- Title
- Effects of different landslide boundaries and their spatial shapes on the uncertainty of landslide susceptibility prediction
- Creator
- Huang, Faming; Cao, Yu; Fan, Xuanmei; Li, Wenbin; Huang, Jinsong; Zhou, Chuangbing; Fan, Wenyan
- Relation
- Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering Vol. 40, Issue 15 November 2021, p. 3227-3240
- Relation
- http://english.whrsm.cas.cn/sp/200909/t20090904_35796.html
- Publisher
- Zhongguo Kexueyuan Wuhan Yantu Lixue Yanjiuso,Chinese Academy of Sciences, Institute of Rock and Soil Mechanics
- Resource Type
- journal article
- Date
- 2021
- Description
- The landslide boundaries and their spatial shapes usually appear as irregular polygonal surfaces such as semi-circle and dustpan. However, literature review shows that inaccurate landslide point and buffer circle are commonly used as the landslide boundary for landslide susceptibility prediction(LSP), leading to some uncertainties in the LSP results. To study the effects of different landslide boundaries on the LSP modelling, 337 landslides and 10 types of environmental factors in Shangyou County of Jiangxi Province are taken as basic data. The correlations between environmental factors and landslides are built based on different landslide boundaries forms of point, buffer circle and accurate polygonal surface. Next, the multi-layer perceptron(MLP) and random forest(RF) are selected to build six kinds of LSP models, namely, Point, circle and polygon-based MLP and RF models. Finally, three methods are used to analyse the LSP uncertainties, including the ROC accuracy, difference significance analysis and distribution rules of landslide susceptibilityindexs. Results show that:(1) LSP uncertainties will increase under the landslide boundaries of landslide point or buffer circle, while the accuracy and reliability of LSP results will increase under the accurate landslide polygon boundaries. (2) The uncertainty rules of LSP obtained by MLP and RF models are consistent, however, the uncertainty of RF is lower than those of MLP.(3) The LSP results of point and buffer circle based models can also reflect the spatial distribution rules of landslide probability on the whole, and can be used as a substitute scheme in the absence of accurate landslide boundaries.
- Subject
- landslide boundary; landslide susceptibility; machine learning; random forest; slope engineering; uncertainty analysis
- Identifier
- http://hdl.handle.net/1959.13/1472947
- Identifier
- uon:48954
- Identifier
- ISSN:1000-6915
- Language
- eng
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