Land Use Detection of Kara Menderes Basin (ÇANAKKALE-TURKEY) With Remote Sensing

Abstract Recently, there have been many studies on the detection and protection of natural sources. In this respect, especially the detection of land use deserves great importance. Remote sensing facilitates such detections. This is not limited to current land use, but also the change of the land use in time. Due to these facilitations, remote sensing data and methods are becoming more common in Turkey as it is in the world. In this study, it is aimed to explore the land use utilizing the case of Kara Menderes Basin. As the data, the SPOT 5 satellite data images, which have high resolutions and belong to the date of May 10 2010, are used. The classification is achieved using maximum likelihood algorithms in the scope of supervised classification method. In this study, nine different land use types are detected. The distribution of these classifications are displayed in the headings of “Settlement roads, stone mine”, “forest”, “scrub”, “Grassland and pasture”, “dry agriculture”, “irrigated agriculture”, “Fruit and vineyard”, “water surfaces ”, and the like. According to the results of the classification, the largest land use has been detected as forests with 55.7 percent. Accuracy assessments of the classification results were done according to the “random sampling algorithms” and “the ground truth” methods that were highly used in the land studies literature. Accuracy assessment results are found to be 90.60 percent for random sampling algorithms and 90.34 percent fort he ground truth data. Key words: Kara Menderes Basin (Çanakkale), remote sensing, image processing, land use classification