Cumhuriyet Science Journal

Abstract

Water resources management is
one of the most important issues of today. Satellite remote sensing have 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-based image analysis
(GEOBIA) and (4) NDWI supported GEOBIA (GEOBIA_NDWI) were examined for water
body area detection. For this purpose, Atikhisar Dam Lake, the only water
source of Çanakkale central district of Turkey was selected as study area. As
remote sensing data nine multitemporal Landsat-8 Operational Land Imager (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 main issues discussed in this
study can be specified as follows: (i) Is pixel-based classification SVM or
object-based image classification GEOBIA more successful in the water body
detection?, (ii) Are the image classification methods (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 body detection? 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 detection of the
lake boundary. Additionally, NDWI made a better separation of the land cover
classes adjacent to water at the border. The object based GEOBIA was better
than the pixel based SVM for distinguishing water and other land cover classes
adjacent to border. GEOBIA_NDWI lake area results were more accurate than the
standard object-based classification. Mixed pixels out of the lake area was
determined less in the NDWI and GEOBIA_NDWI results.