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SETSCI - Volume (2018)
ISAS 2018 - Ist International Symposium on Innovative Approaches in Scientific Studies, Kemer-Antalya, Turkey, Apr 11, 2018

Determination of Seasonal Coastal Boundary Change of Ağyatan Natural Site Area (ISAS 2018_86)
Sevim Yasemin Çiçekli1, Tolga Kaynak2, Mustafa Hayri Kesikoğlu3*
1Harita Mühendisliği Bölümü, Çukurova Üniversitesi , Adana, Turkey
2Harita Mühendisliği Bölümü, Erciyes Üniversitesi, Kayseri, Turkey
3Harita Mühendisliği Bölümü, Erciyes Üniversitesi , Kayseri, Turkey
* Corresponding author: hayrikesikoglu@erciyes.edu.tr
Published Date: 2018-06-23   |   Page (s): 91-91   |    127     8

ABSTRACT Coastal boundaries are areas that undergo the most change in the world. These changes occur result of natural or human-induced events. Located west of Ceyhan River Ağyatan is a lagoon lake formed in the place where the Ceyhan river which constantly changes bed approaches the sea. This area is a wetland that live sea and land creatures with endemic plants and endangered birds, consisting of forest, sand, reeds and marshes. In the scope of this study, it was aimed to determine the change occurring seasonally in the Ağyatan Lake in 2016. Landsat 8 images belonging to 4 different seasons of 2016 were used to determine these changes. Images were cut according to the work area. It is seen that object-based classification methods give better results than pixel-based classification methods when the made studies are examined. For this reason, the k-nearest neighbour method, which is an object-based classification method, is used in determining the area of the Ağyatan Lake. The study areas are divided into 6 classes: lake, sea, cultivated agricultural land, soil, settlement and water channel. In the result of the classification, thematic maps of 4 images were obtained. Then, change determination analyzes were performed using image differencing method. As a result of the analyzes, in the area of the lake decrease from winter season to the spring, increase from spring to summer and autumn to summer were detected  
KEYWORDS Coastal boundary change, object-based classification, k-nearest neighbour

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