Abstract
In this study, hybrid integration of MultiBoosting based on two artificial intelligence methods (the radial basis function network (RBFN) and credal decision tree (CDT) models) and geographic information systems (GIS) were used to establish landslide susceptibility maps, which were used to evaluate landslide susceptibility in Nanchuan County, China. First, the landslide inventory map was generated based on previous research results combined with GIS and aerial photos. Then, 298 landslides were identified, and the established dataset was divided into a training dataset (70%, 209 landslides) and a validation dataset (30%, 89 landslides) with ensured randomness, fairness, and symmetry of data segmentation. Sixteen landslide conditioning factors (altitude, profile curvature, plan curvature, slope aspect, slope angle, stream power index (SPI), topographical wetness index (TWI), sediment transport index (STI), distance to rivers, distance to roads, distance to faults, rainfall, NDVI, soil, land use, and lithology) were identified in the study area. Subsequently, the CDT, RBFN, and their ensembles with MultiBoosting (MCDT and MRBFN) were used in ArcGIS to generate the landslide susceptibility maps. The performances of the four landslide susceptibility maps were compared and verified based on the area under the curve (AUC). Finally, the verification results of the AUC evaluation show that the landslide susceptibility mapping generated by the MCDT model had the best performance.
Highlights
Landslide often do not exist in isolation
The landslide susceptibility maps generated by the two-hybrid models and those generated by the two single models were compared in pairs
The final results show that both the hybrid model and the single model contributed to the evaluation of landslide susceptibility in the study area, but the evaluation capabilities were different
Summary
Landslide often do not exist in isolation. Landslides may occur at the same time (known as connected landslide groups) with a spatiotemporal symmetry. Landslides are among the most dangerous natural disasters and often occur after heavy rains or earthquakes [1]. The number of people who die from landslides every year is about 1000 worldwide, and landslides result in annual property losses of up to four billion dollars [2]. Landslides may be caused by various other factors, such as geological features and vegetation coverage [3,4,5,6].
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