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  • Tran, Quoc CuongInstitute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam (författare)

Novel Ensemble Landslide Predictive Models Based on the Hyperpipes Algorithm : A Case Study in the Nam Dam Commune, Vietnam

  • Artikel/kapitelEngelska2020

Förlag, utgivningsår, omfång ...

  • 2020-05-27
  • Switzerland :MDPI,2020
  • electronicrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:ltu-79019
  • https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79019URI
  • https://doi.org/10.3390/app10113710DOI

Kompletterande språkuppgifter

  • Språk:engelska
  • Sammanfattning på:engelska

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Klassifikation

  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:art swepub-publicationtype

Anmärkningar

  • Validerad;2020;Nivå 2;2020-06-15 (alebob)
  • Development of landslide predictive models with strong prediction power has become a major focus of many researchers. This study describes the first application of the Hyperpipes (HP) algorithm for the development of the five novel ensemble models that combine the HP algorithm and the AdaBoost (AB), Bagging (B), Dagging, Decorate, and Real AdaBoost (RAB) ensemble techniques for mapping the spatial variability of landslide susceptibility in the Nam Dan commune, Ha Giang province, Vietnam. Information on 76 historical landslides and ten geo-environmental factors (slope degree, slope aspect, elevation, topographic wetness index, curvature, weathering crust, geology, river density, fault density, and distance from roads) were used for the construction of the training and validation datasets that are the prerequisites for building and testing the proposed models. Using different performance metrics (i.e., the area under the receiver operating characteristic curve (AUC), negative predictive value, positive predictive value, accuracy, sensitivity, specificity, root mean square error, and Kappa), we verified the proficiency of all five ensemble learning techniques in increasing the fitness and predictive powers of the base HP model. Based on the AUC values derived from the models, the ensemble ABHP model that yielded an AUC value of 0.922 was identified as the most efficient model for mapping the landslide susceptibility in the Nam Dan commune, followed by RABHP (AUC = 0.919), BHP (AUC = 0.909), Dagging-HP (AUC = 0.897), Decorate-HP (AUC = 0.865), and the single HP model (AUC = 0.856), respectively. The novel ensemble models proposed for the Nam Dan commune and the resultant susceptibility maps can aid land-use planners in the development of efficient mitigation strategies in response to destructive landslides.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Minh, Duc DoVNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam (författare)
  • Jaafari, AbolfazlResearch Institute of Forests and Rangelands, Agricultural Research, Education, and Extension Organization (AREEO), P.O. Box 64414-356, Tehran 64414, Iran (författare)
  • Al-Ansari, Nadhir,1947-Luleå tekniska universitet,Geoteknologi(Swepub:ltu)nadhir (författare)
  • Minh, Duc DaoInstitute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam. Vietnam Academy of Sciences and Technology, Graduate University of Science and Technology, 18 Hoang Quoc Viet, Hanoi 100000, Vietnam (författare)
  • Van, Duc TungInstitute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam (författare)
  • Nguyen, Duc AnhInstitute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam (författare)
  • Tran, Trung HieuInstitute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam (författare)
  • Ho, Lanh SiCivil and Environmental Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739-527, Japan (författare)
  • Nguyen, Duy HuuFaculty of Geography, VNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam (författare)
  • Prakash, IndraDepartment of Science & Technology, Bhaskarcharya Institute for Space Applications and Geo-Informatics (BISAG), Government of Gujarat, Gandhinagar 382002, India (författare)
  • Le, Hiep VanInstitute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam (författare)
  • Pham, Binh ThaiUniversity of Transport Technology, Hanoi 100000, Vietnam (författare)
  • Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, VietnamVNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:Applied SciencesSwitzerland : MDPI10:112076-3417

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