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dc.contributor.authorRahdari, Vahiden_US
dc.contributor.authorSoffianian, Alirezaen_US
dc.contributor.authorPourmanafi, Saeiden_US
dc.contributor.authorMosadeghi, Raziehen_US
dc.contributor.authorMohammadi, Ghaiumien_US
dc.date.accessioned2019-06-06T01:40:53Z
dc.date.available2019-06-06T01:40:53Z
dc.date.issued2018en_US
dc.identifier.issn0354-8724en_US
dc.identifier.doi10.5937/22-16620en_US
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.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherUniverzitet u Novom Sadu * Prirodno-Matematicki Fakulteten_US
dc.publisher.placeSerbiaen_US
dc.relation.ispartofpagefrom30en_US
dc.relation.ispartofpageto39en_US
dc.relation.ispartofissue1en_US
dc.relation.ispartofjournalInternational Scientific Journal Geographica Pannonicaen_US
dc.relation.ispartofvolume22en_US
dc.subject.fieldofresearchEnvironmental Sciences not elsewhere classifieden_US
dc.subject.fieldofresearchcode059999en_US
dc.titleA hierarchical approach of hybrid image classification for land use and land cover mappingen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dc.type.codeC - Journal Articlesen_US
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/en_US
dc.description.versionPublisheden_US
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.en_US
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