Derya ÖZTÜRK

22023

Samsun-Atakum’da Kentsel Geçirimsiz Yüzey Alanlarının Sentinel-2 Uydu Görüntülerinden Spektral İndeksler Kullanılarak Belirlenmesi

Günümüzde hızlı kentleşmeyle birlikte geçirimsiz yüzeyler hızla artmakta ve çeşitli çevresel ve ekolojik sorunlara neden olmaktadır. Bu nedenle geçirimsiz yüzeylerin uzaktan algılama gibi etkin yöntemlerle takibi önem kazanmaktadır. Bu çalışmada yüksek kentleşme oranına sahip Samsun-Atakum ilçesinde 07.07.2022 tarihli Sentinel-2 uydu görüntüsünden UI, NDBI, IBI, CBCI ve NISI indeksleri kullanılarak Coğrafi Bilgi Sistemleri (CBS) ortamında geçirimsiz yüzey alanları çıkarılmış, indekslerin performansı spektral ayrım indeksi ve hata matrisi yaklaşımı ile değerlendirilmiştir. Analizlerin sonucunda çalışma alanında en başarılı indeksin NISI olduğu belirlenmiştir. NISI indeksi 1,3605 spektral ayrım indeksi, % 89,20 genel doğruluk ve 0,7850 kappa değeriyle yüksek performans göstermiş, hem binaların hem de yolların çıkarımında başarılı olmuştur. NISI indeksi sonuçlarına göre çalışma alanında incelenen 30 mahallenin 5’inde geçirimsiz yüzey alanlarının %40’ın üzerinde ve 2’sinde % 30–40 arasında olduğu belirlenmiştir. Çalışmadan elde edilen sonuçlar Sentinel-2 uydu görüntülerinin geçirimsiz yüzey çıkarımında önemli bir potansiyel taşıdığını ve farklı indekslerin karşılaştırılması sonucunda belirlenen optimum indeksin kullanılmasıyla geçirimsiz yüzey çıkarım başarısının artırılabileceğini ortaya çıkarmıştır.
Anahtar Kelimeler:

Kentleşme, Geçirimsiz yüzey indeksi, Uzaktan algılama, Sentinel-2, Atakum

Extraction of Urban Impervious Surface Areas in Samsun-Atakum Using Spectral Indices from Sentinel-2 Satellite Images

Impervious surfaces are increasing rapidly and causing many environmental and ecological problems because of rapid urbanization. It is important to monitor impervious surfaces through effective methods, such as remote sensing. In this study, impervious surface areas were extracted from the Sentinel-2 satellite image (July 7, 2022) in Samsun-Atakum district using UI, NDBI, IBI, CBCI, and NISI indices in the GIS environment and the indices performances were compared using the spectral discrimination index and error matrix approach. NISI was the most accurate index with a spectral discrimination index of 1.3605, an overall accuracy of 89.20%, and a kappa value of 0.7850. According to NISI, the impervious surface areas were over 40% in 5 of the 30 neighborhoods and between 30–40% in 2 neighborhoods. The results showed that Sentinel-2 satellite images have considerable potential in the extraction of impervious surfaces, and the success of impervious surface extraction can be increased by using the optimum index determined by comparing different indices.
Keywords:

Urbanization, Impervious surface index, Remote sensing, Sentinel-2, Atakum,

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Coğrafi Bilimler Dergisi-Cover
  • ISSN: 1303-5851
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 2003
  • Yayıncı: Ankara Üniversitesi Türkiye Coğrafyası Araştırma ve Uygulama Merkezi
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