Abstract

Landslide is one of the most disastrous geological hazards in the Pearl River Delta area. In the article, landslide susceptibility index (LSI) and analytical hierarchy process (AHP) have been adopted to assess landslide susceptibility (LS) of the Pearl River Delta area. A total of 294 historical landslide sites were extracted from China Geological Survey Result CGS2015-008 and remote sensing images as landslide inventory. In each experiment, 198 landslide points were randomly selected as training samples and the remaining 96 as verification samples. Nine influencing factors, i.e., standard deviation (STD) of elevation, terrain roughness, curvature, lithology, fault, land use, water density, road density, and aspect, were obtained through ASTER GDEM, China Geological Survey Result CGS2015-008, Geographical Information Monitoring Cloud Platform, Open Street Map, and Google Earth. LSI was used to represent the contribution of each category within the influencing factors to the occurrence of landslides (LSIi), and AHP was used to calculate the weights between different influencing factors (Wi). Finally, the summation of the product of LSIi by Wi was used to represent the LS value for each pixel. Then, the study area was grouped into five susceptibility classes based on the landslide susceptibility. It is indicated that terrain factors have the greatest impact on landslides, followed by engineering geological lithology and land use types. The high and very high susceptibility classes were mainly distributed in the area of: 1) STD of elevation of 0.8–2.5, roughness of 1.004–1.030, and curvature 2.7–7.2; 2) sand-shale stone and coal, bedded clastic rock, and bedded epimetamorphic rock; and 3) woodland and the urban and rural land. The receiver operating characteristic curves of many experimental results prove that the model has fine prediction performance and good stability. This article could provide a basis for landslide prevention and land development in the Pearl River Delta area.

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