The performance analyses of support vector machine classifiers for examination of the temporal change of land-use/cover in the Beyşehir Basin in Turkey (1984-2018)

Yıl 2021, Cilt: 8 Sayı: 1, 57 - 71, 01.05.2021

Münevver Gizem Gümüş , S. Savaş Durduran

https://doi.org/10.9733/JGG.2021R0005.E

Öz

This study aimed to investigate the temporal change in land-use/cover in the Beyşehir-Kaşaklı Subbasin, which is one of the nine subbasins of the Konya Closed Basin and known as the largest closed basin in Turkey, using Remote Sensing and Geographic Information Systems techniques. For this purpose, in the study, Landsat Thematic Mapper, Enhanced Thematic Mapper, and Operational Land Imager digital satellite images obtained in the years 1984, 1990, 1996, 2000, 2006, 2012, and 2018 were used. The Support Vector Machines (SVM) method was applied as the classification method. In order to apply the SVM method, firstly, the kernel function and parameter set, giving the highest accuracy in the classification, were selected. In the study, four different kernel functions and different parameter sets were experienced as different from each other. Seventy-two different models in total were applied using different combinations of parameters. As a result of the trials of seventy-two different parameters, it was concluded that the method and algorithm giving the most accurate result with 83.81% classification accuracy and 0.7949 Kappa statistics were the polynomial function of SVMs. As a result of the classification process examined the period between 1984 and 2018 using the determined algorithm and parameters, it was detected that artificial surfaces increased by 418%, arable agricultural lands and pastures decreased by 14%, forests and semi-natural areas increased by 4%, and coastal wetlands on the coasts increased by 6%. On the other hand, the surface area of the water bodies in the region, which demonstrated a decreasing trend until the year 2003, was determined to increase by 3% with the establishment of Suğla Storage in 2003.

Anahtar Kelimeler

Beyşehir lake, Geographic information systems, Landsat, Support vector machines, Sustainable land management, Remote sensing

Destekleyen Kurum

Necmettin Erbakan Üniversitesi Bilimsel Araştırma Projeleri Birimi

Proje Numarası

191419002

Teşekkür

This study is derived from the ongoing thesis titled "Investigation of Sustainable Land Management in Beyşehir-Kaşaklı Sub-Basin Using Geographic Information Systems and Remote Sensing Techniques".This work was supported by Necmettin Erbakan University Scientific Research Projects Unit with the Project Code 191419002.

Türkiye'deki Beyşehir havzasında arazi kullanım/örtüsündeki zamansal değişimin incelenmesi için destek vektör makine sınıflandırıcılarının performans analizleri (1984-2018)

Öz

Bu çalışmada, Türkiye’nin en büyük kapalı havzası olarak bilinen Konya Kapalı Havzası’nın dokuz alt havzasından biri olan Beyşehir-Kaşaklı Alt Havzası’nda meydana gelen arazi kullanımındaki/örtüsündeki zamansal değişikliklerin Uzaktan Algılama teknikleriyle incelenmesi amaçlanmıştır. Bu amaçla çalışmada 1984, 1990, 1996, 2000, 2006, 2012 ve 2018 yıllarında elde edilen Landsat Thematic Mapper, Enhanced Thematic Mapper ve Operational Land Imager dijital uydu görüntüleri kullanılmıştır. Çalışmada piksel tabanlı sınıflandırmalar arasından Destek Vektör Makineleri (DVM) yöntemi uygulanmıştır. DVM yönteminin uygulanması için öncelikle sınıflandırmada en yüksek doğruluğu veren kernel fonksiyon ve parametre seti seçimi yapılmıştır. Çalışmada birbirinden farklı olarak 4 farklı kernel fonksiyon ve farklı parametre setleri denenmiştir. Farklı parametre kombinasyonları kullanılarak toplamda 72 farklı model uygulanmıştır. Belirlenen modeller ile algoritma, kernel fonksiyon ve bu kernele ait parametre seçiminin sınıflandırma doğruluğuna etkisi irdelenmiştir. 72 ayrı parametrenin denemesi sonucunda %83.81 sınıflandırma doğruluğu, 0.7949 Kappa istatistiği ile en doğru sonucu veren yöntem ve algoritmanın DVM’ lere ait polinomal fonksiyon olduğu sonucuna varılmıştır. Belirlenen algoritma ve parametreler kullanılarak 1984 ve 2018 yılları arası irdelenen sınıflandırma işleminin sonucunda yapay yüzeylerin %418 arttığı, ekilebilir tarım alanlarının ve meraların %14 azaldığı, orman ve yarı doğal alanların %4 arttığı, kıyılarda bulunan kıyısal sulak alanların %6 oranında arttığı ve bölgedeki su yapısının ise 2003 yılına kadar azalan bir trend gösterirken 2003 yılında kurulan Suğla Depolaması ile birlikte su yapısının yüzey alanının %3 arttığı tespit edilmiştir.

Anahtar Kelimeler

Beyşehir gölü, Coğrafi bilgi sistemleri, Landsat, Destek vektör makineleri, Sürdürülebilir arazi yönetimi, Uzaktan algılama

Proje Numarası

191419002

Kaynakça

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