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The availability of new constellations of synthetic aperture radar (SAR) sensors is leading to important advances in infrastructure monitoring. These constellations offer the advantage of reduced revisit times, providing low-latency data that enable analysis that can identify infrastructure instability and dynamic deformation processes. In this paper we use COSMO-SkyMed (CSK) and TerraSAR-X (TSX) data to monitor seasonal induced deformation at the Pertusillo dam (Basilicata, Italy) using multi-temporal SAR data analysis. We analyzed 198 images spanning 2010–2015 using a coherent and incoherent PS approach to merge COSMO-SkyMed adjacent tracks and TerraSAR-X acquisitions, respectively. We used hydrostatic-seasonal-temporal (HST) and hydrostatic-temperature-temporal (HTT) models to interpret the non-linear deformation at the dam wall using ground measurements together with SAR time-series analysis. Different look geometries allowed us to characterize the horizontal deformation field typically observed at dams. Within the limits of our models and the SAR acquisition sampling we found that most of the deformation at the Pertusillo dam can be explained by taking into account only thermal seasonal dilation and hydrostatic pressure. The different models show slightly different results when interpreting the aging term at the dam wall. The results highlight how short-revisit SAR satellites in combination with models widely used in the literature for interpreting pendulum and GPS data can be used for supporting structural health monitoring and provide valuable information to ground users directly involved in field measurements. [ABSTRACT FROM AUTHOR]

Rapid determination of the location and extent of earthquake ruptures is helpful for disaster response, as it allows prediction of the likely area of major damage from the earthquake and can help with rescue and recovery planning. With the increasing availability of near real-time data from the Global Positioning System (GPS) and other global navigation satellite system receivers in active tectonic regions, and with the shorter repeat times of many recent and newly launched satellites, geodetic data can be obtained quickly after earthquakes or other disasters. We have been building a data system that can ingest, catalog, and process geodetic data and combine it with seismic analysis to estimate the fault rupture locations and slip distributions for large earthquakes. [ABSTRACT FROM AUTHOR]