Collecting information on landslide occurrence and activity over wide areas is a crucial task for landslide hazard assessment. Field techniques, despite being very precise, are usually not sufficient to achieve this goal, since they mostly provide point-based measurements. Mainly because of its synoptic view and its capability for repetitive observations, optical (visible-infrared) remotely sensed imagery acquired at different dates and at high spatial resolution can be considered as an effective complementary tool for field techniques to derive such information. An image-processing method to map and monitor landslide activity using multitemporal optical imagery is proposed. The method entails automatic change detection of suitably pre-processed (geometrically registered and radiometrically normalised) sequential images, followed by thresholding into landslide-related change pixels. Subsequent filtering based on the degree of rectangularity of regions can also be considered to eliminate pixel clusters corresponding to man-made land use changes. The application of this method is illustrated in the complex Tessina landslide in the Eastern Italian Alps. It has focused on discriminating the effects of a major reactivation that occurred in 1992, hence inferring the dynamics of the landslide at that time. Although the method has been devised for optical remote sensing imagery in general, in the absence of high-resolution satellite imagery covering that period, digital images derived by scanning existing aerial photograph diapositives at 1-m pixel size have been used. The method is able to classify image pixels according to landslide activity conditions.
Hervas, J. et al. (2003): Monitoring Landslides from Optical Remotely Sensed Imagery: The Case History of Tessina Landslide, Italy. Geomorphology, Vol. 54, 63-75.
