EGU23-6436
https://doi.org/10.5194/egusphere-egu23-6436
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Open-source Performance of DInSAR Technique for the Detection of Ground Deformation induced by Large Earthquakes using Sentinel-1 and SNAP operators in Python

Martina Occhipinti1, Shaila Amorini2, Claudio De Luca3, and Massimiliano Porreca1
Martina Occhipinti et al.
  • 1University of Perugia, Department of Physics and Geology, Perugia, Italy (martina.occhipinti@studenti.unipg.it)
  • 2EagleProjects S.p.A., Perugia, Italy
  • 3CNR-IREA, Naples, Italy

 

Satellite Differential Synthetic Aperture Radar Interferometry (DInSAR) is a well-known technique that allows investigation surface displacements affecting large areas (km-scale) on the Earth, in both natural and anthropogenic hazard scenarios, with rather limited costs and a centimeter accuracy. In particular, in the last two decades, the effectiveness of the satellite DInSAR technology for ground deformation analysis induced by seismic events, and its crucial role in the emergency, have been largely demonstrated. In this context, we present a complete open-source tool of DInSAR technique, starting from the dataset download up to the data processing and interpretation of the deformation field. SAR imageries from Sentinel-1 satellite of the Copernicus are collected. Data processing is executed thanks to SNAP software from ESA (https://earth.esa.int/eogateway/tools/snap), and using snappy module in Python that allows interacting with the Java API of SNAP to avoid eventual bugs and to automatize the process. The workflow will include not only the work chain to obtain the displacement map along the satellite Line of Sight (LOS), but also several modules that the operator can exploit to retrieve the vertical and horizontal (east-west) displacement field when, obviously, on the same seismic event, at least two independent acquisitions geometries (at least one ascending and one descending orbit), are available. The workflow is applied to three case studies characterized by compressional and strike-slip tectonics: Bandar-Abbas seismic sequence, Iran (November 2021); Petrinya earthquake, Croatia (December 2020) and Menuyan earthquake, China (January 2022). The final scope of this research is to provide a single, automatic and repeatable product to create a two-dimensional deformation map with only open-source tools. This method is helpful not only for its simplicity as it can be adopted also by beginning users in the very first stage of approaching DInSAR technique, but also for the extension of studies related to seismic areas as a combination with the on-field observation in order to mitigate their seismic risk.

How to cite: Occhipinti, M., Amorini, S., De Luca, C., and Porreca, M.: Open-source Performance of DInSAR Technique for the Detection of Ground Deformation induced by Large Earthquakes using Sentinel-1 and SNAP operators in Python, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6436, https://doi.org/10.5194/egusphere-egu23-6436, 2023.