首页|Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization

Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization

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  • NSTL
  • Springer Nature
The main objective of this study is to produce a landslide susceptibility map for the Lao Cai area (Vietnam) using a new hybrid intelligent method based on least squares support vector machines (LSSVM) and artificial bee colony (ABC) optimization, namely LSSVM-BC. LSSVM and ABC are state-of-the-art soft computing techniques that have been rarely utilized in landslide susceptibility assessment. LSSVM is adopted to develop landslide prediction model whereas ABC was used to optimize the prediction model by identifying an appropriate set of the LSSVM hyper-parameters. To establish the hybrid intelligent method, a GIS database with ten landslide-influencing factors and 340 landslide locations that occurred mainly during the last 20-years was constructed. These historical landslide locations were collected from the existing inventories that sourced from (i) five landslide projects carried out in this study areas before and (ii) interpretations of SPOT satellite images with resolution of 2.5 m. The study area was geographically split into two different parts, with landslides located in the first part was used for building models whereas the other landslides in the second part was used for the model validation. Performance of the LSSVM-BC model was assessed using the receiver operating characteristic (ROC) curve and area under the curve (AUC). Result shows that the prediction power of the model is good with the area under the curve (AUC) = 0.900. Experiments have pointed out the prediction power of the LSSVM-BC is better than that obtained from the popular support vector machines. Therefore, the proposed model is a promising tool for spatial prediction of landslides at the study area. The landslide susceptibility map is useful for landuse planning for the Lao Cai area.

LandslideArtificial bee colonyLeast squares support vector machinesGISLao CaiVietnam

Bui, Dieu Tien、Tran Anh Tuan、Nhat-Duc Hoang、Nguyen Quoc Thanh、Duy Ba Nguyen、Ngo Van Liem、Pradhan, Biswajeet

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Univ Coll Southeast Norway, Dept Business Adm & Comp Sci, Geog Informat Syst Grp, Hallvard Eikas Plass, N-3800 Bo I Telemark, Norway

Vietnam Acad Sci & Technol, Inst Marine Geol & Geophys, A27,18 Hoang Quoc Viet, Hanoi, Vietnam

Duy Tan Univ, Inst Res & Dev, Fac Civil Engn, P809-K7-25, Danang, Vietnam

Vietnam Acad Sci & Technol, Inst Geol Sci, 84 Chua Lang, Hanoi, Vietnam

Hanoi Univ Min & Geol, Fac Geomat & Land Adm, Hanoi, Vietnam

Univ Putra Malaysia, Dept Civil Engn, GISRC, Fac Engn, Serdang 43400, Selangor, Malaysia

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2017

10.1007/s10346-016-0711-9

Landslides

Landslides

EISCI
ISSN：1612-510X
年,卷(期)：2017.14(2)
  • 118
  • 74