Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor

Abstract

Landslide susceptibility mapping is essential in delineating landslide prone areas in mountainous regions. The primary purpose of this study is to evaluate landslide susceptibility mapping using three methods, information value (IV), weights-of-evidence (WofE), and certainty factor (CF) in southeastern Gansu province, China. Firstly, the landslide in the study area was located mainly using aerial-photo interpretation and field surveys. A total of 529 landslides were randomly divided using a ratio of 70/30 for training and validation of these methods. Eight landslide conditioning factors including slope angle, altitude, NDVI, distance to faults, distance to roads, distance to rivers, rainfall, and lithology, were considered. Landslide susceptibility maps were produced for each of the three methods. Susceptibility maps were verified and compared using the area under the curve (AUC) method. The success rate curve demonstrated that the AUC for the IV, WofE, and CF methods was 88.02, 87.56, and 89.04%, respectively, and the prediction rate curve showed that the AUC was 86.24, 86.34, and 87.44%, respectively. Furthermore, results showed that CF method had the highest accuracy in comparison with other methods. Generally, the three methods showed reasonable accuracy in landslide susceptibility mapping. Results of this study can serve as guidelines to managers and policy makers regarding the prevention and mitigation of landslide hazards.