In this work, an innovative methodology to generate the automatic ground motion areas mapping is presented. The methodology is based on the analysis of the Synthetic Aperture Radar (SAR)-based displacement time series. The procedure includes two modules developed using the ModelBuilder tool (ArcGis). These modules allow to identify the ground motion areas (GMA) using only one dataset and the persistent GMA (PGMA) considering the different monitored periods and datasets. These areas represent clusters of targets characterized by the same displacement time series trend. The procedure was tested using different sensors such as ERS- 1/2, ENVISAT, COSMO-SkyMed and Sentinel-1 covering the periods, 1992-2000, 2003-2010, 2012-2016 and 2014-2017, respectively, over an area of about 500 km2 in the Venetian-Friulian coastal Plain (NE Italy). The resulting mapping allows to detect priority areas where to address further in situ investigations such as to verify the presence of localized buried landforms.

Ground motion areas detection (GMA-D): An innovative approach to identify ground deformation areas using the SAR-based displacement time series

Meisina C.;
2020-01-01

Abstract

In this work, an innovative methodology to generate the automatic ground motion areas mapping is presented. The methodology is based on the analysis of the Synthetic Aperture Radar (SAR)-based displacement time series. The procedure includes two modules developed using the ModelBuilder tool (ArcGis). These modules allow to identify the ground motion areas (GMA) using only one dataset and the persistent GMA (PGMA) considering the different monitored periods and datasets. These areas represent clusters of targets characterized by the same displacement time series trend. The procedure was tested using different sensors such as ERS- 1/2, ENVISAT, COSMO-SkyMed and Sentinel-1 covering the periods, 1992-2000, 2003-2010, 2012-2016 and 2014-2017, respectively, over an area of about 500 km2 in the Venetian-Friulian coastal Plain (NE Italy). The resulting mapping allows to detect priority areas where to address further in situ investigations such as to verify the presence of localized buried landforms.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1424774
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