Show simple item record

dc.contributor.authorSeyedmohammadi, J
dc.contributor.authorSarmadian, F
dc.contributor.authorJafarzadeh, AA
dc.contributor.authorMcDowell, Richard
dc.date.accessioned2019-10-15T01:15:01Z
dc.date.available2018-11-22
dc.date.issued2018-12-10
dc.date.submitted2018-11-13
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000466609800003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=42fe17854fe8be72a22db98beb5d2208
dc.identifier.issn0365-0340
dc.identifier.otherHW3RG (isidoc)
dc.identifier.urihttps://hdl.handle.net/10182/11008
dc.description.abstractLand suitability assessment can inform decisions on land uses suitable for maximizing crop yield while making best use, but not impairing the ability of natural resources such as soil to support growth. We assessed the suitability of maize to be produce in 12,000 ha land of Dasht-e-Moghan region of Ardabil province, northwest of Iran. Suitability criteria included soil depth, gypsum (%), CaCO₃ (%), pH, electrical conductivity (EC), exchangeable sodium percentage (ESP), slope (%) and climate data. We modified and developed a novel set of techniques to assess suitability: fuzzy set theory, analytic network process (ANP), remote sensing and GIS. A map of suitability was compared a map created using a traditional suitability technique, the square root method. The coefficient of determination between the land suitability index and observed maize yield for square root and ANP-fuzzy methods was 0.747 and 0.919, respectively. Owing to greater flexibility to represent different data sources and derive weightings for meaningful land suitability classes, the ANP-fuzzy method was a superior method to represent land suitability classes than the square root method.
dc.format.extentpp.1063-1079
dc.languageen
dc.language.isoen
dc.publisherTaylor & Francis
dc.relationThe original publication is available from Taylor & Francis - https://doi.org/10.1080/03650340.2018.1549363
dc.relation.urihttps://doi.org/10.1080/03650340.2018.1549363
dc.rights© 2018 Informa UK Limited, trading as Taylor & Francis Group
dc.subjectanalytic network process
dc.subjectfuzzy set theory
dc.subjectGIS
dc.subjectland evaluation
dc.subjectremote sensing
dc.titleIntegration of ANP and Fuzzy set techniques for land suitability assessment based on remote sensing and GIS for irrigated maize cultivation
dc.typeJournal Article
lu.contributor.unitLincoln University
lu.contributor.unitFaculty of Agriculture and Life Sciences
lu.contributor.unitDepartment of Soil and Physical Sciences
dc.identifier.doi10.1080/03650340.2018.1549363
dc.relation.isPartOfArchives of Agronomy and Soil Science
pubs.issue8
pubs.notesAccepted author version posted online 22 Nov 2018 Published online 10 Dec 2018
pubs.organisational-group|LU
pubs.organisational-group|LU|Agriculture and Life Sciences
pubs.organisational-group|LU|Agriculture and Life Sciences|SOILS
pubs.organisational-group|LU|Research Management Office
pubs.organisational-group|LU|Research Management Office|QE18
pubs.publication-statusPublished
pubs.volume65
dc.identifier.eissn1476-3567
lu.identifier.orcid0000-0003-3911-4825


Files in this item

Default Thumbnail

This item appears in the following Collection(s)

Show simple item record