Analysis of Ground Deformation Detected Using the SBAS-DInSAR Technique in Umbria, Central Italy

Abstract

Ground deformation affecting the Umbria region (central Italy) in the 9-year period from 1992 to 2000 was investigated through multi-temporal Differential Synthetic Aperture Radar Interferometry (DInSAR). For the purpose, the Small BAseline Subset (SBAS) technique was adopted, which allows studying the temporal evolution of the detected deformation at two spatial scales: a low-resolution (regional) scale, and a full-resolution (local) scale. For the analysis, SAR data acquired by the European Remote Sensing (ERS-1/2) satellites along ascending and descending orbits were used. The detected deformation was analysed to investigate its relevance to geophysical, geomorphologic, and human-induced processes that may result in hazardous conditions to the population of Umbria. Low-resolution deformation data were used to: (i) determine the amount of displacement caused by the Umbria-Marche earthquake sequence from September 1997 to April 1998 in the Foligno area, (ii) determine the number and percentage of the known landslides that can be monitored by the DInSAR technology in the investigated area, and (iii) identify and measure subsidence induced by exploitation of a confined aquifer in the Valle Umbra. Results indicate that earthquakes moved through the Foligno area westwards up to 3.9 cm and with an uplift reaching 1.7 cm. Intersection in a GIS of the low-resolution deformation maps with a detailed landslide inventory map allowed the determination that the portion of landslides that can be monitored by the SBAS-DInSAR technique in Umbria ranges from 2.7% to 3.4%, and the percentage of the total landslide area ranges from 10.4% to 12.8%. In the Valle Umbra, a dependency was found between the time and the amount of detected ground deformation, and the record of water withdrawal. The full-resolution deformation data were used to investigate the movement of the Ivancich landslide, in the Assisi Municipality. Joint analysis of the spatial and the temporal characteristics of the ground displacement allowed the formulation of a hypothesis on the landslide geometry and deformation pattern. RI Guzzetti, Fausto/G-4404-201

Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys

“…Among the several DInSAR techniques, in this work we benefit from the full resolution Small BAseline Subset (SBAS) approach [17,28] that has the capability to retrieve a very large number of measure points by processing only interferograms less affected by noise (small baseline interferograms) [16]. The SBAS DInSAR approach has been successfully applied in analyzing deformation phenomena caused by natural and human-induced processes, resulting a useful tool for the assessment and mitigation of the hydrogeological and urban risk [18,[29][30][31][32][33]. Such a capability allows us to map the whole zone covered by the mass movement, by retrieving accurate and spatially dense information on the surface displacements affecting the investigated area.…”

“…The Ivancich landslide has been studied by using different SAR datasets to detect surface displacements and to carry out their long-term monitoring [18,26,30]. In this work, we benefit from the images acquired by the Cosmo-SkyMed (CSK) constellation.…”

Rule-based semi-automated approach for the detection of landslides induced by 18 September 2011 Sikkim, Himalaya, earthquake using IRS LISS3 satellite images

“…Identifying and detecting of landslides by RS technology are based on three main features of the sensors: spatial, spectral and temporal resolutions (Gao 1999). The advancement of satellite technology and development of sensors have resulted many cutting edge technologies, such as interferometry (Kimura & Yamaguchi 2000;Lauknes et al 2010;Cigna et al 2011;Jebur et al 2013b), differential interferometry (Guzzetti et al 2009), change detection (Nichol & Wong 2005;Mondini et al 2011;Al-shalabi et al 2013;Tehrany et al 2013b), image classification ), digital terrain model differencing (Dewitte & Demoulin 2005) and object-oriented analysis (Martha et al 2010a(Martha et al , 2010bStumpf & Kerle 2011), for landslide detection (Booth et al 2009;Parker et al 2011).…”

The Use of C-/X-Band Time-Gapped SAR Data and Geotechnical Models for the Study of Shanghai’s Ocean-Reclaimed Lands through the SBAS-DInSAR Technique

“…It relies on the least-squares (LS) inversion of a suitably selected sequence of small baseline (SB) interferograms through the singular value decomposition (SVD) method [32]. Over recent years, DInSAR techniques have been widely applied to monitor deformation phenomena caused by several natural and anthropogenic hazards, including landslides [33,34], ground failures due to tunneling excavations [35,36], and terrain consolidation and land-subsidence of river deltas [37][38][39].…”