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dc.contributor.authorÇavur, Mahmut
dc.contributor.authorDüzgün, Hafize Şebnem
dc.contributor.authorKemeç, Serkan
dc.contributor.authorDemirkan, Doğa Çağdaş
dc.date.accessioned2020-12-24T12:39:02Z
dc.date.available2020-12-24T12:39:02Z
dc.date.issued2019
dc.identifier.issn1682-1750en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/3652
dc.identifier.urihttps://doi.org/10.5194/isprs-archives-XLII-1-W2-13-2019
dc.description.abstractLand use and land cover (LULC) maps in many areas have been used by companies, government offices, municipalities, and ministries. Accurate classification for LULC using remotely sensed data requires State of Art classification methods. The SNAP free software and ArcGIS Desktop were used for analysis and report. In this study, the optical Sentinel-2 images were used. In order to analyze the data, an object-oriented method was applied: Supported Vector Machines (SVM). An accuracy assessment is also applied to the classified results based on the ground truth points or known reference pixels. The overall classification accuracy of 83,64% with the kappa value of 0.802 was achieved using SVM. The study indicated that of SVM algorithms, the proposed framework on Sentinel-2 imagery results is satisfactory for LULC maps.en_US
dc.description.sponsorshipEuropean Commissionen_US
dc.language.isoengen_US
dc.publisherInternational Society for Photogrammetry and Remote Sensingen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLand use land coveren_US
dc.subjectLULCen_US
dc.subjectSentinel 2A analysisen_US
dc.subjectSVMen_US
dc.titleLand Use And Land Cover Classification Of Sentinel 2-A: St Petersburg Case Studyen_US
dc.typeconferenceObjecten_US
dc.identifier.startpage13en_US
dc.identifier.endpage16en_US
dc.relation.journalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archivesen_US
dc.identifier.issue1/W2en_US
dc.identifier.volume42en_US
dc.departmentFakülteler, İşletme Fakültesi, Yönetim Bilişim Sistemleri Bölümüen_US
dc.identifier.doi10.5194/isprs-archives-XLII-1-W2-13-2019en_US
dc.identifier.scopus2-s2.0-85084985698en_US
dc.institutionauthorÇavur, Mahmuten_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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