Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/22263
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dc.contributor.authorTehrany, Mahyaten
dc.contributor.authorShabani, Farzinen
dc.contributor.authorJavier, Dymphnaen
dc.contributor.authorKumar, Laliten
dc.date.accessioned2018-01-02T11:23:00Z-
dc.date.issued2017-
dc.identifier.citationGeomatics, Natural Hazards and Risk, 8(2), p. 1695-1714en
dc.identifier.issn1947-5713en
dc.identifier.issn1947-5705en
dc.identifier.urihttps://hdl.handle.net/1959.11/22263-
dc.description.abstractSoil erosion is a global geological hazard which can be mitigated through better future land-use planning. In the current research, a Dempster-Shafer-based evidential belief function (EBF) and frequency ratio (FR) were used to map the soil erosion susceptible areas and their outcomes were compared subsequently. These methods were selected due to their efficiency and popularity in natural hazard studies. Moreover, the application of EBF is poorly examined in this area of research. Nine conditioning factors belonging to the current time, and rainfall intensity for the two time periods of current time and 2100 based on the A2 scenario CSIRO global climate model, were utilized in this research. The main aim was to estimate and compare the soil erosion hazards at Southern Luzon in the Philippines under two time periods, current time and 2100. This region has been highly affected by erosion and has not received much attention in the past. The area under the curve outcomes indicated that the FR model produced 70.6% prediction rate, while EBF showed superior prediction accuracy with a rate of 83.1%. The results also project that soil erosion hazards in the Philippines will increase due to changes in rainfall patterns by 2100.en
dc.languageenen
dc.publisherTaylor & Francisen
dc.relation.ispartofGeomatics, Natural Hazards and Risken
dc.titleSoil erosion susceptibility mapping for current and 2100 climate conditions using evidential belief function and frequency ratioen
dc.typeJournal Articleen
dc.identifier.doi10.1080/19475705.2017.1384406en
dcterms.accessRightsGolden
dc.subject.keywordsGeospatial Information Systemsen
dc.subject.keywordsEnvironmental Engineering Modellingen
dc.subject.keywordsEnvironmental Monitoringen
local.contributor.firstnameMahyaten
local.contributor.firstnameFarzinen
local.contributor.firstnameDymphnaen
local.contributor.firstnameLaliten
local.subject.for2008050206 Environmental Monitoringen
local.subject.for2008090903 Geospatial Information Systemsen
local.subject.for2008090702 Environmental Engineering Modellingen
local.subject.seo2008961010 Natural Hazards in Urban and Industrial Environmentsen
local.subject.seo2008960303 Climate Change Modelsen
local.subject.seo2008961008 Natural Hazards in Mountain and High Country Environmentsen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailmtehrany@une.edu.auen
local.profile.emailfshaban2@une.edu.auen
local.profile.emaildjavier@myune.edu.auen
local.profile.emaillkumar@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-chute-20171010-145556en
local.publisher.placeUnited Kingdomen
local.format.startpage1695en
local.format.endpage1714en
local.peerreviewedYesen
local.identifier.volume8en
local.identifier.issue2en
local.access.fulltextYesen
local.contributor.lastnameTehranyen
local.contributor.lastnameShabanien
local.contributor.lastnameJavieren
local.contributor.lastnameKumaren
dc.identifier.staffune-id:mtehranyen
dc.identifier.staffune-id:fshaban2en
dc.identifier.staffune-id:djavieren
dc.identifier.staffune-id:lkumaren
local.profile.orcid0000-0002-9205-756Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:22452en
local.identifier.handlehttps://hdl.handle.net/1959.11/22263en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleSoil erosion susceptibility mapping for current and 2100 climate conditions using evidential belief function and frequency ratioen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorTehrany, Mahyaten
local.search.authorShabani, Farzinen
local.search.authorJavier, Dymphnaen
local.search.authorKumar, Laliten
local.uneassociationUnknownen
local.identifier.wosid000418899200089en
local.year.published2017en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/e45249ed-5fd4-4181-8aa2-a20dde1cf2baen
local.subject.for2020401102 Environmentally sustainable engineeringen
local.subject.for2020401103 Global and planetary environmental engineeringen
local.subject.for2020401302 Geospatial information systems and geospatial data modellingen
local.subject.seo2020190501 Climate change modelsen
dc.notification.token47d6259f-8dc5-43a9-8136-60b84ab0c798en
local.codeupdate.date2022-03-25T09:50:49.563en
local.codeupdate.epersonghart4@une.edu.auen
local.codeupdate.finalisedtrueen
local.original.for2020401302 Geospatial information systems and geospatial data modellingen
local.original.for2020undefineden
local.original.for2020401102 Environmentally sustainable engineeringen
local.original.for2020401103 Global and planetary environmental engineeringen
local.original.seo2020190501 Climate change modelsen
local.original.seo2020undefineden
local.original.seo2020undefineden
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School of Environmental and Rural Science
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