Bi-temporal change analysis of satellite imagery to detect landslides triggered by intense rainfall events

This paper presents the results of implementation of bi-temporal change analysis methods to RapidEye satellite imagery to support the detection, at regional scale, of landslides caused by two intense rainfall events of 2009 and 2011, in Northern Tuscany. Image geometric and radiometric pre-processing were applied. Then, bitemporal image ratioing of Difference Vegetation Index (DVI) and bitemporal spectral transformations (Principal Component Analysis - PCA; Independent Component Analysis - ICA) were implemented. Finally, unsupervised and supervised classification allowed us to obtain thematic representation of areas of changes which supported the identification of almost hundred landslides in the study area.