检索结果-南通市图书馆

GIS-based spatial prediction of landslide using road factors and random forest for Sichuan-Tibet Highway

Journal of Mountain Science 2022年第2期19卷 461-476页

作者： YE Cheng-ming WEI Rui-long GE Yong-gang LI Yao jose marcato junior Jonathan LI Key Laboratory of Earth Exploration and Information Technology of Ministry of Education Chengdu University of TechnologyChengdu 610059China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China Faculty of Engineering Architecture and Urbanism and GeographyFederal University of Mato Grosso do SulCampo Grande 79070-900Brazil Department of Geography and Environmental Management University of WaterlooWaterlooONN2L 3G1Canada

Accurate evaluation of landslide susceptibility is very important to ensure the safe operation of mountain *** Sichuan-Tibet Highway,which traverses the east of the Tibetan Plateau,frequently encounters natural *** studies generally use statistical methods to analyze the hazards along the Sichuan-Tibet *** this research,we present two road factors,namely aspect to road and road profile to increase the accuracy of landslide susceptibility mapping by considering the influence of landslide movement direction on ***,the aspect to road,which represents the impact of different landslide movement directions on the highway,was extracted by combining road direction with mountain ***,the road profile,which reflects the subgrade structure between the road and surrounding mountains,was extracted according to the terrain ***,the landslide susceptibility maps were produced based on the random forest(RF)method by using 473 landslides and 10 conditioning factors,including road factors(aspect to road,road profile)and primitive factors(slope,aspect,curvature,relief amplitude,peak ground acceleration,crustal movement velocity,faults,rainfall).The area under the receiver operating characteristic curve(AUC)and the Gini importance were used to evaluate the performance of proposed road *** AUC values on two groups that add road factors and only use primitive factors were 0.8517 and 0.8243,*** Gini importance indicated that road profile(0.123)and aspect to road(0.116)have a significant contribution to landslides compared with the primitive *** results of multi-collinearity analysis and frequency ratio confirmed the suitability of the road factors for predicting hazards along the highway.

关键词： Landslide susceptibility Spatial modeling Random forest Sichuan-Tibet Highway

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