A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

The main purpose of the present study is to use three state-of-the-art data mining techniques, namely, logistic model tree (LMT), random forest (RF), and classification and regression tree (CART) models, to map landslide susceptibility. Long County was selected as the study area. First, a landslide...

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Vydáno v:	Catena (Giessen) Ročník 151; s. 147 - 160
Hlavní autoři:	Chen, Wei, Xie, Xiaoshen, Wang, Jiale, Pradhan, Biswajeet, Hong, Haoyuan, Bui, Dieu Tien, Duan, Zhao, Ma, Jianquan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.04.2017
Témata:	aerial photography altitude China Classification and regression tree inventories land use Landslide landslides Logistic model tree logit analysis normalized difference vegetation index prediction rain Random forest rivers roads support vector machines surveys Classification and regression tree Random forest Landslide China Logistic model tree
ISSN:	0341-8162, 1872-6887
On-line přístup:	Získat plný text
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