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QIN Chengyun, REN Guangming, LIU Bin, LUO Fei, LIU Xiaoyu. The Susceptibility Assessment of Landslides Based on GIS and PCA-Logistic[J]. Journal of Xihua University(Natural Science Edition), 2019, 38(6): 100-106. DOI: 10.3969/j.issn.1673-159X.2019.06.016
Citation: QIN Chengyun, REN Guangming, LIU Bin, LUO Fei, LIU Xiaoyu. The Susceptibility Assessment of Landslides Based on GIS and PCA-Logistic[J]. Journal of Xihua University(Natural Science Edition), 2019, 38(6): 100-106. DOI: 10.3969/j.issn.1673-159X.2019.06.016

The Susceptibility Assessment of Landslides Based on GIS and PCA-Logistic

  • Assessment of regional geological hazard susceptibility is an important basis for regional early disaster warning.This article stated in the region of the 1 : 50 000 geological disaster survey data as the foundation, analyzed the development law, distribution characteristics and influencing factors of regional slope hazards, selecting regional faults, water system and stratigraphic lithology, etc eight factors based on GIS platform and combined with Logistic regression (Logistic) and principal component analysis (PCA) method to judge the liability of regional slope geological disasters. Fault density and historical disaster density in the study area are the main controlling factors affecting the development of slope geological hazards in the region. With the increase of fault density and disaster point density, the distance between faults and water systems decreases, and the distribution of slope hazards in the region presents an increasing trend. Among them, the high vulnerable areas of slope disasters should be distributed on both sides of hot water river, the middle vulnerable areas are mainly distributed on the east side of anning river, and the low vulnerable areas and basic safety areas are mainly distributed in the flat terrain areas of anning river valley.The AUC test of the two evaluation results shows that the evaluation results of the two models can accurately reflect the development of geological hazards in the region, and the evaluation results of the vulnerability of the complex mathematical model to geological hazards are better than that of the single mathematical model.
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