The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-7/W3
https://doi.org/10.5194/isprsarchives-XL-7-W3-827-2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-827-2015
29 Apr 2015
 | 29 Apr 2015

Long-term monitoring of a deep-seated, slow-moving landslide by mean of C-band and X-band advanced interferometric products: the Corvara in Badia case study (Dolomites, Italy)

M. Mulas, M. Petitta, A. Corsini, S. Schneiderbauer, F. V. Mair, and C. Iasio

Keywords: Deep-seated landslide, Monitoring, SAR, Advanced-Interferometry, Time-Series, Landslides

Abstract. The availability of data from various Synthetic Aperture Radar (SAR) operating in X-Band and C-Band acquired in the last decades enables to monitor slopes affected by landslides. The ASI-founded project ‘LAWINA’ (2010 – 2012) aimed at the improvement of SAR – based monitoring techniques as well as at the integration of SAR data with data stemming from other sensors. Test case area of LAWINA has been a slow-moving landslide located up-stream of Corvara in Badia village in the Dolomites, Italy. Within the scope of the project different time-series obtained through 35 Envisat2, 40 Radarsat-1 and 46 Cosmo-SkyMed covering this test area have been processed in order to explore the potentials to analyse historical and near real time landslide dynamics. The SAR data are characterized by various geometric and temporal resolutions having been acquired by 3 sensors operating at different bands in different periods between 2003 and 2011. TeleRilevamento Europa (TRE) exploited these data in order to retrive displacement timeseries applying its proprietary SqueeSAR algorithm. After re-projecting Envisat-2 and Radarsat datasets according to the CSK Line Of Sight a comparison of displacements recorded by each sensor has been possible. For this purpose, we have selected areas characterized by the presence of Persistent Scatterers or Diffused Scatterers from at least two datasets. This multi-sensor approach allowed determining the slope displacement tracking during 8 years. Even though the different time series are not formally integrated each other, the result is accurate enough to allow the evaluation of the landslide’s behaviour and trend over several years.