Large Scale Interferometric Processing of Sentinel-1 Data over the Atacama Desert - a Contribution to the TecVolSA Project

• Main Authors: De Zan, Francesco, Ansari, Homa, Parizzi, Alessandro, Shau, Robert, Eineder, Michael, Montazeri, Sina, Navarro Sanchez, Victor Diego, Walter, Thomas
• Format: Conference Object
• Language: English
• Published: 2021
• Subjects: SAR-Signalverarbeitung; permafrost
• Online Access: https://elib.dlr.de/143000/; https://elib.dlr.de/143000/1/Fringe_2021_TecVolSA.pdf

The project TecVolSA (Tectonics and Volcanoes in South America) aims at developing an intelligent Earth Observation (EO) data processing system for monitoring the earthquake cycle and volcanic events in South America. The Remote Sensing Technology Institute of DLR participates to this project together with GFZ (German Research Centre for Geosciences). The project is partially financed by Helmholtz. So far we have processed about 40 Sentinel-1 slices covering the Atacama Desert with mixed Permanent Scatterer and Distributed Scatterer (PS/DS) techniques. The area is very dry and the spatio-temporal coverage is excellent. Tropospheric correction have been applied using ECMWF ERA5 data, hence improving the performance in observing both topography related and large scale deformation signals. The current results reveal, as expected, plenty of interesting signals to be interpreted (see attached figure for an overview of the velocity field). Preliminary GPS cross-validation, thanks to data freely available from the Geodetic Nevada Laboratory, confirm that the InSAR relative error in the estimated velocities is in the order of 1 mm/yr at large scale (>100 km) and confirms the large scale signal related to the subduction of the Nazca plate (see attached figure). More GNSS validation will be possible with additional GPS stations. The challenge of the project is the separation of different contributions to the InSAR measurements: apart from the tectonic effects, there are contributions coming from volcanic unrest, atmospheric delays, moisture effects, snow, flank instability (likely downhill creep or solifluction related to permafrost, see attached figure), salt lake growth, mining, and likely more. We are dealing with this complexity with a diversity of tools: physical modeling and statistical analysis, deep neural networks, and expert knowledge. GFZ contributes process knowledge, historic seismic data, in-situ motion measurements and observations and 4D geophysical modelling codes for producing a diverse database for ...