kcieslik/eq-insar: EQ-INSAR v0.1.0
Abstract
First public release of EQ-INSAR, a lightweight, physics-based forward model for generating synthetic InSAR surface deformation data from earthquake sources. Features Davis (1986) point source model for fast surface displacement computation 9 SAR satellites — Sentinel-1, ALOS-2, TerraSAR-X, COSMO-SkyMed, RADARSAT-2, NISAR, SAOCOM, ENVISAT, ICEYE InSAR-native outputs — LOS displacement, wrapped/unwrapped interferometric phase ML training ready — time series generation with pre/co/post-event frames, binary segmentation labels, batch generation Noise models — Gaussian noise and orbital ramps Export formats — GeoTIFF (rasterio) and NetCDF (netCDF4) Minimal dependencies — core computation requires only NumPy Installation pip install eq-insar Links - Documentation: https://kcieslik.github.io/eq-insar/ - PyPI: https://pypi.org/project/eq-insar/
Fields of Study & Subjects
Synthetic Aperture Radar (SAR) Applications and Techniques
Image and Signal Denoising Methods
Computational Physics and Python Applications
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 February 2026
- Language
- EN