{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T18:43:23Z","timestamp":1776105803142,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Research Council-Institute of Atmospheric Sciences and Climate (CNR-ISAC) in Rome, Italy","award":["CUP B53D23033400001"],"award-info":[{"award-number":["CUP B53D23033400001"]}]},{"name":"the University of Pavia\u2019s Modulo ASI Scholarships Programme 2024","award":["CUP B53D23033400001"],"award-info":[{"award-number":["CUP B53D23033400001"]}]},{"name":"the European Union\u2013Next Generation EU, Mission 4-Component 2 (M4C2), PRIN 2022 PNRR project SubRISK+ 2023\u22122025","award":["CUP B53D23033400001"],"award-info":[{"award-number":["CUP B53D23033400001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Advanced statistics can enable the detailed characterization of ground deformation time series, which is a fundamental step for thoroughly understanding the phenomena of land subsidence and their main drivers. This study presents a novel methodological approach based on pre-existing open-access statistical tools to exploit satellite differential interferometric synthetic aperture radar (DInSAR) data to investigate land subsidence processes, using European Ground Motion Service (EGMS) Sentinel-1 DInSAR 2018\u22122022 datasets. The workflow involves the implementation of Persistent Scatterers (PS) time series classification through the PS-Time tool, deformation signal decomposition via independent component analysis (ICA), and drivers\u2019 investigation through spatio-temporal correlation with geospatial and monitoring data. Subsidence time series at the three demonstration sites of Bologna, Ravenna and Carpi (Po Plain, Italy) were classified into linear and nonlinear (quadratic, discontinuous, uncorrelated) categories, and the mixed deformation signal of each PS was decomposed into independent components, allowing the identification of new spatial clusters with linear, accelerating\/decelerating, and seasonal trends. The relationship between the different independent components and DInSAR-derived displacement velocity, acceleration, and seasonality was also analyzed via regression analysis. Correlation with geological and groundwater monitoring data supported the investigation of the relationship between the observed deformation and subsidence drivers, such as aquifer resource exploitation, local geological setting, and gas extraction\/reinjection.<\/jats:p>","DOI":"10.3390\/rs16214066","type":"journal-article","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T09:57:36Z","timestamp":1730368656000},"page":"4066","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Statistical and Independent Component Analysis of Sentinel-1 InSAR Time Series to Assess Land Subsidence Trends"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-1574-732X","authenticated-orcid":false,"given":"Celina","family":"Far\u00edas","sequence":"first","affiliation":[{"name":"Institute of Atmospheric Sciences and Climate (ISAC), National Research Council (CNR), Via del Fosso del Cavaliere 100, 00133 Rome, Italy"},{"name":"Facultad de Ciencias Exactas F\u00edsicas y Naturales (FCEFyN), Universidad Nacional de C\u00f3rdoba (UNC), Av. V\u00e9lez Sarsfield 299, C\u00f3rdoba X5000JJC, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9424-9774","authenticated-orcid":false,"given":"Michelle","family":"Lenard\u00f3n S\u00e1nchez","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Sciences and Climate (ISAC), National Research Council (CNR), Via del Fosso del Cavaliere 100, 00133 Rome, Italy"},{"name":"Facultad de Ciencias Exactas F\u00edsicas y Naturales (FCEFyN), Universidad Nacional de C\u00f3rdoba (UNC), Av. V\u00e9lez Sarsfield 299, C\u00f3rdoba X5000JJC, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3477-1044","authenticated-orcid":false,"given":"Roberta","family":"Bon\u00ec","sequence":"additional","affiliation":[{"name":"Department of Science, Technology and Society (STS), University School for Advanced Studies (IUSS), 27100 Pavia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8134-1576","authenticated-orcid":false,"given":"Francesca","family":"Cigna","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Sciences and Climate (ISAC), National Research Council (CNR), Via del Fosso del Cavaliere 100, 00133 Rome, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6180","DOI":"10.1038\/s41467-023-41933-z","article-title":"Global Land Subsidence Mapping Reveals Widespread Loss of Aquifer Storage Capacity","volume":"14","author":"Hasan","year":"2023","journal-title":"Nat. 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