Abstract
Landslides are one of the most extensive geological disasters in the world. The objective of this study was to assess the performances of different landslide susceptibility models information content method (ICM), analytical hierarchy process (AHP), and random forest (RF) model) and mapping unit (slope unit and grid unit) for landslide susceptibility mapping in the Helong city, Jilin province, northeastern China. First, a total of 159 landslides were mapped in the study area based on a geological hazard survey (1:50,000) of Helong city. Then, the slope units of the study area were divided by using the curvature watershed method. Next, eight influencing factors, namely, lithology, slope angle, slope aspect, rainfall, land use, seismic intensity, distance to river, and distance to fault, were selected to map the landslide susceptibility based on geological data, field survey, and landslide information. Afterward, landslide susceptibility modeling of landslide inventory data is performed for extracting and learning the symmetry latent in data patterns and relationships by three landslide susceptibility models and utilizing it to predict landslide susceptibility. Finally, the receiver operating characteristic (ROC) curve was used to compare the landslide susceptibility models. In addition, results based on grid units were calculated for comparison. The AUC (the area under the curve) result for ICM, AHP, and RF model was 87.1%, 80.5%, and 94.6% for slope units, and 83.4%, 70.9%, and 91.3% for grid units, respectively. Based on the overall assessments, the SU-RF model was the most suitable model for landslide susceptibility mapping. Consequently, these methods can be very useful for landslide hazard mitigation strategies.
Highlights
Landslides are among the world’s most destructive geological disasters, threatening the human life, environments, resources, and property [1,2,3,4]
The receiver operating characteristic (ROC) curve has been widely used in the accuracy validation of binary classification models [13,32,33]
The results indicate that tectonic activity, river action, lithology, and topography are the main factors that contribute to the occurrence of landslides in the study area
Summary
Landslides are among the world’s most destructive geological disasters, threatening the human life, environments, resources, and property [1,2,3,4]. By analyzing maps of landslide susceptibility, areas that are highly susceptible to these events can be evaluated and located. With this information, people can take appropriate preventive measures to reduce the negative impact of the landslide. Landslide susceptibility mapping has become one of the most important subjects in international geomorphology and engineering geology [7,8,9,10]. The methods used for landslide susceptibility mapping are mainly divided into qualitative analysis and quantitative analysis [11,12,13,14,15]. The basis of qualitative analysis is the thorough investigation of the causal mechanism of landslides by gaining a complete understanding of the Symmetry 2020, 12, 1848; doi:10.3390/sym12111848 www.mdpi.com/journal/symmetry
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