气候变化领域集成服务门户(CCPortal): Key predisposing factors and susceptibility assessment of landslides along the Yunnan-Tibet traffic corridor, Tibetan plateau: Comparison with the LR, RF, NB, and MLP techniques

CCPortal

DOI	10.3389/feart.2022.1100363
	Key predisposing factors and susceptibility assessment of landslides along the Yunnan-Tibet traffic corridor, Tibetan plateau: Comparison with the LR, RF, NB, and MLP techniques
	Wang, Sen; Ling, Sixiang; Wu, Xiyong; Wen, Hong; Huang, Junpeng; Wang, Feng; Sun, Chunwei
发表日期	2023
EISSN	2296-6463
卷号	10
英文摘要	The Yunnan-Tibet traffic corridor runs through the Three Rivers Region, southeastern Tibetan Plateau, which is characterized by high-relief topography and active tectonics, with favourable conditions for landslides. It is of great significance to identify the key predisposing factors of landslides and to reveal the landslide susceptibility in this area. A total of 2,308 landslides were identified as learning samples through remote sensing interpretation and detailed field surveys, and four machine learning algorithms involving logistic regression (LR), random forest (RF), naive Bayes (NB) and multilayer perceptron (MLP) were compared to model the landslide susceptibility. Through the multicollinearity test, 13 influential factors were selected as conditioning factors. The area under the curve (AUC) values of LR, RF, NB and MLP models are .788, .918, .785 and .836 respectively, indicating that the four models have good or very good prediction accuracy in landslide susceptibility assessment along the Yunnan-Tibet traffic corridor. In addition, the elevation, slope, rainfall, distance to rivers, and aspect play a major role in landslide development in the study area. The susceptibility zoning map based on the best RF model shows that the areas with high susceptibility and very high susceptibility account for 12.24% and 6.72%, respectively, and are mainly distributed along the Jinsha River, the Lancang River and the G214 highway.
关键词	landslide susceptibility machine learning algorithms variable importance three rivers region yunnan-tibet traffic corridor
英文关键词	SUPPORT VECTOR MACHINE; RANDOM FOREST; LOGISTIC-REGRESSION; SPATIAL PREDICTION; FREQUENCY RATIO; NEURAL-NETWORKS; TREE; AREA; CLASSIFICATION; OPTIMIZATION
WOS研究方向	Geosciences, Multidisciplinary
WOS记录号	WOS:000918667300001
来源期刊	FRONTIERS IN EARTH SCIENCE
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/282845
作者单位	Southwest Jiaotong University; Southwest Jiaotong University; Xihua University; University of Sydney
推荐引用方式 GB/T 7714	Wang, Sen,Ling, Sixiang,Wu, Xiyong,et al. Key predisposing factors and susceptibility assessment of landslides along the Yunnan-Tibet traffic corridor, Tibetan plateau: Comparison with the LR, RF, NB, and MLP techniques[J],2023,10.
APA	Wang, Sen.,Ling, Sixiang.,Wu, Xiyong.,Wen, Hong.,Huang, Junpeng.,...&Sun, Chunwei.(2023).Key predisposing factors and susceptibility assessment of landslides along the Yunnan-Tibet traffic corridor, Tibetan plateau: Comparison with the LR, RF, NB, and MLP techniques.FRONTIERS IN EARTH SCIENCE,10.
MLA	Wang, Sen,et al."Key predisposing factors and susceptibility assessment of landslides along the Yunnan-Tibet traffic corridor, Tibetan plateau: Comparison with the LR, RF, NB, and MLP techniques".FRONTIERS IN EARTH SCIENCE 10(2023).