# FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service
Since 2014, the radar satellite constellation of the European Copernicus Sentinel-1 mission (S-1) provides massive amounts of SAR data available free of charge (4 Peta-bytes/year today). Continental regions are systematically covered by acquisitions in the interferometric widespread (IW) mode, with continuous 250 km-wide tracks. With the launch of Sentinel 1-B in April 2016, the revisit time in Europe has dropped to 6 days. Therefore, at the beginning of 2021, after 5 years of mission, about 300 images per viewing geometry are available. In tectonically active regions outside Europe, the sampling frequency is about 12 to 24 days. The retrieval of ground deformation at continental scale, with unprecedented temporal sampling, is now providing new observables leading to major scientific discoveries and enabling operational applications in the fields of environment, risk and asset management. However, taking advantage of this extraordinary dataset requires the development of fully automated processing chains, as well as large computational and storage facilities coupled with the ability of software to scale up while processing thousands of SAR scenes, all of which require significant human resources. The S-1 imaging is done by the terrain observation with progressive scans (TOPSAR) technique [24] which is based on antenna forward-backward sweeping inside each burst, and on the switching the radar footprint between three overlapping sub-swaths. Its specificity strongly increases the complexity of the processing workflow, the number and size of intermediate files written on disk requiring intensive input/output (I/O) operations, and the usage of \"scratch\" disk space. A number of InSAR processing chains now handle S-1 SAR data, and are freely available (e.g., sentinel application platform (SNAP) [25], InSAR scientific computing environment (ISCE) [26], generic mapping tools (GMT) for SAR (GMTSAR) [27]), or delivered by commercial agreement (e.g., Gamma, [28]). Implemented strategies for MTInSAR processing of large stacks of S-1 data differ from one group to another. Some rely on permanent scatterers (PS, [5]) or distributed scatterers (DS) techniques, i.e., the phase delay information is extracted from reliable points or from sets of neighboring points, sharing common statistical properties (e.g., SqueeSAR, [7]), for each secondary acquisition with respect to a single reference acquisition. Unwrapped phase time series are then obtained on a mesh made of PS or DS points, that can be associated with a defined, single feature on ground. Another class of processing strategy is the small baseline subset (SBAS) approach depicted in [4], in which redundant differential interferograms between images separated by a small baseline are constructed, multi-looked, and spatially filtered. Unwrapped phase time series are then continuous in space, with an improved signal to noise ratio in non-urban areas, but a mixing of ground targets by the multi-looking and filtering steps. Whether based on PS, PS-DS, or relying on SBAS approach, on-demand services or remote massive data processing have been implemented on high performance computers or on cloud computing environments. For example, an on-demand MTInSAR service has been installed on the ESA geohazards exploitation platform (GEP) based on the Parallel-SBAS algorithm [29; 30]. PS or PS-DS algorithms have also been employed for ground motion mapping at country-scale, based for example on SqueeSAR [31; 32] or on PSI techniques [33; 34; 35]. In a fairly limited number of cases, national geological survey agencies have made the PS or PSDS ground velocity maps and displacement time series available for the public and free of charge through a web portal (e.g., [[https://bodenbewegungsdienst.bgr.de/](https://bodenbewegungsdienst.bgr.de/)]([https://bodenbewegungsdienst.bgr.de/](https://bodenbewegungsdienst.bgr.de/)), for Germany, [[https://insar.ngu.no/](https://insar.ngu.no/)]([https://insar.ngu.no/](https://insar.ngu.no/)) for Norway, accessed on 10 September 2021).