Vulnerability Assessment of Buildings due to Land Subsidence using InSAR Data in the Ancient Historical City of Pistoia (Italy)

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Title: Vulnerability Assessment of Buildings due to Land Subsidence using InSAR Data in the Ancient Historical City of Pistoia (Italy)
Authors: Ezquerro Martín, Pablo | Del Soldato, Matteo | Solari, Lorenzo | Tomás, Roberto | Raspini, Federico | Ceccatelli, Mattia | Fernández-Merodo, José Antonio | Casagli, Nicola | Herrera García, Gerardo
Research Group/s: Ingeniería del Terreno y sus Estructuras (InTerEs)
Center, Department or Service: Universidad de Alicante. Departamento de Ingeniería Civil
Keywords: Sentinel-1 | COSMO-SkyMed | Pistoia | Land subsidence | Vulnerability | Fragility curves
Knowledge Area: Ingeniería del Terreno
Issue Date: 12-May-2020
Publisher: MDPI
Citation: Ezquerro P, Del Soldato M, Solari L, Tomás R, Raspini F, Ceccatelli M, Fernández-Merodo JA, Casagli N, Herrera G. Vulnerability Assessment of Buildings due to Land Subsidence using InSAR Data in the Ancient Historical City of Pistoia (Italy). Sensors. 2020; 20(10):2749. doi:10.3390/s20102749
Abstract: 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.
Sponsor: This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI) and European Funds for Regional Development (FEDER) under projects AQUARISK (ESP2013-47780-C2-2-R) and TEMUSA (TEC2017-85244-C2-1-P) and STAR-EO (TIN2014-55413-C2-2-P). The first author shows gratitude for the PhD student contract BES-2014-069076. The work was conceived during the research stay of P. Ezquerro and R. Tomás in the Università degli Studi di Firenze and the research stay of G. Herrera in the IGOT Lisbon University, supported by the Spanish Ministry of Education, Culture and Sport under fellowships EEBB-I-18-13014, PRX17/00439 and PRX19/00065, respectively. The S-1 monitoring activity is funded and supported by the Tuscany Region under the agreement “Monitoring ground deformation in the Tuscany Region with satellite radar data.” The authors also gratefully acknowledge TRE ALTAMIRA for having processed the S-1 data. The project was carried out using CSK® Products, © ASI (Italian Space Agency), delivered under the ASI Project Id Science 678 - “High resolution Subsidence investigation in the urban area of Pistoia (Tuscany Region, central Italy). The work is under the framework of the e-shape project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 820852. This paper is also supported by the PRIMA programme under grant agreement No 1924, project RESERVOIR. The PRIMA programme is supported by the European Union.
ISSN: 1424-8220
DOI: 10.3390/s20102749
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Peer Review: si
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Appears in Collections:INV - INTERES - Artículos de Revistas
Research funded by the EU

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