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Evaluation of Landscape Change Using Remote Sensing: A Case Study of Burdur Lake Basin

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  • Ahmet Benliay

    (Akdeniz University, Faculty of Architecture, Department of Landscape Architecture, Turkey)

Abstract

Georeferenced satellite images can be used for acquisition of topographic information, navigation and visualisation for various environmental studies. The objectives of this study were to determine land use and land cover changes and describe local landscape characteristics in the Burdur Lake Basin. Analyses were carried out using remotely sensed data. The topography of the land has been determined using GlobalDEM data of ASTER satellite with a resolution of 15 m. With this data, ArcMap 10.3 ArcHydro plugin was used to identify the basin of Burdur Lake and it was accepted as the boundary of the study. LT51790341987245 (02 August 1987) and LT51790342011254 (11 August 2011) coded Landsat TM satellite images have been used in the study. For the orthorectification, a digital elevation model (DEM) with an RMS accuracy of ca. 3.5 m, and for classifications 100 selected ground control points (GCPs) measured with differential GPS were used. Land uses identified with classified satellite images are analyzed in a spatial and proportional manner in a total study area of 3.361,56 km2. The changes in land cover are compared with each other and have been evaluated in terms of landscape change. Population growth, rising water consumption for agricultural and domestic purposes and building dams has led to water surfaces declining from 208,71 km2 to 155,42 km2. Also analyses show that the landscape had been dominated by a mixture of urban and cultivated land, and became more homogenous and aggregated in in 24 years.

Suggested Citation

  • Ahmet Benliay, 2017. "Evaluation of Landscape Change Using Remote Sensing: A Case Study of Burdur Lake Basin," European Journal of Multidisciplinary Studies Articles, Revistia Research and Publishing, vol. 2, September.
    • Handle: RePEc:eur:ejmsjr:256
    DOI: 10.26417/ejms.v6i1.p31-36
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