Terrain Pattern Recognition and Spatial Decision Making for Regional Slope Stability Studies

Abstract

A terrain partition scheme is presented that allows the identification of regions with high landslide risk in natural terrain zones on the basis of geomorphometric criteria from moderate resolution DEMs. The key factor being the terrain segmentation to aspect regions (regions formed by points preserving the same aspect direction) instead of using an artificial regular-grid terrain partition scheme. The study area is in western Greece (NW Peloponnesus) whereas a moderate resolution digital elevation model with spacing 75 m is used. Landslide inventory analysis and knowledge conceptualization identified that the landslide susceptibility of a particular aspect region is high, if the mean elevation is low and the mean gradient is high. Each aspect region was parametrically represented on the basis of its mean gradient and elevation. The domain of each parameter was divided to seven slices (classes) on the basis of the observed density. Subsequent knowledge based mapping identified aspect regions with high landslide susceptibility for the following spatial rule: (a) “mean slope in class 6 or 7” and (b) “mean elevation in class 1 to 5”. Alternatively the rule is expressed as mean slope to be equal or greater than 15∘ whereas mean elevation to be in the range 0 to 750 m. These identified zones correspond to regions where historical landslides occurred (populated coastal areas in the North) as well as to south regions (natural terrain zone) where no landslide record is available, because of the limitations posed by the natural terrain landslide mapping program in Greece. The presented terrain segmentation technique combined to the spatial decision-making process, provided both an object framework for integrating geomorphometric parameters and a method for landslide risk analysis in natural terrain zones.