|Paper title||Rapid identification of surface deformation processes in El Salvador using satellite Interferometric Synthetic-Aperture Radar|
|Form of presentation||Poster|
The country of El Salvador lies on a tectonically active subduction margin with high deformation rates. However, other deformation phenomena dominate the signal detectable by geodetic techniques in certain areas. Identifying active deformation processes such as landslides, which have caused many casualties in the past, results crucial for the safety of people living in these areas. To this date, no study has been performed trying to broadly recognise non-tectonic deforming areas within the whole country using geodetic data.
Here we use satellite interferometric synthetic-aperture radar (InSAR) data to identify ongoing ground deformation across El Salvador. ESA’s Sentinel-1 SAR images have been processed using the web based Geohazard Exploitation Platform (GEP), specifically through the PSBAS (Parallel Small BAseline Subset) processing chain. In total, seven years of data have been processed for each geometry (ascending and descending), including the whole period of Sentinel-1 up to November 2021. The results are then analysed using the ADAtools in order to automatically identify active deformation areas (ADAs) and classify them according to the natural or anthropic causative phenomenon, analysing the behaviour of the deformation signal together with geological and other ancillary information of the study area (Digital Elevation Models, inventories of different geohazards, cadastral inventories, etc). This is followed by a manual supervision. Thus, we identify several ADAs affected by different proposed deformation phenomena, such as landslides, consolidation settlements, land subsidence or subsidence related to geothermal exploitation. We also detect ground deformation potentially related to volcanic activity on the Izalco and San Miguel volcanoes.
We further validate the InSAR time series by comparing them with 8 permanent GNSS stations across El Salvador.
Acknowledging previously unknown processes will help future studies to focus on these areas. This information can be useful for identifying stable areas across the country, allowing to better interpret other data such as GNSS time series. Moreover, eventual monitoring of these phenomena can be of great importance for decision-makers in urban planning and risk prevention policies.
This work has been developed in the framework of project PID2020-116540RB-C22 funded by MCIN/ AEI/10.13039/501100011033 and project CGL2017-83931-C3-3-P funded by MCIN/ AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, as well us under the Grant FPU19/03929 funded by MCIN/AEI/10.13039/501100011033 and by “FSE invests in your future”.