DOI: 10.1007/s11069-020-04128-z
论文题名: Mapping the susceptibility to landslides based on the deep belief network: a case study in Sichuan Province, China
作者: Wang W. ; He Z. ; Han Z. ; Li Y. ; Dou J. ; Huang J.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期: 3 起始页码: 3239
结束页码: 3261
语种: 英语
中文关键词: Deep belief network
; Deep learning
; Landslides mapping
; Sichuan area
; Susceptibility
英文关键词: artificial neural network
; back propagation
; data set
; geological mapping
; landslide
; machine learning
; regression analysis
; stochasticity
; trigger mechanism
; China
; Sichuan
英文摘要: A dataset of landslides from Sichuan Province in China, containing 1551 historical individual landslides, is a result of two teams’ effort in the past few years to map the susceptibility to landslides. Considering complex internal relations among the triggering factors, logistic regression (LR) and shallow neural networks, such as back-propagation neural network (BPNN), are often limited. In this paper, we make a straightforward development that the deep belief network (DBN) based on deep learning technology is introduced to map the regional susceptibility to landslides. Seven factors with respect to geomorphology, geology and hydrology are considered and verified through the collinearity test. A DBN model containing three pre-trained layers of restricted Boltzmann machines by stochastic gradient descent method is configured to obtain the susceptibility to landslides. Susceptibility results evaluated by DBN model are compared with those by LR and BPNN in the receive operator characteristic (ROC) analysis, showing that DBN has a better prediction precision, with a lower rate of false alarms and fake alarms. The case study also indicates different sensitivities of the triggering factors to the landslide susceptibility, that the factors of altitude, distance to drainage network and average annual rainfall have significant impact in mapping the susceptibility to landslides in the region. This research will contribute to a better-performance model for regional-scale mapping for the susceptibility to landslides, in particular, at the area where triggering factors show complex relations and relative independence. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168786
Appears in Collections: 气候变化与战略
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作者单位: School of Civil Engineering, Central South University, 22 Shaoshan Road, Changsha, Hunan 410075, China; The Key Laboratory of Engineering Structures of Heavy Haul Railway, Ministry of Education, Changsha, 410075, China; Department of Civil and Environmental Engineering, Nagaoka University of Technology, Niigata, 940-2188, Japan
Recommended Citation:
Wang W.,He Z.,Han Z.,et al. Mapping the susceptibility to landslides based on the deep belief network: a case study in Sichuan Province, China[J]. Natural Hazards,2020-01-01,103(3)