RESUMEN
The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the processing of large C-B and radar images can be used to highlight temporal and spatial deformation anomalies, and their detailed analysis and postprocessing to generate operative products for final users. In this work, the wide-area mapping capability of Sentinel-1 was used in synergy with the COSMO-SkyMed high resolution SAR data to characterize ground subsidence affecting the urban fabric of the city of Pistoia (Tuscany Region, central Italy). Line of sight velocities were decomposed on vertical and E-W components, observing slight horizontal movements towards the center of the subsidence area. Vertical displacements and damage field surveys allowed for the calculation of the probability of damage depending on the displacement velocity by means of fragility curves. Finally, these data were translated to damage probability and potential loss maps. These products are useful for urban planning and geohazard management, focusing on the identification of the most hazardous areas on which to concentrate efforts and resources.
RESUMEN
Depletion of groundwater aquifers along with all of the associated quality and quantity problems which affect profitability of direct agricultural and urban users and linked groundwater-ecosystems have been recognized globally. During recent years, attention has been devoted to land subsidence-the loss of land elevation that occurs in areas with certain geological characteristics associated with aquifer exploitation. Despite the large socioeconomic impacts of land subsidence most of these effects are still not well analyzed and not properly recognized and quantified globally. In this paper we developed a land subsidence impact extent (LSIE) index that is based on 10 land subsidence attributes, and applied it to 113 sites located around the world with reported land subsidence effects. We used statistical means to map physical, human, and policy variables to the regions affected by land subsidence and quantified their impact on the index. Our main findings suggest that LSIE increases between 0.1 and 6.5% by changes in natural processes, regulatory policy interventions, and groundwater usage, while holding all other variables unchanged. Effectiveness of regulatory policy interventions varies depending on the lithology of the aquifer system, in particular its stiffness. Our findings suggest also that developing countries are more prone to land subsidence due to lower performance of their existing water governance and institutions.