Comparison of Remote Sensing Classification Techniques for Water Body Detection: A Case Study in Atikhisar Dam Lake (Çanakkale)

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dc.contributor.authorÖzelkan, Emre
dc.date.accessioned2025-01-27T19:20:47Z
dc.date.available2025-01-27T19:20:47Z
dc.date.issued2019
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractWater resources management is one of the most important issues of today. Satellite remote sensinghave been successfully used to detect the presence of water bodies. In this study, four remote sensing methods:(1) normalized difference water index (NDWI), (2) support vector machine (SVM), (3) geographic object-basedimage analysis (GEOBIA) and (4) NDWI supported GEOBIA (GEOBIA_NDWI) were examined for waterbody area detection. For this purpose, Atikhisar Dam Lake, the only water source of Çanakkale central districtof Turkey was selected as study area. As remote sensing data nine multitemporal Landsat-8 Operational LandImager (OLI) multispectral satellite images between 2013 and 2017 were used. For the accuracy assessment,area values extracted from the used methods were tested with in-situ measurement lake area values. The mainissues discussed in this study can be specified as follows: (i) Is pixel-based classification SVM or object-basedimage classification GEOBIA more successful in the water body detection?, (ii) Are the image classificationmethods (SVM and GEOBIA) or the water index (NDWI) more successful in the water body detection? and(iii) What is the contribution of NDWI to GEOBIA_NDWI (GEOBIA_NDWI) classification in the water bodydetection? The results show that meteorological factors and irrigation were influential in lake area variations.NDWI was found to be superior to other methods in determining water body and allowed for better detectionof the lake boundary. Additionally, NDWI made a better separation of the land cover classes adjacent to waterat the border. The object based GEOBIA was better than the pixel based SVM for distinguishing water andother land cover classes adjacent to border. GEOBIA_NDWI lake area results were more accurate than thestandard object-based classification. Mixed pixels out of the lake area was determined less in the NDWI andGEOBIA_NDWI results.
dc.identifier.doi10.17776/csj.556440
dc.identifier.endpage661
dc.identifier.issn2587-2680
dc.identifier.issn2587-246X
dc.identifier.issue3
dc.identifier.startpage650
dc.identifier.trdizinid320302
dc.identifier.urihttps://doi.org/10.17776/csj.556440
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/320302
dc.identifier.urihttps://hdl.handle.net/20.500.12428/15023
dc.identifier.volume40
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofCumhuriyet Science Journal
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_TRD_20250125
dc.subjectSu Kaynakları
dc.subjectÇevre Bilimleri
dc.titleComparison of Remote Sensing Classification Techniques for Water Body Detection: A Case Study in Atikhisar Dam Lake (Çanakkale)
dc.typeArticle

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