In the framework of the WISELAND project, funded by MIUR, we tested the integration between LiDAR and hyperspectral methodologies in the Valoria landslide (Modena province, Italy), a high risk area with vulnerable elements, subjected to periodic and abrupt reactivations. Multitemporal LiDAR Digital Terrain Models (DTMs) allowed the calculation of a differential surface, highlighting absolute height variations, recognizing the main landslide components and identifying depletion and accumulation zones. Hyperspectral data helped in the landslide terrain roughness characterization, performing the Principal Component Analysis (PCA) and correlating the results with Flatness and Organization geomorphometric parameters derived from LiDAR DTM.

LiDAR And Hyperspectral Data Integration For Landslide Monitoring: The Test Case Of Valoria Landslide

Sterzai P;Vellico M;Coren F;
2010

Abstract

In the framework of the WISELAND project, funded by MIUR, we tested the integration between LiDAR and hyperspectral methodologies in the Valoria landslide (Modena province, Italy), a high risk area with vulnerable elements, subjected to periodic and abrupt reactivations. Multitemporal LiDAR Digital Terrain Models (DTMs) allowed the calculation of a differential surface, highlighting absolute height variations, recognizing the main landslide components and identifying depletion and accumulation zones. Hyperspectral data helped in the landslide terrain roughness characterization, performing the Principal Component Analysis (PCA) and correlating the results with Flatness and Organization geomorphometric parameters derived from LiDAR DTM.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.14083/3429
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