Landslide susceptibility assessment in southern Anhui Province based on slope units and semantic segmentation
Landslide disasters seriously affect people's lives and property safety and cause significant damage to the natural environment.Landslide susceptibility assessment based on slope units can allow for a more accurate representation of the actual terrain and provide more scientific theoretical support for the prevention and control of landslide disasters.Based on the data of landslide points in Huangshan,Xuancheng,Chizhou cities and the basic geographical data of southern Anhui Province,this paper selects landslide evaluation factors by using principal component analysis and multicollinearity analysis,proposes an innovative method that combines the geometric shape information of slope units and semantic segmentation,builds a landslide disaster vulnerability assessment model to evaluate the vulnerability of landslide disasters in southern Anhui Province and reveal its spatial distribution pattern.The results show that the landslide susceptibility assessment model constructed by combining slope units and semantic segmentation has high prediction accuracy and can fully consider the influence of geometric shape information of slope units on landslide susceptibility,and accurately assess the landslide susceptibility in southern Anhui Province.The evaluation results are consistent with the formation mechanism of landslides,with 62.19%of landslide units distributed on slope units with medium to high landslide susceptibility levels.The model predicts an AUC value of 0.878,which is significantly improved in prediction accuracy compared to CNN models lacking geometric shape information.