Object-based classification of Izmir Metropolitan City by using sentinel-2 images

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  • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar

Özet

This study aims to create Land Cover Land Use (LCLU)map of a part of the Izmir metropolitan city in Turkey, based on an enhanced Urban Atlas nomenclature and object based classification approach. Multi-temporal Sentinel-2 images from different seasons are used and rule-based object oriented classification techniques are applied on the images. Totally 20 LCLU classes are identified in the study area with different accuracy values. Thematic open source data were also integrated into classification to better identify some land use classes and to increase the total classification accuracy. Our results show that 10-m bands of Sentinel-2 images are capable to produce thematically detailed LCLU map with an overall accuracy of 86% and 0.852 Kappa values.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/15040Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1109/rast.2019.8767781Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorOzlem Yilmaz, Elif
dc.contributor.authorVarol, Beril
dc.contributor.authorHale Topaloglu, Raziye
dc.contributor.authorSertel, Elif
dc.contributor.editorMenekay, S.
dc.contributor.editorCetin, O.
dc.contributor.editorAlparslan, O.
dc.date.accessioned2026-10-22T10:23:30.274189268Z
dc.date.available2026-10-22T10:23:30.274189268Z
dc.date.issued2019
dc.description.abstractThis study aims to create Land Cover Land Use (LCLU)map of a part of the Izmir metropolitan city in Turkey, based on an enhanced Urban Atlas nomenclature and object based classification approach. Multi-temporal Sentinel-2 images from different seasons are used and rule-based object oriented classification techniques are applied on the images. Totally 20 LCLU classes are identified in the study area with different accuracy values. Thematic open source data were also integrated into classification to better identify some land use classes and to increase the total classification accuracy. Our results show that 10-m bands of Sentinel-2 images are capable to produce thematically detailed LCLU map with an overall accuracy of 86% and 0.852 Kappa values.
dc.description.sponsorshipIstanbul Technical University Department of Scientific Research Projects
dc.description.sponsorshipTUBA
dc.description.sponsorshipInternational Technological University, ITU, (MGA-2017-40936)
dc.description.sponsorshipTürkiye Bilimler Akademisi
dc.identifier.articlenumber8767781
dc.identifier.doi10.1109/rast.2019.8767781
dc.identifier.endpage412
dc.identifier.isbn978-153869448-0
dc.identifier.scopus2-s2.0-85073894150
dc.identifier.startpage407
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/15040
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.conference9th International Conference on Recent Advances in Space Technologies, RAST 2019
dc.relation.ispartofProceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectLCLU maps
dc.subjectobject based classification
dc.subjectSentinel-2
dc.subjectUrban Atlas
dc.subject.otherImage classification
dc.subject.otherLand use
dc.subject.otherClassification accuracy
dc.subject.otherLand cover land use
dc.subject.otherMetropolitan cities
dc.subject.otherObject oriented classification
dc.subject.otherObject-based classifications
dc.subject.otherOverall accuracies
dc.subject.otherSentinel-2
dc.subject.otherUrban Atlas
dc.subject.otherMaps
dc.titleObject-based classification of Izmir Metropolitan City by using sentinel-2 images
dc.typeConference Object
dspace.entity.typePublication
rdl.citation.openalex9
rdl.citation.scopus6
rdl.conference.date11 June 2019 through 14 June 2019
rdl.conference.placeIstanbul
rdl.oa.statusclosed
rdl.sdgSDG11
rdl.source.indexSCOPUS