Exploitation of satellite A-DInSAR time series for detection, characterization and modelling of land subsidence

Bonì, Roberta; Meisina, Claudia; Cigna, Francesca; Herrera, Gerardo; Notti, Davide; Bricker, Stephanie; McCormack, Harry; Tomás, Roberto; Béjar-Pizarro, Marta; Mulas, Joaquín; Ezquerro, Pablo. 2017 Exploitation of satellite A-DInSAR time series for detection, characterization and modelling of land subsidence. Geosciences, 7 (2). 25.

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In the last two decades, advanced differential interferometric synthetic aperture radar (A-DInSAR) techniques have experienced significant developments, which are mainly related to (i) the progress of satellite SAR data acquired by new missions, such as COSMO-SkyMed and ESA’s Sentinel-1 constellations; and (ii) the development of novel processing algorithms. The improvements in A-DInSAR ground deformation time series need appropriate methodologies to analyse extremely large datasets which consist of huge amounts of measuring points and associated deformation histories with high temporal resolution. This work demonstrates A-DInSAR time series exploitation as valuable tool to support different problems in engineering geology such as detection, characterization and modelling of land subsidence mechanisms. The capabilities and suitability of A-DInSAR time series from an end-user point of view are presented and discussed through the analysis carried out for three test sites in Europe: the Oltrepo Pavese (Po Plain in Italy), the Alto Guadalentín (Spain) and the London Basin (United Kingdom). Principal component analysis has been performed for the datasets available for the three case histories, in order to extract the great potential contained in the A-DInSAR time series

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 2076-3263
Date made live: 20 Dec 2017 11:50 +0 (UTC)

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