This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
EQ-INSAR: A Python Package for Generating Synthetic Earthquake InSAR Deformation Data
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Abstract
EQ-INSAR is an open-source Python package for generating synthetic Interferometric Synthetic Aperture Radar (InSAR) surface deformation data from earthquake sources. The package implements the Davis (1986) point source model to compute three component ground displacement from double-couple earthquake mechanisms. Then it projects the displacement onto satellite line-of-sight (LOS) geometries to produce interferometric phase maps and binary segmentation labels suitable for machine learning. EQ-INSAR supports 9 pre configured SAR satellite geometries and includes C-band, L-band, and X-band, and provides batch generation of randomized training datasets. Real data validation against the 2021 Yangbi Mw 6.1 earthquake demonstrates sub centimeter RMS fit to observed Sentinel-1 InSAR data and independent recovery of the deformation centroid to within 6km of the Global CMT solution. The software is designed for researchers developing Machine Learning based InSAR analysis tools, educators teaching InSAR interpretation, and scientists requiring synthetic benchmarks for natural and induced seismicity studies.
DOI
https://doi.org/10.31223/X5T19M
Subjects
Geophysics and Seismology, Remote Sensing
Keywords
Python, InSAR, earthquake, induced seismicity, synthetic aperture radar, deformation modeling, machine learning, remote sensing
Dates
Published: 2026-02-24 09:17
Last Updated: 2026-02-24 09:17
License
CC BY Attribution 4.0 International
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Conflict of interest statement:
The authors declare no conflict of interest
Data Availability (Reason not available):
Code and data are available at https://github.com/kcieslik/eq-insar and archived on Zenodo (DOI: 10.5281/zenodo.18647189)
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