A python package that evaluates the spatial variability of a site utilizing HVSR.
Francisco Javier G. Ornelas1
1 University of California, Los Angeles (UCLA)
hvspatialpy is a Python package designed to assess the spatial variability of sites using the Horizontal-to-Vertical Spectral Ratio (HVSR) method. This package enables users to analyze multiple HVSR curves collected from various locations around a site and compare them against a reference curve, including assessments for different distances from the reference point. The package processes HVSR data by organizing the curves into specified frequency intervals and comparing HVSR measurements across varying distances. This structured approach allows for a detailed evaluation of variability, particularly concerning resonant peaks. By systematically analyzing the spatial distribution of these resonant features, users can gain insights into the subsurface characteristics of the site and identify areas of significant variability. This package was developed by Francisco Javier G. Ornelas under the supervision of Dr. Jonathan P. Stewart and Dr. Scott J. Brandenberg at the University of California, Los Angeles (UCLA).
HVSR is derived from ratios of the horizontal and vertical components of a Fourier Amplitude Spectrum (FAS) from a 3-component recording of microtremors or earthquakes. This is done by recording ground vibrations either from temporarily-deployed or permanently-installed seismometers, for a relatively short period of time (~1-2 hrs) or a longer period of time.
This method or technique was first proposed by Nogoshi and Igarashi (1971) [ABSTRACT] and later popularized by Nakamura (1989) [ABSTRACT]. The method works by assuming that the horizontal wavefield is amplified as seismic waves propagate through the soil deposits compared to the vertical wavefield.
HVSR can be useful in site characterization since it can identify resonant frequencies at sites, through peaks in an HVSR spectrum. Studies have also found that the lowest peak in HVSR spectra can be associated with the fundamental frequency of a site (e.g., [ABSTRACT]). The identification of these peaks is significant because they correlate with impedance contrasts at a given site. When multiple HVSR surveys are conducted at the same location, it becomes possible to illustrate the spatial variability of impedance contrasts across the site. Consequently, HVSR is a valuable tool for assessing and understanding the spatial heterogeneity of site characteristics
hvspatialpy is available using pip and can be installed with:
- Jupyter Notebook
pip install hvspatialpy - PyPI
py -m pip install hvspatialpy
hvspatialpy is a python package that evaluates spatial variability at a site utilizing HVSR.
The library contains various features, such as:
- A graphical user interface (GUI) to use in inputting parameters.
- The ability to vary the frequency interval of interest, to narrow down which peaks one wants to evaluate.
- A plot showing the approximate location of the site with all the tests done. These tests are color coded based on the correlation type used (e.g., LCSS).
Examples of these can be found under the examples folder in the Github repository [GIT]
If you use hvspatialpy (directly or as a dependency of another package) for work resulting in an academic publication or other instances, we would appreciate if you cite the following:
Ornelas, F. J. G. (2024). hvspatialpy (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.13770432.
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This project has been licensed under 