Abstract
We present the continuous monitoring of ground deformation at regional scale using ESA (European Space Agency) Sentinel-1constellation of satellites. We discuss this operational monitoring service through the case study of the Tuscany Region (Central Italy), selected due to its peculiar geological setting prone to ground instability phenomena. We set up a systematic processing chain of Sentinel-1 acquisitions to create continuously updated ground deformation data to mark the transition from static satellite analysis, based on the analysis of archive images, to dynamic monitoring of ground displacement. Displacement time series, systematically updated with the most recent available Sentinel-1 acquisition, are analysed to identify anomalous points (i.e., points where a change in the dynamic of motion is occurring). The presence of a cluster of persistent anomalies affecting elements at risk determines a significant level of risk, with the necessity of further analysis. Here, we show that the Sentinel-1 constellation can be used for continuous and systematic tracking of ground deformation phenomena at the regional scale. Our results demonstrate how satellite data, acquired with short revisiting times and promptly processed, can contribute to the detection of changes in ground deformation patterns and can act as a key information layer for risk mitigation.
Highlights
Over the past two decades, studies showing the applicability of images gathered by satellite-based Synthetic Aperture Radar (SAR) sensors for the detection and mapping of geo-hazard-induced deformation have gained increasing attention
We provide a clear example of the potential of multi-temporal interferometric SAR (InSAR) analyses applied to multi-temporal Sentinel-1 data for continuous monitoring of ground deformation induced by hydrogeological processes
SqueeSAR analysis is designed to identify a sparse grid of measurement points (MP) for which it is possible to estimate, with millimetric accuracy[17,18,19] the mean yearly velocity and displacement time series (TS) along the satellite line of sight (LOS)
Summary
Over the past two decades, studies showing the applicability of images gathered by satellite-based Synthetic Aperture Radar (SAR) sensors for the detection and mapping of geo-hazard-induced deformation have gained increasing attention This is mainly related to (i) advances in the performance of satellite systems, providing an ever increasing temporal and spatial resolution of satellite data covering large areas; (ii) development of more sophisticated processing chains for SAR images, capable of reducing the impact of noise and atmospheric disturbances on radar data; and (iii) increases in computational capabilities (via parallel processing and cloud computing), allowing users to greatly reduce processing times. Up to now, the potential of this constellation has not been fully exploited
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