The Use of TERRA-ASTER Satellite for Landslide Detection

Abstract

In August 2005, numerous shallow landslides occurred in the region of Vorarlberg (Austria), particularly induced by unfavourable event-related weather conditions. Two scenes of TERRA-ASTER sensor were used for the identification of the vegetation change induced by the landslides. The focus of this study is the establishment of a reliable method, comparable to aerial-photo visual interpretation standards, able to identify accurately landslides by processing a series of medium-resolution remote sensing optical data, before and after a catastrophic event. A very intuitive workflow for a semi-automatic image classification for the detection of landslide-induced change on the image data is proposed. The accuracy and validation assessment was carried out by means of a landslide (aerial-photos derived) inventory. By taking into account the central area of investigation, the landslide detection method, which adopted an innovative double classification workflow (a first supervised followed by an unsupervised algorithm), delivered a very high producer accuracy (81.5%) coupled to a more-than-acceptable user accuracy (68.9%) and kappa coefficient (72.9%).