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

Catena

Volumn 151, Issue , 2017, Pages 147-160

  Chen, Wei ^a   Xie, Xiaoshen ^a   Wang, Jiale ^a   Pradhan, Biswajeet ^b,c   Hong, Haoyuan ^d   Bui, Dieu Tien ^e   Duan, Zhao ^a   Ma, Jianquan ^a  

^a XI'AN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^c Sejong University   (South Korea)

^d Jiangxi Meteorological Bureau   (China)

^e UNIVERSITY OF SOUTH EASTERN NORWAY   (Norway)

Author keywords

China; Classification and regression tree; Landslide; Logistic model tree; Random forest

Indexed keywords

ACCURACY ASSESSMENT; AERIAL PHOTOGRAPHY; AREAL INTERPOLATION; COMPARATIVE STUDY; CURVATURE; DATA MINING; FIELD SURVEY; LANDSLIDE; LOGIT ANALYSIS; MODEL VALIDATION; PREDICTION; REGRESSION ANALYSIS; SLOPE ANGLE; SPATIAL ANALYSIS; SUPPORT VECTOR MACHINE; VULNERABILITY;

GEORGIA; LONG COUNTY; UNITED STATES;

EID: 85007211610     PISSN: 03418162     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.catena.2016.11.032     Document Type: Article

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