Abstract
Abstract. Subsidence can now be routinely mapped on a national scale thanks to ESA's Sentinel-1 sensors and advanced scalable SqueeSAR® processing. In order to be integrated into existing monitoring programmes, the SqueeSAR® datasets can be calibrated with GNSS measurements. The dense spatial coverage of SqueeSAR® deformation maps captures local deformation phenomena, and with appropriate calibration, can advance the understanding of regional deformation trends. The regular and reliable SAR image acquisitions by Sentinel-1, as well as significant improvements in the scalability of SqueeSAR® processing allow regular updates of deformation maps on a national scale. Filtering the large amount of data for relevant information is achieved by using an algorithm to detect changes in displacement trends.
Highlights
The Sentinel-1 satellites of the European Space Agency (ESA) are acquiring SAR images since late 2014, and are the first sensors designed for surface deformation monitoring over large areas
The following examples are taken from the national SqueeSAR® map for California (US), which was calibrated with GNSS data, from the national SqueeSAR® map for Japan, which was not calibrated with GNSS data and from the SqueeSAR® monitoring service provided to the region of Tuscany (Italy), which is updated every two weeks
The nationwide ground deformation map created with SqueeSAR®, based on Sentinel-1 SAR images, reveals these heterogenous patterns
Summary
The Sentinel-1 satellites of the European Space Agency (ESA) are acquiring SAR images since late 2014, and are the first (civilian) sensors designed for surface deformation monitoring over large areas. The Sentinel-1 image stacks have been used to produce the deformation maps presented here, which have been processed using TRE ALTAMIRA’s advanced InSAR processing algorithm called SqueeSAR®. Significant improvements in computing power and adapting the SqueeSAR® processing to cloud computing allow regular updates of nationwide InSAR deformation maps. The calibration methodology presented here provides a way to integrate InSAR deformation maps with GNSS measurements. The results show examples from some of the yearly updated national deformation maps currently provided for Denmark, Japan, France and California (US) Examples from Tuscany are presented, where as part of a continuous monitoring programme, regional deformation maps are updated every two weeks. To retrieve relevant information from this large amount of data, the maps are filtered with a trend change detection algorithm to highlight areas of significant deformation (Del Soldato et al, 2019)
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