Landslide susceptibility mapping along the upper Jinsha River, south-western China: a comparison of hydrological and curvature watershed methods for slope unit classification

The mapping unit is the smallest indivisible unit of landslide susceptibility mapping. The mapping unit considerably affects the effect of landslide susceptibility mapping. Among many mapping units, the slope unit is one of the most suitable units for landslide susceptibility mapping. The methods available for classifying slope unit are not uniform, and the dividing effects differ. In this study, the hydrological method and curvature watershed method were used to classify the slope units in the study area on the upper Jinsha River, south-western China. Lithology, slope angle, slope aspect, normalized difference vegetation index (NDVI), land cover, rainfall, curvature, distance-to-river, distance-to-fault, were selected as the landslide conditioning factors. Support vector machine were applied to the landslide susceptibility modeling. Statistical indexes, 5-flod cross validation, Kappa coefficient, and AUC values were introduced to validate the prediction accuracy of the landslide susceptibility model. By comparing the shape characteristics of slope units classified by the two methods, we found that the slope unit classified based on curvature watershed method has a uniform size, shape between circle and equilateral triangle, and small internal terrain variation. As for the mean prediction accuracy, Kappa coefficient and AUC values of landslide susceptibility model, in the training stage, were 81.62%, 63.23%, and 89.72%, respectively, for the hydrological method, while 84.26%, 68.51%, and 90.80%, respectively, for the curvature watershed method; in the testing stage, were 80.70%, 61.40%, and 88.08%, respectively, for the hydrological method, while 83.24%, 66.49%, and 88.96%, respectively, for the curvature watershed method, which means that the curvature watershed method is more effective to produce landslide susceptibility map of the study area.