Monitoring long-term ground movements and Deep Seated Gravitational Slope Deformations by InSAR time series: cases studies in Italy

Salvatore Stramondo(1) , M Saroli(2) , M. Moro(1) , S. Atzori(1) , C. Tolomei(1) , S. Salvi(1) , and Riccardo Lanari(3)

(1) Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata 605, 00143 Roma, Italy
(2) Università degli Studi di Roma La Sapienza, Piazzale Aldo Moro, 5 00185 Roma, 00185 Roma, Italy
(3) IREA-CNR, via Diocleziano 328, 80124 Napoli, Italy

Abstract

Surface soil movements can be the expression of gravitative or tectonic events. Two techniques like InSAR and aerial photo analysis (Volo Italia, 1988-89) have been combined to study these movements, in northern-central portion of Sicily region (Southern Italy), in the Lucanian Apennines ("axial zone" of the southern Apennines, Italy), in Abruzzi and Umbria- Marche regions. This integrated approach allows to detect and classify slow movements as Deep Seated Gravitational Slope Deformations (DSGSD). The investigated areas are morphologically characterized by significant elevation changes due to the presence of high mountainous peaks, separated from surrounding depressed areas by steep escarpments. Consequently, relief energy favours the development of gravity-driven deformations. They seem to be superimposed on and influenced by the inherited structural and tectonic pattern, related to the sin- and post-thrusting evolution. Recent improvements of the classical Differential SAR Interferometry have expanded the field of application of this technique to the detection of very slow deformations, providing measurements of ground velocity with accuracies of mm/years (Ferretti et al., 2001; Berardino et al., 2002). In these new techniques, long time series of SAR images are used, and, provided that sufficient multi-temporal coherence exists, the displacement time history is computed for each coherent pixel or stable ground scatterer. A specific filtering algorithm is then used to remove the tropospheric contribution from the phase signal, restoring the ground displacement velocity in the line of sight of the SAR antenna (LoS). We present the application of the Small Baseline Subset technique (Berardino et al., 2002) to large datasets of ERS images for the selected areas.

 

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