Landslide Susceptibility Mapping Using Weighted Linear Combination: A Case of Gucheng Town in Ningxia, China

The main purpose of this study was to compare and evaluate the applicability of two weighted linear combination methods (WLC) in landslide susceptibility assessment, with Gucheng town of Ningxia province in China taken as the study area. Subsequently, through the study of geological environment char...

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Veröffentlicht in:Geotechnical and geological engineering 2023-03, Vol.41 (2), p.1247-1273
Hauptverfasser: Li, Huan, Mao, Zhengjun, Sun, Jiewen, Zhong, Jiaxin, Shi, Shuojie
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Mao, Zhengjun
Sun, Jiewen
Zhong, Jiaxin
Shi, Shuojie
description The main purpose of this study was to compare and evaluate the applicability of two weighted linear combination methods (WLC) in landslide susceptibility assessment, with Gucheng town of Ningxia province in China taken as the study area. Subsequently, through the study of geological environment characteristics, landslide development and landslide formation mechanism in loess region, divided the slope unit, using TFN-AHP and FR, and RF and FR weighted linear combination methods (WLC) to assess landslide susceptibility. Furthermore, the zoning map of landslide susceptibility assessment was drawn taking into account 11 landslide influencing factors which include elevation, slope, aspect, plan curvature, profile curvature, lithology, rainfall, NDVI, groundwater, land use and distance to river. Meanwhile, this study particularly used WLC to combine the weight of the two models, and Receiver Operating Characteristic (ROC) was used to verify the success rate. The AUC results of TFN-AHP and FR, and RF and FR weighted linear grouping methods were 0.777 and 0.749, respectively. It was then concluded thus, that TFN-AHP and FR, and RF and FR weight linear combination methods could be used in landslide susceptibility assessment research, but different geological environment conditions and assessment units may have a great impact on the research results. RF and FR weighted linear combination method also proved to be inferior to TFN-AHP and FR weighted linear combination method, which may be due to the small number of landslides. Moreover, there is urgent need for further exploration in research areas similar to WLC method, as it certainly holds a significant reference value.
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Subsequently, through the study of geological environment characteristics, landslide development and landslide formation mechanism in loess region, divided the slope unit, using TFN-AHP and FR, and RF and FR weighted linear combination methods (WLC) to assess landslide susceptibility. Furthermore, the zoning map of landslide susceptibility assessment was drawn taking into account 11 landslide influencing factors which include elevation, slope, aspect, plan curvature, profile curvature, lithology, rainfall, NDVI, groundwater, land use and distance to river. Meanwhile, this study particularly used WLC to combine the weight of the two models, and Receiver Operating Characteristic (ROC) was used to verify the success rate. The AUC results of TFN-AHP and FR, and RF and FR weighted linear grouping methods were 0.777 and 0.749, respectively. It was then concluded thus, that TFN-AHP and FR, and RF and FR weight linear combination methods could be used in landslide susceptibility assessment research, but different geological environment conditions and assessment units may have a great impact on the research results. RF and FR weighted linear combination method also proved to be inferior to TFN-AHP and FR weighted linear combination method, which may be due to the small number of landslides. 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subjects Civil Engineering
Curvature
Earth and Environmental Science
Earth Sciences
Geology
Geotechnical Engineering & Applied Earth Sciences
Groundwater
Hydrogeology
Land use
Landslides
Landslides & mudslides
Lithology
Loess
Methods
Original Paper
Rainfall
Susceptibility
Terrestrial Pollution
Waste Management/Waste Technology
Weight
title Landslide Susceptibility Mapping Using Weighted Linear Combination: A Case of Gucheng Town in Ningxia, China
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