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dc.contributor.authorRandari, Vahid
dc.contributor.authorSoffianian, Alireza
dc.contributor.authorPourmanafi, Saeid
dc.contributor.authorMosadeghi, Razieh
dc.contributor.authorMohammadi, Hamid Ghaiumi
dc.date.accessioned2019-06-18T12:31:19Z
dc.date.available2019-06-18T12:31:19Z
dc.date.issued2018
dc.identifier.issn0354-8724
dc.identifier.doi10.5937/22-16620
dc.identifier.urihttp://hdl.handle.net/10072/381214
dc.description.abstractRemote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC) in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherUniverzitet u Novom Sadu * Prirodno-Matematicki Fakultet
dc.publisher.placeSerbia
dc.relation.ispartofpagefrom30
dc.relation.ispartofpageto39
dc.relation.ispartofissue1
dc.relation.ispartofjournalInternational Scientific Journal Geographica Pannonica
dc.relation.ispartofvolume22
dc.subject.fieldofresearchEnvironmental Sciences not elsewhere classified
dc.subject.fieldofresearchcode059999
dc.titleA hierarchical approach of hybrid image classification for land use and land cover mapping
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.description.versionPublished
gro.rights.copyright© The Author(s) 2018. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorMosadeghi, Razi


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