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dc.contributor.authorBayram, Bulent
dc.contributor.authorAvsar, Ozgur
dc.contributor.authorSeker, Dursun Zafer
dc.contributor.authorKayi, Abdullah
dc.contributor.authorErdogan, Mustafa
dc.contributor.authorEker, Oktay
dc.contributor.authorReis, Hatice Catal
dc.date.accessioned2021-11-09T19:50:18Z
dc.date.available2021-11-09T19:50:18Z
dc.date.issued2017
dc.identifier.issn1018-4619
dc.identifier.issn1610-2304
dc.identifier.urihttps://hdl.handle.net/20.500.12440/4234
dc.description18th International Symposium on Environmental Pollution and its Impact on Life in the Mediterranean Region (MESAEP) -- SEP 26-30, 2015 -- Crete, GREECEen_US
dc.description.abstractCoastline changes are increasing rapidly due to both natural and human effects. The expansion of touristic, industrial and culture fishing establishments through coastal areas has brought about uncontrolled and unplanned urbanization. In this study, the coastline in Karasu district of Turkey has been extracted by using Unmanned Aerial Vehicle (UAV) images. For this purpose; 7 cm ground sample distance (GSD) UAV images taken in 2013 by Gatewing-X100 by 40% side and 70% forward overlap was used as post images. Produced ortho images were used as the base map for extraction of the coastline. An object-oriented approach has been applied to capture the shoreline from these ortho images. In the presented study, the eCognition object-oriented fuzzy image processing software has been used. This commercial software has the ability to develop custom tools for image classification in addition to its standard object feature tools. Customized arithmetic features have been used to achieve more accurate shoreline segmentation results. Three main object classes have been created as sea, shoreline buffer and land to extract shoreline. The segmentation results were converted into dxf vector data format. The results were compared with manual digitizing of 55 blind readers. An algorithm has been developed by using Matlab to analyze the differences between object-oriented classification and manual digitizing results. Results were evaluated according to students' gender, age, spent time, used software and courses taken. The root mean square error (RMSE) was calculated as 7.15 m.en_US
dc.language.isoengen_US
dc.publisherParlar Scientific Publications (P S P)en_US
dc.relation.ispartofFresenius Environmental Bulletinen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectObject-orienteden_US
dc.subjectunmanned aerial vehicle (UAV)en_US
dc.subjectshore line extractionen_US
dc.subjectimage processingen_US
dc.titleTHE ROLE OF NATIONAL AND INTERNATIONAL GEOSPATIAL DATA SOURCES IN COASTAL ZONE MANAGEMENTen_US
dc.typeconferenceObjecten_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.description.wospublicationidWOS:000395724000052en_US
dc.departmentGümüşhane Üniversitesien_US
dc.authoridSeker, Dursun Zafer / 0000-0001-7498-1540
dc.authoridERDOGAN, Mustafa / 0000-0003-3219-5546
dc.authoridVarna, Inese / 0000-0002-9050-7803
dc.identifier.volume26en_US
dc.identifier.issue1en_US
dc.identifier.startpage383en_US
dc.identifier.endpage391en_US
dc.authorwosidSeker, Dursun Zafer / ABA-7384-2020
dc.authorwosidERDOGAN, Mustafa / U-1126-2019
dc.authorwosidBayram, Bulent / J-2002-2015
dc.authorwosidVarna, Inese / AAG-1007-2020


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