Unsupervised generation of co-seismic DInSAR maps by exploiting Sentinel-1 Data

Earth's surface deformation that occur as a consequence of an earthquake is a crucial information for investigating the causative source of the seismic event. In this context, the space-borne Differential Synthetic Aperture Radar Interferometry (DInSAR) has proven to be one of the key methods for the quantitative measurement of the Earth's surface deformation, with centimetres to millimetres accuracy [1]. DInSAR relies on the evaluation of the phase difference between two SAR images, acquired from different orbital positions and at different times [1]. Depending on the system configuration, the footprint of space-borne SAR acquisitions can span from a few kilometres up to hundreds of kilometres, making it particularly suitable for accurate investigations of wide areas at relative low cost. In these sense, according to USGS records [2], from 1992 to 2016, about 3700 earthquakes with significant magnitudes (Mw > 6.0) have occurred, while only a limited number of them has been successfully investigated through DInSAR [3]. This is mainly due, apart the intrinsic limitation of the DInSAR technique, to the lack of a satellite program with a systematic and global acquisition policy, which are fundamental characteristics to allow creating DInSAR operational services at global scale. However, since the launch of the Copernicus Sentinel-1 SAR satellite missions in 2014 and 2016, the availability of SAR images dramatically increased. Indeed, this constellation acquires, with global coverage policy, radar images every 6/12 days over the same area, allowing us to dispose of a huge archive of SAR data that can be processed for obtaining co-seismic displacement maps in a short time frame and anywhere in the world. Considering the relevance of the satellite interferometric analysis for the hazards monitoring, as well as the availability of new radar systems as Sentinel-1, which are characterized by a high reliability level, is it therefore possible the development of operational services for the generation of DInSAR products, some of them being already in place [4, 5]. In this work an unsupervised and automatic tool for the generation of DInSAR co-seismic displacement maps is presented. Benefiting from the mostly global availability of Sentinel-1 SAR data and the on-line earthquake catalogues, the tool retrieves information about the depth and magnitude of recent earthquakes and triggers, if necessary, the interferometric process over the area affected by the seismic event. The workflow process is the following (Figure 1). First, the extraction of earthquake information (epicenter location, magnitude, time, ...) from the on-line public available web catalogues, as those provided by main international geophysical institutions (e.g. USGS [2], INGV [6]), is performed (Block A of Figure 1). The retrieved information is provided according to different standard formats (QuakeML, geoJSON, ...) and is accessible via subscription feeds that are updated with a defined frequency. The system is not limited to a single earthquake catalog interface. The relevant earthquake information is collected in accordance to an empirical magnitude and depth relation, which considers that only high magnitude (> Mw 6.0) and relatively shallow earthquakes (typically < 20 km) very likely induce a surface deformation that is detectable via DInSAR [7] (Block B). Among the earthquakes that respect the relation, only those with the epicentre on land (or even on water but that can likely induce detectable deformation on land) are processed. Once the occurred earthquake has been selected, the SAR data retrieval is performed via an automatic query to the open access Sentinel-1 catalogue (Block C). The query is performed over an area whose extension depends of the relation betwee