In this work, we present a methodology for improving persistent scatterer interfero- metry (PSI) data analysis for landslide studies. This methodology is a revision of previously described procedures with several improved and newly proposed aspects. To both evaluate and validate the results from this methodology, we used various persistent scatterer (PS) datasets from different satellites (ERS – ENVISAT, Radarsat, TerraSAR-X, and ALOS PALSAR) that were processed using three PSI techniques (stable point network – SPN, permanent scatterer interferometry – PSInSARTM, and SqueeSARTM) to map and monitor landslides in various mountainous environments in Spain and Italy. This methodology consists of a preprocessing model that predicts the presence of a PS over a certain area and a post-processing method used to determine the stability threshold, project the line of sight (LOS) velocity along the slope, estimate the E–W and vertical components of the velocity, and identify anomalous areas.

A methodology for improving landslide PSI data analysis / Notti D.; Herrera G.; Bianchini S.; Meisina C.; García-Davalillo J. C.; Zucca F.. - In: INTERNATIONAL JOURNAL OF REMOTE SENSING. - ISSN 0143-1161. - STAMPA. - 35(6):(2014), pp. 2186-2214. [10.1080/01431161.2014.889864]

A methodology for improving landslide PSI data analysis

Bianchini S.;
2014

Abstract

In this work, we present a methodology for improving persistent scatterer interfero- metry (PSI) data analysis for landslide studies. This methodology is a revision of previously described procedures with several improved and newly proposed aspects. To both evaluate and validate the results from this methodology, we used various persistent scatterer (PS) datasets from different satellites (ERS – ENVISAT, Radarsat, TerraSAR-X, and ALOS PALSAR) that were processed using three PSI techniques (stable point network – SPN, permanent scatterer interferometry – PSInSARTM, and SqueeSARTM) to map and monitor landslides in various mountainous environments in Spain and Italy. This methodology consists of a preprocessing model that predicts the presence of a PS over a certain area and a post-processing method used to determine the stability threshold, project the line of sight (LOS) velocity along the slope, estimate the E–W and vertical components of the velocity, and identify anomalous areas.
2014
35(6)
2186
2214
Notti D.; Herrera G.; Bianchini S.; Meisina C.; García-Davalillo J. C.; Zucca F.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1119880
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