Combining spectral and geoenvironmental information for probabilistic event landslide mapping

Abstract

Landslide mapping is important for emergency management and landslide risk assessment. In this study, we propose a new mapping method, which combines the spectral signal contained in a satellite image and the geoenvironmental information included in a landslide susceptibility map. The image analysis captures areas with spectral signatures of event landslides in the image, while the landslide susceptibility map filters sub-areas, which do not have landslide prone conditions. The method assigns to every pixel of the satellite image a combined probability of landslide presence. We mapped typhoon-triggered landslides in southern Taiwan using the method. To compare with a landslide inventory prepared from orthophotos, we converted the probability map to a binary map of landslides and landslide free areas. Map comparison resulted in an overall accuracy of 0.93, an area percentage of overlapped landslides of 0.84, a modified success rate of 0.89, and a kappa statistic of 0.73. The method is fast, flexible, and relatively easy to use, and the probability map the method produces is useful by itself. We expect that the method can facilitate the rapid production of event landslide inventory maps, which in turn can assist emergency management.