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GIS based novel hybrid computational intelligence models for mapping landslide susceptibility: A case study at Da Lat City, Vietnam

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dc.citedby31
dc.contributor.authorNguyen V.-T.en_US
dc.contributor.authorTran T.H.en_US
dc.contributor.authorHa N.A.en_US
dc.contributor.authorNgo V.L.en_US
dc.contributor.authorNadhir A.-A.en_US
dc.contributor.authorTran V.P.en_US
dc.contributor.authorNguyen H.D.en_US
dc.contributor.authorMalek M.A.en_US
dc.contributor.authorAmini A.en_US
dc.contributor.authorPrakash I.en_US
dc.contributor.authorHo L.S.en_US
dc.contributor.authorPham B.T.en_US
dc.contributor.authorid57213173188en_US
dc.contributor.authorid57217085119en_US
dc.contributor.authorid57218650327en_US
dc.contributor.authorid57195242782en_US
dc.contributor.authorid51664437800en_US
dc.contributor.authorid57212081293en_US
dc.contributor.authorid57208347181en_US
dc.contributor.authorid55636320055en_US
dc.contributor.authorid49361121300en_US
dc.contributor.authorid57130381500en_US
dc.contributor.authorid57191583880en_US
dc.contributor.authorid57021167000en_US
dc.date.accessioned2023-05-29T07:22:28Z
dc.date.available2023-05-29T07:22:28Z
dc.date.issued2019
dc.descriptionartificial intelligence; computer simulation; damage mechanics; disaster management; GIS; land use planning; landslide; mapping; NDVI; weathering; Da Lat; Viet Namen_US
dc.description.abstractLandslides affect properties and the lives of a large number of people in many hilly parts of Vietnam and in the world. Damages caused by landslides can be reduced by understanding distribution, nature, mechanisms and causes of landslides with the help of model studies for better planning and risk management of the area. Development of landslide susceptibility maps is one of the main steps in landslide management. In this study, the main objective is to develop GIS based hybrid computational intelligence models to generate landslide susceptibility maps of the Da Lat province, which is one of the landslide prone regions of Vietnam. Novel hybrid models of alternating decision trees (ADT) with various ensemble methods, namely bagging, dagging, MultiBoostAB, and RealAdaBoost, were developed namely B-ADT, D-ADT, MBAB-ADT, RAB-ADT, respectively. Data of 72 past landslide events was used in conjunction with 11 landslide conditioning factors (curvature, distance from geological boundaries, elevation, land use, Normalized Difference Vegetation Index (NDVI), relief amplitude, stream density, slope, lithology, weathering crust and soil) in the development and validation of the models. Area under the receiver operating characteristic (ROC) curve (AUC), and several statistical measures were applied to validate these models. Results indicated that performance of all the models was good (AUC value greater than 0.8) but B-ADT model performed the best (AUC= 0.856). Landslide susceptibility maps generated using the proposed models would be helpful to decision makers in the risk management for land use planning and infrastructure development. � 2019 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7118
dc.identifier.doi10.3390/su11247118
dc.identifier.issue24
dc.identifier.scopus2-s2.0-85081628946
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85081628946&doi=10.3390%2fsu11247118&partnerID=40&md5=216c0f0f987545caa6a5a61ac1f84e6a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24260
dc.identifier.volume11
dc.publisherMDPIen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleSustainability (Switzerland)
dc.titleGIS based novel hybrid computational intelligence models for mapping landslide susceptibility: A case study at Da Lat City, Vietnamen_US
dc.typeArticleen_US
dspace.entity.typePublication
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