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Spatial distribution of natural disaster risk has been taking as a reference in urban planning and disaster management. Especially to the remote mountainous areas located in southwestern China where landslide disaster could cause enormous damage. In those areas, only few exposure researches could reveal disaster risk and exposure distribution which related to landslide occurrence since lack of landslide indicator information. This research aimed at combining landslide risk mapping with highly exposure mapping to reveal distribution of highly landslide exposure in a remote mountainous area: Panzhihua basin, Yangtze River, China. In this research, 203 landslide point data (103 occurrences and 100 absences) were collected based on governmental landslide inventory and fieldwork to build CART (Classification and Regression Tree) model, which was applied to investigate the relationship between landslide disaster and four independent variables (vegetation, elevation, slope and top soil type). Finally, we developed a landslide-prone hazard map based on transportation, threatened population and property distribution to illustrate potential socioeconomic damage of landslide occurrence. The output maps show that landslide-prone area basically follows valley stretch and Yangtze Rivers. Northeastern and center zone in study area are classified with higher risk to generate landslide disaster. Threaten population and property exposure shows similar distribution in northeastern and northwestern areas while detached in center and southeastern areas. To the transportation sector, there are 75.3km of local road, 8.6km of main road, 29.5km of railway and 39.2km of national highway are highly exposed to landslide occurrence respectively.

Spatial Distribution of Landslide Risk and Exposure Based on CART Model and GIS Technology - Case Study of Panzhihua Basin, Yangtze River, China