Yazar "Ozelkan, Emre" seçeneğine göre listele

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    Comparative assessment of remote sensing-based water dynamic in a dam lake using a combination of Sentinel-2 data and digital elevation model
    (Springer, 2022) Karaman, Muhittin; Ozelkan, Emre
    Monitoring and determining the amount of water in reservoirs is of great importance in terms of water planning and management. This study proposes a geographic information system (GIS)-based methodology to estimate the water volume changes in water reservoirs. Two specific methods are proposed using Australian National University's Digital Elevation Model (ANUDEM) raster surface and Triangulated Irregular Network (TIN) surface models, both utilizing normalized difference water index (NDWI) of Sentinel 2A satellite images for water-covered area and coastline and digital elevation model (DEM) for 3D modelling of the reservoir. The most crucial part of this study is the comprehensive evaluation of the model findings considering hydrological, meteorological and anthropogenic factors, simultaneously. Application of the proposed methods is provided for the analysis of the multi-temporal water volume changes of Bayramic Dam Lake (canakkale, Turkey) in two hydrological periods covering the 2015-2016 and 2016-2017 water years. The results indicate that the TINS model produced water volume values much closer to the in situ Turkish General Directorate of State Hydraulic Works (DSI) values than the ANUDEM model. The performance of these methods was also assessed by the temporal dynamics of surface hydrological processes. Regarding the water storage dynamics, hydro-meteorological factors influence the water input, while anthropogenic factors strongly influence the water output. Water consumption for irrigation and electricity generation was found to be the most important water budget components of the total water consumption.
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    Öğe
    Water Body Detection Analysis Using NDWI Indices Derived from Landsat-8 OLI
    (Hard, 2020) Ozelkan, Emre
    Normalized different water indices (NDWIs) derived from satellite images are commonly and successfully utilized in surface water body detection and mapping. In this study, the water body detection capability of three NDWI models (NDWI(Green, NIR), NDWI(Green, SWIR1) and NDWI(Green, SWIR2)) generated using 28 multitemporal Landsat-8 OLI multispectral satellite images was analyzed for Atikhisar Dam Lake, the only water source of Canakkalecity's central district in Turkey between 2013 and 2017. This study focused on two important open research questions: (i) Which NDWI model produces the most superior results? and (ii) How much does accuracy change in the use of 15 m and 30 m spatial resolution satellite data? For the accuracy analysis, area values extracted from the NDWI models were compared with in-situ lake area values as measured by the General Directorate of State Hydraulic Works (DSI). The results of this study show that as the lake area grows, discrimination of water from other classes is better with NIR region, and that the performance of NDWI(Green, NIR) is relatively better in terms of lake expansion effect. Results also indicate that hydrometeorological factors such as precipitation and evaporation and anthropogenic factors such as irrigation and daily consumption are decisive in lake area variations. The order of accuracy from high to low was found to be NDWI(Green, NIR), NDWI(Green, SWIR1) and NDWI(Green, SWIR2), and 15 m spatial resolution data generated better results than 30 m resolution.