GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
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Updated
Nov 9, 2024 - C++
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
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Satellite imagery for dummies.
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A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
High-level geospatial data visualization library for Python.
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Transform, query, and download geospatial data on the web.
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A list of open geospatial datasets available on AWS, Earth Engine, Planetary Computer, NASA CMR, and STAC Index
A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.
Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray
Tutorial on geospatial data manipulation with Python
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Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
THREDDS Data Server v4.6
OSM in memory
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