Landslide spatial probability and size are two essential components of landslide susceptibility. However, in existing slope-unit-based landslide susceptibility assessment methods, landslide size has not been explicitly considered. This paper developed a novel slope-unit based approach for landslide susceptibility assessment that explicitly incorporates landslide size. This novel approach integrates the predicted occurrence probability (spatial probability) of landslides and predicted size (area) of potential landslides for a slope-unit to obtain a landslide susceptibility value for that slope-unit. The results of a case study showed that, from a quantitative point of view, integrating spatial probability and size in slope-unit-based landslide susceptibility assessment can bring remarkable increases of AUC (Area under the ROC curve) values. For slope-unit-based scenarios using the logistic regression method and the neural network method, the average increase of AUC brought by incorporating landslide size is up to 0.0627 and 0.0606, respectively. Slope-unit-based landslide susceptibility models incorporating landslide size had utilized the spatial extent information of historical landslides, which was dropped in models not incorporating landslide size, and therefore can make potential improvements. Nevertheless, additional case studies are still needed to further evaluate the applicability of the proposed approach.
Keywords: integration; landslide susceptibility assessment; size; slope-unit; spatial probability.