions that seek to improve our understanding of linkages among various components of the Earth System. Decadal predictions using a version of the GEOS-5 AOGCM were contributed to the CMIP5 project. The dataset include a three-member ensemble initialized on December 1 of each year from 1960 to 2010. These data are available, with the designation NASA GMAO, from the CMIP5 Archive at NASA NCCS.	not-provided
 GOMIGEO.v002	MISR Geometric Parameters subset for the GoMACCS region V002	LARC	2006-07-30	2006-10-17	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1625796320-LARC.json	Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Geometric Parameters subset for the GoMACCS region V002 contains the Geometric Parameters which measure the sun and view angles at the reference ellipsoid.	not-provided
-Global_Litter_Carbon_Nutrients_1244.v1	A Global Database of Litterfall Mass and Litter Pool Carbon and Nutrients	ORNL_CLOUD	1827-01-01	1997-12-31	-156.7, -54.5, 176.2, 72.5	https://cmr.earthdata.nasa.gov/search/concepts/C2784385713-ORNL_CLOUD.json	Measurement data of aboveground litterfall and littermass and litter carbon, nitrogen, and nutrient concentrations were extracted from 685 original literature sources and compiled into a comprehensive database to support the analysis of global patterns of carbon and nutrients in litterfall and litter pools. Data are included from sources dating from 1827 to 1997. The reported data include the literature reference, general site information (description, latitude, longitude, and elevation), site climate data (mean annual temperature and precipitation), site vegetation characteristics (management, stand age, ecosystem and vegetation-type codes), annual quantities of litterfall (by class, kg m-2 yr-1), litter pool mass (by class and litter layer, kg m-2), and concentrations of nitrogen (N), phosphorus (P), and base cations for the litterfall (g m-2 yr-1) and litter pool components (g m-2).  The investigators intent was to compile a comprehensive data set of individual direct field measurements as reported by researchers. While the primary emphasis was on acquiring C data, measurements of N, P, and base cations were also obtained, although the database is sparse for elements other than C and N. Each of the 1,497 records in the database represents a measurement site. Replicate measurements were averaged according to conventions described in Section 5 and recorded for each site in the database. The sites were at 575 different locations. 	not-provided
-Global_Microbial_Biomass_C_N_P_1264.v1	A Compilation of Global Soil Microbial Biomass Carbon, Nitrogen, and Phosphorus Data	ORNL_CLOUD	1977-11-16	2012-06-01	-180, -90, 177.9, 79	https://cmr.earthdata.nasa.gov/search/concepts/C2216863966-ORNL_CLOUD.json	This data set provides the concentrations of soil microbial biomass carbon (C), nitrogen (N) and phosphorus (P), soil organic carbon, total nitrogen, and total phosphorus at biome and global scales. The data were compiled from a comprehensive survey of publications from the late 1970s to 2012 and include 3,422 data points from 315 papers. These data are from soil samples collected primarily at 0-15 cm depth with some from 0-30 cm. In addition, data were compiled for soil microbial biomass concentrations from soil profile samples to depths of 100 cm. Sampling site latitude and longitude were available for the majority of the samples that enabled assembling additional soil properties, site characteristics, vegetation distributions, biomes, and long-term climate data from several global sources of soil, land-cover, and climate data. These site attributes are included with the microbial biomass data. This data set contains two *.csv files of the soil microbial biomass C, N, P data. The first provides all compiled results emphasizing the full spatial extent of the data, while the second is a subset that provides only data from a series of profile samples emphasizing the vertical distribution of microbial biomass concentrations.There is a companion file, also in .csv format, of the references for the surveyed publications. A reference_number relates the data to the respective publication.The concentrations of soil microbial biomass, in combination with other soil databases, were used to estimate the global storage of soil microbial biomass C and N in 0-30 cm and 0-100 cm soil profiles. These storage estimates were combined with a spatial map of 12 major biomes (boreal forest, temperate coniferous forest, temperate broadleaf forest, tropical and subtropical forests, mixed forest, grassland, shrub, tundra, desert, natural wetland, cropland, and pasture) at 0.05-degree by 0.5-degree spatial resolution. The biome map and six estimates of C and N storage and C:N ration in soil microbial biomass are provided in a single netCDF format file. 	not-provided
-Global_Phosphorus_Hedley_Fract_1230.v1	A Global Database of Soil Phosphorus Compiled from Studies Using Hedley Fractionation	ORNL_CLOUD	1985-01-01	2010-12-31	-117.86, -42.5, 117.6, 63.23	https://cmr.earthdata.nasa.gov/search/concepts/C2216863440-ORNL_CLOUD.json	This data set provides concentrations of soil phosphorus (P) compiled from the peer-reviewed literature that cited the Hedley fractionation method (Hedley and Stewart, 1982). This database contains estimates of different forms of naturally occurring soil phosphorus, including labile inorganic P, organic P, occluded P, secondary mineral P, apatite P, and total P, based on the analyses of the various Hedley soil fractions.The recent literature survey (Yang and Post, 2011) was restricted to studies of natural, unfertilized, and uncultivated soils since 1995. Ninety measurements of soil P fractions were identified. These were added to the 88 values from soils in natural ecosystems that Cross and Schlesinger (1995) had compiled. Cross and Schlesinger provided a comprehensive survey on Hedley P data prior to 1995. Measurement data are provided for studies published from 1985 through 2010. In addition to the Hedley P fraction measurement data Yang and Post (2011) also compiled information on soil order, soil pH, organic carbon and nitrogen content, as well as the geographic location (longitude and latitude) of the measurement sites. 	not-provided
-Global_RTSG_Flux_1078.v1	A Global Database of Gas Fluxes from Soils after Rewetting or Thawing, Version 1.0	ORNL_CLOUD	1956-01-01	2009-12-31	-149.63, -36.45, 160.52, 74.5	https://cmr.earthdata.nasa.gov/search/concepts/C2216863284-ORNL_CLOUD.json	This database contains information compiled from published studies on gas flux from soil following rewetting or thawing. The resulting database includes 222 field and laboratory observations focused on rewetting of dry soils, and 116 field laboratory observations focused on thawing of frozen soils studies conducted from 1956 to 2010. Fluxes of carbon dioxide, methane, nitrous oxide, nitrogen oxide, and ammonia (CO2, CH4, N2O, NO and NH3) were compiled from the literature and the flux rates were normalized for ease of comparison. Field observations of gas flux following rewetting of dry soils include events caused by natural rainfall, simulated rainfall in natural ecosystems, and irrigation in agricultural lands. Similarly, thawing of frozen soils include field observations of natural thawing, simulated freezing-thawing events (i.e., thawing of simulated frozen soil by snow removal), and thawing of seasonal ice in temperate and high latitude regions (Kim et al., 2012). Reported parameters include experiment type, location, site type, vegetation, climate, soil properties, rainfall, soil moisture, soil gas flux after wetting and thawing, peak soil gas flux properties, and the corresponding study references. There is one comma-delimited data file. 	not-provided
 GreenBay.v0	2010 Measurements made in Green Bay, Wisconsin	OB_DAAC	2010-09-17		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360352-OB_DAAC.json	Measurements made in Green Bay, Wisconsin in 2010.	not-provided
 IKONOS_MSI_L1B.v1	IKONOS Level 1B Multispectral 4-Band Satellite Imagery	CSDA	1999-10-14	2015-03-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2497453433-CSDA.json	The IKONOS Level 1B Multispectral 4-Band Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This satellite imagery is in the visible and near-infrared waveband range with data in the blue, green, red, and near-infrared wavelengths. The spatial resolution is 3.2m at nadir and the temporal resolution is approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.	not-provided
 IKONOS_Pan_L1B.v1	IKONOS Level 1B Panchromatic Satellite Imagery	CSDA	1999-10-24	2015-03-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2497468825-CSDA.json	The IKONOS Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This data product includes panchromatic imagery with a spatial resolution of 0.82m at nadir and a temporal resolution of approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.	not-provided
@@ -250,16 +209,12 @@ KUKRI_He	(U-Th)/He ages from the Kukri Hills of southern Victoria Land	SCIOPS	19
 L1B_Wind_Products	Aeolus preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers	ESA	2020-04-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2119689596-ESA.json	The Level 1B wind product of the Aeolus mission contains the preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers, which are generated in Near Real Time. Standard atmospheric correction (Rayleigh channel), receiver response and bias correction is applied. The product is generated within 3 hours after data acquisition.	not-provided
 L2B_Wind_Products	Aeolus Scientific L2B Rayleigh/Mie wind product	ESA	2020-04-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2119689544-ESA.json	The Level 2B wind product of the Aeolus mission is a geo-located consolidated HLOS (horizontal line-of-sight) wind observation with actual atmospheric correction applied to Rayleigh channel. The product is generated by within 3 hours after data acquisition.	not-provided
 L2C_Wind_products	Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing	ESA	2020-07-09		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2619280864-ESA.json	The Level 2C wind product of the Aeolus mission provides ECMWF analysis horizontal wind vectors at the geolocations of assimilated L2B HLOS wind components.  The L2C can therefore be described as an Aeolus-assisted horizontal wind vector product. The L2C is a distinct product, however the L2C and L2B share a common Earth Explorer file template, with the L2C being a superset of the L2B.  The L2C consists of extra datasets appended to the L2B product with information which are relevant to the data assimilation of the L2B winds.	not-provided
-LAI_Woody_Plants_1231.v1	A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011	ORNL_CLOUD	1932-01-01	2011-12-31	-164.78, -54.2, 175.62, 78.42	https://cmr.earthdata.nasa.gov/search/concepts/C2784385653-ORNL_CLOUD.json	This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources.	not-provided
 LGB_10m_traverse.v1	10 m firn temperature data: LGB traverses 1990-95	AU_AADC	1989-11-01	1995-02-28	54, -77, 78, -69	https://cmr.earthdata.nasa.gov/search/concepts/C1214313574-AU_AADC.json	The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. Ten metre depth (10 m) firn temperatures, as a proxy indicator of annual mean surface temperature at a site, were recorded approximately every 30 km along the 2014 km main traverse route from LGB00 (68.6543 S, 61.1201 E) near Mawson Station, to LGB72 (69.9209 S, 76.4933 E) near Davis Station.  10 m depth firn temperatures were recorded manually in field notebooks and the data transferred to spreadsheet files (MS Excel).  Summary data (30 km spatial resolution) can be obtained from CRC Research Note No.09 'Surface Mass Balance and Snow Surface Properties from the Lambert Glacier Basin Traverses 1990-94'.  This work was completed as part of ASAC projects 3 and 2216.  Some of this data have been stored in a very old format.  The majority of files have been updated to current formats, but some files (kaleidograph files in particular) were not able to be modified due to a lack of appropriate software.  However, these files are simply figures, and can be regenerated from the raw data (also provided).  The fields in this dataset are:  Latitutde Longitude Height Cane Distance Elevation Density Mass Accumulation Year Delta Oxygen-18 Grain Size Ice Crusts Depth Hoar	not-provided
-Leaf_Carbon_Nutrients_1106.v1	A Global Database of Carbon and Nutrient Concentrations of Green and Senesced Leaves	ORNL_CLOUD	1970-01-01	2009-12-31	-159.7, -50, 176.9, 68.5	https://cmr.earthdata.nasa.gov/search/concepts/C2784383820-ORNL_CLOUD.json	This data set provides carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations in green and senesced leaves. Vegetation characteristics reported include species growth habit, leaf area, mass, and mass loss with senescence. The data were compiled from 86 selected studies in 31 countries, and resulted in approximately 1,000 data points for both green and senesced leaves from woody and non-woody vegetation as described in Vergutz et al (2012). The studies were conducted from 1970-2009. There are two comma-delimited data files with this data set.	not-provided
-Leaf_Photosynthesis_Traits_1224.v1	A Global Data Set of Leaf Photosynthetic Rates, Leaf N and P, and Specific Leaf Area	ORNL_CLOUD	1993-01-01	2010-12-31	-122.4, -43.2, 176.13, 58.42	https://cmr.earthdata.nasa.gov/search/concepts/C2784384781-ORNL_CLOUD.json	This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file.	not-provided
 Level_2A_aerosol_cloud_optical_products	Aeolus L2A Aerosol/Cloud optical product	ESA	2021-05-26		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2207498185-ESA.json	"The Level 2A aerosol/cloud optical products of the Aeolus mission include geo-located consolidated backscatter and extinction profiles, backscatter-to-extinction coefficient, LIDAR ratio, scene classification, heterogeneity index and attenuated backscatter signals.   Resolution -        Horizontal resolution of L2A optical properties at observation scale (~87 km);          Exceptions are group properties (horizontal accumulation of measurements from ~3 km to ~87 km) and attenuated backscatters (~3 km);           Note: the resolution of ""groups"" in the L2A can only go down to 5 measurements at the moment, i.e. ~15 km horizontal resolution. This could be configured to go to 1 measurement -        Vertical resolution 250-2000 m (Defined by Range Bin Settings https://earth.esa.int/eogateway/instruments/aladin/overview-of-the-main-wind-rbs-changes)."	not-provided
 M1_ AVH02C1.v6	METOP-B AVHRR Top-of-Atmosphere Reflectance Daily L3 Global 0.05 Deg. CMG	LAADS	2013-01-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2751091676-LAADS.json	The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present.   The CDR is critically important to studying global climate change.  The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions.  The LTDR draws from the following eight AVHRR missions:   NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.  Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR).  LAI/fPAR was developed as an experimental product.  The METOP-B AVHRR Top-of-Atmosphere Reflectance Daily L3 Global 0.05 Deg CMG, short-name M1_AVH02C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The M1_AVH02C1 consist of Top-of-atmosphere reflectance for bands 1 and 2, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), thermal data (thermal bands 3, 4 and 5), and additional data (scan time).  	not-provided
 M1_ AVH09C1.v6	METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg CMG	LAADS	2013-01-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2187507677-LAADS.json	The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present.   The CDR is critically important to studying global climate change.  The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions.  The LTDR draws from the following eight AVHRR missions:   NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.    Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR).  LAI/fPAR was developed as an experimental product.    The METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg CMG, short-name M1_ AVH09C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The M1_ AVH09C1 consist of BRDF-corrected surface reflectance for bands 1, 2, and 3, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), and thermal data (thermal bands 3, 4, and 5). The AVH09C1 product is available in HDF4 file format.  	not-provided
 M1_AVH13C1.v6	METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG	LAADS	2013-01-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2751635237-LAADS.json	The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present.   The CDR is critically important to studying global climate change.  The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions.  The LTDR draws from the following eight AVHRR missions:   NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.  Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR).  LAI/fPAR was developed as an experimental product.    The METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index (NDVI) Daily L3 Global 0.05 Deg CMG, short-name M1_AVH13C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (M1_AVH01C1). The M1_AVH13C1 product is available in HDF4 file format.  	not-provided
 MCD06COSP_D3_MODIS.v6.1	MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid	LAADS	2002-07-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1887589686-LAADS.json	The combined MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product’s short-name.  The “COSP” acronym in its short-name stands for  Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. This product is an aggregation of combined MODIS Level-2 inputs from both the Terra and Aqua incarnations (MOD35/MOD06 and MYD35/MYD06, respectively), and employs an aggregation methodology consistent with the MOD08 and MYD08 products.  Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters).	not-provided
-MCD06COSP_M3_MODIS.v6.1	MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid	LAADS	2002-07-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1888024429-LAADS.json	The combined MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product’s short-name.  The “COSP” acronym in its short-name stands for  Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. The L3 monthly product is derived by aggregating the daily-produced Aqua+Terra/MODIS D3 Cloud Properties product (MCD06COSP_D3_MODIS).  Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters).	not-provided
 MCD14DL_C5_NRT.v005	MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT	LM_FIRMS	2014-01-28		-180, -80, 180, 80	https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.json	Near Real-Time (NRT) MODIS Thermal Anomalies / Fire locations processed by FIRMS (Fire Information for Resource Management System) - Land Atmosphere Near real time Capability for EOS (LANCE), using swath products (MOD14/MYD14) rather than the tiled MOD14A1 and MYD14A1 products. The thermal anomalies / active fire represent the center of a 1km pixel that is flagged by the MODIS MOD14/MYD14 Fire and Thermal Anomalies algorithm (Giglio 2003) as containing one or more fires within the pixel. This is the most basic fire product in which active fires and other thermal anomalies, such as volcanoes, are identified.MCD14DL are available in the following formats: TXT, SHP, KML, WMS. These data are also provided through the FIRMS Fire Email Alerts. Please note only the TXT and SHP files contain all the attributes.	not-provided
 MIANACP.v1	MISR Aerosol Climatology Product V001	LARC	1999-11-22		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C185127378-LARC.json	MIANACP_1 is the Multi-angle Imaging SpectroRadiometer (MISR) Aerosol Climatology Product version 1. It is 1) the microphysical and scattering characteristics of pure aerosol upon which routine retrievals are based; 2) mixtures of pure aerosol to be compared with MISR observations; and 3) likelihood value assigned to each mode geographically. The ACP describes mixtures of up to three component aerosol types from a list of eight components, in varying proportions. ACP component aerosol particle data quality depends on the ACP input data, which are based on aerosol particles described in the literature, and consider MISR-specific sensitivity to particle size, single-scattering albedo, and shape, and shape - roughly: small, medium and large; dirty and clean; spherical and nonspherical [Kahn et al. , 1998; 2001]. Also reported in the ACP are the mixtures of these components used by the retrieval algorithm. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.	not-provided
 MIANCAGP.v1	MISR Ancillary Geographic Product V001	LARC	1999-11-07	2005-06-30	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C183897339-LARC.json	MIANCAGP_1 is the Multi-angle Imaging SpectroRadiometer (MISR) Ancillary Geographic Product version 1. It is a set of 233 pre-computed files. Each AGP file pertains to a single Terra orbital path. MISR production software relies on information in the AGP, such as digital terrain elevation, as input to the algorithms which generate MISR products. The AGP contains eleven fields of geographical data. This product consists primarily of geolocation data on a Space Oblique Mercator (SOM) Grid. It has 233 parts, corresponding to the 233 repeat orbits of the EOS-AM1 Spacecraft. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.	not-provided
@@ -272,11 +227,9 @@ MYD021KM.v6.1NRT	MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 1km - NRT	LANCE
 MYD02HKM.v6.1NRT	MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 500m - NRT	LANCEMODIS	2017-10-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1426617060-LANCEMODIS.json	The 500 meter MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 7 discrete bands located in the 0.45 to 2.20 micron region of the electromagnetic spectrum. These data are generated from the MODIS Level 1A scans of raw radiance and in the process converted to geophysical units of W/(m^2 um sr). In addition, the Earth Bi-directional Reflectance Distribution Function (BRDF) may be determined for these solar reflective bands through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry).  Additional data are provided including quality flags, error estimates and calibration data.  Visible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously.  Channel locations for the MODIS 500 meter data are as follows:  Band   Center Wavelength (um)    Primary Use ----   ----------------------    ----------- 1          0.620  - 0.670        Land/Cloud Boundaries 2          0.841  - 0.876        Land/Cloud Boundaries 3          0.459  - 0.479        Land/Cloud Properties 4          0.545  - 0.565        Land/Cloud Properties 5          1.230  - 1.250        Land/Cloud Properties 6          1.628  - 1.652        Land/Cloud Properties 7          2.105  - 2.155        Land/Cloud Properties  Channels 1 and 2 have 250 m resolution, channels 3 through 7 have 500 m resolution. However, for the MODIS L1B 500 m product, the 250 m band radiance data and their associated uncertainties have been aggregated to 500 m resolution. Thus the entire channel data set has been co-registered to the same spatial scale in the 500 m product. Separate L1B products are available for the 250 m resolution channels (MYD02QKM) and 1 km resolution channels (MYD021KM). For the latter product, the 250 m and 500 m channel data (bands 1 through 7) have been aggregated into equivalent 1 km pixel values.  Spatial resolution for pixels at nadir is 500 km, degrading to 2.4 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and respectively pixels there, the resulting resolution at the scan extremes is about 1 km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width and provides global coverage every one to two days. A single MODIS Level 1B 500 m granule will contain a scene built from 203 scans sampled 2708 times in the cross-track direction, corresponding to approximately 5 minutes worth of data; thus 288 granules will be produced per day. Since an individual MODIS scan will contain 20 along-track spatial elements for the 500 m channels, the scene will be composed of (2708 x 4060) pixels, resulting in a spatial coverage of (2330 km x 2040 km). Due to the MODIS scan geometry, there will be increasing scan overlap beyond about 20 degrees scan angle.  To summarize, the MODIS L1B 500 m data product consists of:  1. Calibrated radiances, uncertainties and number of samples for (2) 250 m reflected solar bands aggregated to 500 m resolution  2. Calibrated radiances and uncertainties for (5) 500 m reflected solar bands  3. Geolocation for 1km pixels, that must be interpolated to get 500 m pixel locations. For the relationship of 1km pixels to 500m pixels, see the Geolocation ATBD http://modis.gsfc.nasa.gov/data/atbd/atbd_mod28_v3.pdf .  4. Calibration data for all channels (scale and offset)  5. Comprehensive set of file-level metadata summarizing the spatial, temporal and parameter  attributes of the data, as well as auxiliary information pertaining to instrument status and data quality characterization   The MODIS L1B 500 m data are stored in the Earth Observing System Hierarchical Data Format (HDF-EOS) which is an extension of HDF as developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois. A typical file size will be approximately 170 MB.  Environmental information derived from MODIS L1B measurements will offer a comprehensive and unprecedented look at terrestrial, atmospheric, and ocean phenomenology for a wide and diverse community of users throughout the world.  The Shortname for this product is MYD02HKM	not-provided
 MYD02QKM.v6.1NRT	MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 250m - NRT	LANCEMODIS	2017-10-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1426621826-LANCEMODIS.json	The 250 meter MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated  at-aperture radiances for 2 discrete bands located in the 0.62 to 0.88 micron  region of the electromagnetic spectrum. These data are generated from the MODIS  Level 1A scans of raw radiance and in the process converted to geophysical  units of W / (m^2 um sr). In addition, the Earth Bi-directional Reflectance Distribution Function (BRDF) may be determined for these solar reflective bands  through knowledge of the solar irradiance (e.g., determined from MODIS solar  diffuser data, and from the target illumination geometry).  Additional data are  provided including quality flags, error estimates and calibration data. Channel locations for the MODIS 250 meter data are as follows:  Band   Center Wavelength (um)    Primary Use ----   ----------------------    ----------- 1          0.620  - 0.670        Land/Cloud Boundaries 2          0.841  - 0.876        Land/Cloud Boundaries  Separate L1B products are available for the five 500 m resolution channels (MYD02HKM) and the twenty-nine 1 km resolution channels (MYD021KM). For the 500 m product, there are actually seven channels available since the data from the two 250 m channels have been aggregated to 500 m resolution.  Similarly, for the 1 km product, all 36 MODIS channels are available since the data from the two 250 m and five 500 m channels have been aggregated into equivalent 1 km pixel values.  Spatial resolution for pixels at nadir is 250 m, degrading to 1.2 km in the along-scan direction and 0.5 km in the along-track direction for pixels located at the scan extremes. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width and provides global coverage every one to two days. A single MODIS Level 1B 250 m granule will contain a scene built from 203 scans sampled 5416 times in the cross-track direction, corresponding to approximately 5 minutes worth of data; thus 288 granules will be produced per day. Since an individual MODIS scan will contain 40 along-track spatial elements for the 250 m channels, the scene will be composed of (5416 x 8120) pixels, resulting in a spatial coverage of (2330 km x 2040 km). Due to the MODIS scan geometry, there will be increasing scan overlap beyond about 17 degrees scan angle. To summarize, the MODIS L1B 250 m data product consists of:  1. Calibrated radiances and uncertainties for (2) 250 m reflected solar bands  2. Subsampled geolocation at every 4th 250 m pixel across and along track, i.e., a geolocation point every kilometer  3. Satellite and solar angles subsampled at the above frequency  4. Calibration data for all channels (scale and offset)  5. Comprehensive set of file-level metadata summarizing the spatial, temporal and parameter attributes of the data, as well as auxiliary information pertaining to instrument status and data quality characterization  The MODIS L1B 250 m data are stored in the Earth Observing System Hierarchical Data Format (HDF-EOS) which is an extension of HDF as developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois. A typical file size will be approximately 170 MB.  Environmental information derived from MODIS L1B measurements will offer a comprehensive and unprecedented look at terrestrial, atmospheric, and ocean phenomenology for a wide and diverse community of users throughout the world. The Shortname for this product is MYD02QKM	not-provided
 MYD04_3K.v6.1NRT	MODIS/Aqua Aerosol 5-Min L2 Swath 3km - NRT	LANCEMODIS	2017-10-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1426717545-LANCEMODIS.json	The new Collection 6.1 (C61) MYD04_3K product is an improved version based on algorithm changes in Dark Target (DT) Aerosol retrieval over urban areas and uncertainty estimates for Deep Blue (DB) Aerosol retrievals.  The MODIS level-2 atmospheric aerosol product provides retrieved ambient aerosol optical properties, quality assurance, and other parameters, globally over ocean and land. In Collection 5, and earlier collections, there was only one aerosol product (MOD04_L2) at 10km (at nadir) spatial resolution. Starting from C6, the Dark Target (DT) Aerosol algorithm team provided a new 3 km spatial resolution product (MOD04_3k) intended for the air quality community.  The MOD04_3K product is based on the same algorithm and Look up Tables as the standard Dark Target aerosol product. Because of finer resolution, subtle differences are made in selecting pixels for retrieval and in determining QA. The only differences between the existing 10km algorithm and the 3km algorithm are: 1) the size of the pixel-arrays defining each retrieval box (6x6 retrieval boxes of 36 pixels at 0.5km resolution for 3km algorithm as oppose to 20x20 retrieval boxes of 400 pixels at 0.5km resolution for 10km product); 2) the minimum percentage of good pixels required for a retrieval (a minimum of 5 pixels over ocean and 6 pixels over land instead of a minimum of 10 pixels over ocean or 12 pixels over land for 10km product retrieval); 3) the 10km algorithm attempts a poor quality retrieval while 3km algorithm does not. Everything else is same in two products.  For more information on C6.1 changes and updates, visit the MODIS Atmosphere website at: https://modis-atmosphere.gsfc.nasa.gov/documentation/collection-61	not-provided
-MYD04_L2.v6.1	MODIS/Aqua Aerosol 5-Min L2 Swath 10km	LAADS	2002-07-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1443533683-LAADS.json	The MODIS/Aqua Aerosol 5-Min L2 Swath 10km product (MYD04_L2) provides full global coverage of aerosol properties from the Dark Target (DT) and Deep Blue (DB) algorithms. The DT algorithm is applied over ocean and dark land (e.g., vegetation), while the DB algorithm now covers the entire land areas including both dark and bright surfaces. Both results are provided on a 10x10 pixel scale (10 km at nadir). Each MYD04_L2 product file covers a five-minute time interval. The output grid is 135 pixels in width by 203 pixels in length. Every tenth file has an output grid size of 135 by 204 pixels. MYD04_L2 product files are stored in Hierarchical Data Format (HDF-EOS).    The new Collection 6.1 (C61) MYD04_L2 product is an improved version based on algorithm changes in Dark Target (DT) Aerosol retrieval over urban areas and uncertainty estimates for Deep Blue (DB) Aerosol retrievals.    The MODIS level-2 atmospheric aerosol product provides retrieved ambient aerosol optical properties, quality assurance, and other parameters, globally over ocean and land. In Collection 5 and in earlier collections, there was only one aerosol product (MYD04_L2) at 10km (at nadir) spatial resolution. Starting from C6, the Dark Target (DT) Aerosol algorithm team provided a new 3 km spatial resolution product (MYD04_3k) intended for the air quality community.      For more information visit the MODIS Atmosphere website at:  https://modis-atmos.gsfc.nasa.gov/products/aerosol    And, for C6.1 changes and updates, visit:  https://modis-atmosphere.gsfc.nasa.gov/documentation/collection-61	not-provided
 MYD04_L2.v6.1NRT	MODIS/Aqua Aerosol 5-Min L2 Swath 10km - NRT	LANCEMODIS	2017-10-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1426751946-LANCEMODIS.json	The new Collection 6.1 (C61) MYD04_L2 product is an improved version based on algorithm changes in Dark Target (DT) Aerosol retrieval over urban areas and uncertainty estimates for Deep Blue (DB) Aerosol retrievals.  The MODIS level-2 atmospheric aerosol product provides retrieved ambient aerosol optical properties, quality assurance, and other parameters, globally over ocean and land. In Collection 5, and earlier collections, there was only one aerosol product (MYD04_L2) at 10km (at nadir) spatial resolution. Starting from C6, the Dark Target (DT) Aerosol algorithm team provided a new 3 km spatial resolution product (MYD04_3k) intended for the air quality community.  For more information visit the MODIS Atmosphere website at: https://modis-atmos.gsfc.nasa.gov/products/aerosol  And, for C6.1 changes and updates, visit: https://modis-atmosphere.gsfc.nasa.gov/documentation/collection-61	not-provided
 MYD09.v6.1NRT	MODIS/Aqua Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km NRT	LANCEMODIS	2021-02-07		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2007652303-LANCEMODIS.json	The MODIS/Aqua Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km NRT, short name MYD09, is computed from the MODIS Level 1B land bands 1, 2, 3, 4, 5, 6, and 7 (centered at 648 nm, 858 nm, 470 nm, 555 nm, 1240 nm, 1640 nm, and 2130 nm, respectively). The product is an estimate of the surface spectral reflectance for each band as it would have been measured at ground level if there were no atmospheric scattering or absorption. The surface-reflectance product is the input for product generation for several land products: vegetation Indices (VIs), BRDF, thermal anomaly, snow/ice, and Fraction of Photosynthetically Active Radiation/Leaf Area Index (FPAR/LAI).	not-provided
 MYD09CMA.v6.1NRT	MODIS/Aqua Aerosol Optical Thickness Daily L3 Global 0.05-Deg CMA NRT	LANCEMODIS	2021-02-07		-180, -81, 180, 81	https://cmr.earthdata.nasa.gov/search/concepts/C2007652084-LANCEMODIS.json	The MODIS/Aqua Aerosol Optical Thickness Daily L3 Global 0.05-Deg CMA Near Real Time (NRT), short name MYD09CMA, is a daily level 3 global product. It is in linear latitude and longitude (Plate Carre) projection with a 0.05Deg spatial resolution. This product is derived from MYD09IDN, MYD09IDT and MYD09IDS for each orbit by compositing the data on the basis of minimum band 3 (459 - 479 nm band) values (after excluding pixels flagged for clouds and high solar zenith angles).	not-provided
-MYDCSR_B.v6.1	MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands	LAADS	2002-07-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1444160046-LAADS.json	The MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands (MYDCSR_B) product consists of 1-degree zonal mean clear-sky biases (observed minus calculated radiance differences) and associated statistics for bands 31 and 33-36 for each day from the previous eight-day period. Zonal means (5-zone moving averages) are created from the eight-day, 25-km radiance differences for daytime land, nighttime land, and ocean data separately. Day and night land data are combined south of -60 degrees latitude due to poor clear-sky sampling and the difficulty of discriminating between clear and cloudy conditions in this region. The zonal mean biases are utilized to correct clear-sky radiance calculations in the cloud top pressure (CO2 slicing) algorithm. The files are in Hierarchical Data Format (HDF).	not-provided
 MYDGB0.v6.1NRT	MODIS/Aqua 5-minute GBAD data in L0 format - NRT	LANCEMODIS	2017-10-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1427015288-LANCEMODIS.json	MODIS/Aqua Near Real Time (NRT) 5-minute GBAD data in L0 format.	not-provided
 NEX-DCP30.v1	Downscaled 30 Arc-Second CMIP5 Climate Projections for Studies of Climate Change Impacts in the United States	NCCS	1950-01-01	2099-12-31	-125.0208333, 24.0625, -66.4791667, 49.9375	https://cmr.earthdata.nasa.gov/search/concepts/C1542175061-NCCS.json	This NASA dataset is provided to assist the science community in conducting studies of climate  change impacts at local to regional scales, and to enhance public understanding of possible future  climate patterns and climate impacts at the scale of individual neighborhoods and communities.  This dataset is intended for use in scientific research only, and use of this dataset for other  purposes, such as commercial applications, and engineering or design studies is not  recommended without consultation with a qualified expert. Community feedback to improve and  validate the dataset for modeling usage is appreciated. Email comments to  bridget@climateanalyticsgroup.org.  Dataset File Name: NASA Earth Exchange (NEX) Downscaled Climate Projections (NEXDCP30),  https://portal.nccs.nasa.gov/portal_home/published/NEX.html	not-provided
 NEX-GDDP.v1	NASA Earth Exchange Global Daily Downscaled Projections	NCCS	1950-01-01	2100-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1374483929-NCCS.json	The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds.    Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). 	not-provided
@@ -321,7 +274,6 @@ PSScene3Band.v1	PlanetScope Satellite Imagery 3 Band Scene	CSDA	2014-06-01		-180
 QB02_MSI_L1B.v1	QuickBird Level 1B Multispectral 4-Band Satellite Imagery	CSDA	2001-10-18	2015-01-27	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2497489665-CSDA.json	The QuickBird Level 1B Multispectral 4-Band Imagery collection contains satellite imagery acquired from Maxar Technologies by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the DigitalGlobe QuickBird-2 satellite using the Ball High Resolution Camera 60 across the global land surface from October 2001 to January 2015. This satellite imagery is in the visible and near-infrared waveband range with data in the blue, green, red, and near-infrared wavelengths. The spatial resolution is 2.16m at nadir and the temporal resolution is 2.5 to 5.6 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.	not-provided
 QB02_Pan_L1B.v1	QuickBird Level 1B Panchromatic Satellite Imagery	CSDA	2001-10-18	2015-01-27	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2497480059-CSDA.json	The QuickBird Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the DigitalGlobe QuickBird-2 satellite using the Ball High Resolution Camera 60 across the global land surface from October 2001 to January 2015. This data product includes panchromatic imagery with a spatial resolution of 0.55m at nadir and a temporal resolution of 2.5 to 5.6 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.	not-provided
 SEAGLIDER_GUAM_2019.vV1	Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020)	POCLOUD	2019-10-03	2020-01-15	143.63035, 13.39476, 144.613, 14.71229	https://cmr.earthdata.nasa.gov/search/concepts/C2151536874-POCLOUD.json	This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14°N 144°E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington.	not-provided
-SRDB_V5_1827.v5	A Global Database of Soil Respiration Data, Version 5.0	ORNL_CLOUD	1961-01-01	2017-12-31	-163.71, -78.02, 175.9, 81.8	https://cmr.earthdata.nasa.gov/search/concepts/C2216864433-ORNL_CLOUD.json	The Soil Respiration Database (SRDB) is a near-universal compendium of published soil respiration (Rs) data. The database encompasses published studies that report at least one of the following data measured in the field (not laboratory): annual soil respiration, mean seasonal soil respiration, a seasonal or annual partitioning of soil respiration into its source fluxes, soil respiration temperature response (Q10), or soil respiration at 10 degrees C. The SRDB's orientation is to seasonal and annual fluxes, not shorter-term or chamber-specific measurements, and the database is dominated by temperate, well-drained forest measurement locations. Version 5 (V5) is the compilation of 2,266 published studies with measurements taken between 1961-2017. V5 features more soil respiration data published in Russian and Chinese scientific literature for better global spatio-temporal coverage and improved global climate-space representation. The database is also restructured to have better interoperability with other datasets related to carbon-cycle science.	not-provided
 SeaWiFS_L2_GAC_OC.vR2022.0	OrbView-2 SeaWiFS Regional Global Area Coverage (GAC) Ocean Color (OC) Data, version R2022.0	OB_CLOUD	1997-09-04	2010-12-11	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2789774382-OB_CLOUD.json	The SeaWiFS instrument was launched by Orbital Sciences Corporation on the OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from September 1997 until the end of mission in December 2010. SeaWiFS had 8 spectral bands from 412 to 865 nm. It collected global data at 4 km resolution, and local data (limited onboard storage and direct broadcast) at 1 km. The mission and sensor were optimized for ocean color measurements, with a local noon (descending) equator crossing time orbit, fore-and-aft tilt capability, full dynamic range, and low polarization sensitivity.	not-provided
 Survey_1988_89_Mawson_npcms.v1	1988/89 Summer season, surveying and mapping program, Mawson - North Prince Charles Mountains - Davis	AU_AADC	1988-10-01	1989-02-28	62, -70, 79, -66	https://cmr.earthdata.nasa.gov/search/concepts/C1214313847-AU_AADC.json	Field season report of these programs: 1988/89 Summer Season surveying and mapping North Prince Charles Mountains; ...mapping program Northern PCM's - Mawson Doppler Translocation Support; ....mapping program Voyage 6 stopover Davis. Includes maps and mapsheet layouts.  See the report for full details on the program.  Contents are: Introduction Preparation Voytage to Antarctica 1988/89 Summer Season Surveying and Mapping Program, Northern Prince Charles Mountains 1988/89 Summer Season Surveying and Mapping Program, Voyage 6 Stopover, Davis Performance of Equipment Station Marking Field Camping Climatic Conditions Conclusion Appendices 	not-provided
 Turbid9.v0	2004 Measurements made in the Chesapeake Bay	OB_DAAC	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.json	Measurements made in the Chesapeake Bay in 2004.	not-provided