Comparative Evaluation of Various Impervious Surface Indices Using Sentinel-2A MSI and Landsat-9 OLI-2 Images: A case of Samsun

Öz

The world is experiencing rapid urbanization, and many natural areas are transformed into impervious surfaces through urbanization. The increase in impervious surfaces in urban areas leads to the deterioration of the environment and a decrease in natural resources. Therefore, information about impervious surfaces, a primary indicator of urban construction, is needed in studies on urbanization and its environmental effects. Obtaining spatio-temporal urban impervious surface information in an accurate and cost-effective manner is essential for supporting sustainable urban development. Today, impervious surface indices based on remote sensing technology can effectively extract impervious surface areas. However, the difficulty of the impervious surface extraction complicates the selection of the method to get the optimum result. In this study, the performance of six different impervious surface indices, including Urban Index (UI), Normalized Difference Built-up Index (NDBI), Index-based Built-up Index (IBI), Combinational Biophysical Composition Index (CBCI), Enhanced Normalized Difference Impervious Surfaces Index (ENDISI), and Normalized Impervious Surface Index (NISI), were employed to extract impervious surfaces from Sentinel-2A MSI and Landsat-9 OLI-2 images in an area of Samsun, where has high urbanization potential. The results were evaluated by spectral discrimination index and error matrix approach. Additionally, the effects of indices were investigated using visual assessments. The results showed that ENDISI was the best-performing index in both Sentinel-2A MSI and Landsat-9 OLI-2 images in the study area, but Sentinel-2A MSI gave higher accuracy than Landsat-9 OLI-2. In the extraction of impervious surfaces using the ENDISI index, the overall accuracy for Sentinel-2A MSI is 91.53% and the kappa value is 0.8301, while the overall accuracy for Landsat-9 OLI-2 is 78.29% and the kappa value is 0.5646. The study’s results revealed that Sentinel-2 and Landsat-9 satellite images have a significant potential for impervious surface extraction, and the extraction success can be increased with the optimum result to be determined by comparisons based on different satellite images and indices.

Anahtar Kelimeler

• impervious surface index
• Sentinel-2
• Landsat-9
• accuracy
• comparison

Sentinel-2A MSI ve Landsat-9 OLI-2 Görüntüleri Kullanılarak Farklı Geçirimsiz Yüzey İndekslerinin Karşılaştırmalı Değerlendirmesi: Samsun Örneği

Öz

Dünyada hızlı bir kentleşme yaşanmakta ve kentleşme süreciyle birlikte önemli miktarda doğal alan geçirimsiz yüzeylere dönüşmektedir. Kentsel alanlarda geçirimsiz yüzeylerin artması, çevrenin bozulmasına ve doğal kaynakların azalmasına yol açmaktadır. Bu nedenle, kentleşme ve kentleşmenin çevresel etkileriyle ilgili çalışmalarda kentsel yapılaşmanın temel bir göstergesi olan geçirimsiz yüzeylerle ilgili bilgilere gereksinim duyulmaktadır. Kentsel geçirimsiz yüzey bilgilerinin zamanında, maliyet etkin ve doğru bir şekilde elde edilmesi, sürdürülebilir kentsel gelişimin desteklenmesi için büyük önem taşımaktadır. Günümüzde uzaktan algılama teknolojisine dayalı geçirimsiz yüzey indeksleri, geçirimsiz yüzey alanlarının elde edilmesinde etkin olarak kullanılabilmektedir. Ancak geçirimsiz yüzey çıkarımının karmaşıklığı, optimum sonucu elde etmek için yöntem seçimini zorlaştırmaktadır. Bu çalışmada Samsun’da yüksek kentleşme potansiyeli olan bir alanda Sentinel-2A MSI ve Landsat-9 OLI-2 görüntülerinden geçirimsiz yüzey çıkarımında Kent İndeksi (Urban Index-UI), Normalleştirilmiş Fark Yapay Alan İndeksi (Normalized Difference Built-up Index-NDBI), İndeks Tabanlı Yapay Alan İndeksi (Index-based Built-up index-IBI), Kombinasyonel Biyofiziksel Bileşim İndeksi (Combinational Biophysical Composition Index-CBCI), Geliştirilmiş Normalleştirilmiş Fark Geçirimsiz Yüzey İndeksi (Enhanced Normalized Difference Impervious Surfaces Index-ENDISI) ve Normalleştirilmiş Geçirimsiz Yüzey İndeksi (Normalized Impervious Surface Index-NISI) olmak üzere altı farklı geçirimsiz yüzey indeksinin performansı spektral ayrım indeksi ve hata matrisi yaklaşımıyla karşılaştırılmış, ayrıca görsel incelemeler ile indeks etkileri araştırılmıştır. Çalışmanın sonucunda ENDISI’nin hem Sentinel-2A MSI hem de Landsat-9 OLI-2 görüntülerinde en iyi performans gösteren indeks olduğu ancak Sentinel-2A MSI ile Landsat-9 OLI-2’den daha yüksek doğruluk elde edildiği belirlenmiştir. ENDISI indeksiyle geçirimsiz yüzey çıkarımında Sentinel-2A MSI için toplam doğruluk % 91,53 ve kappa değeri 0,8301 iken Landsat-9 OLI-2 için toplam doğruluk % 78,29 ve kappa değeri 0,5646’dır. Çalışmanın sonuçları Sentinel-2 ve Landsat-9 uydu görüntülerinin geçirimsiz yüzey çıkarımında önemli bir potansiyele sahip olduğunu ve farklı uydu görüntüleri ve indekslere dayalı karşılaştırmalarla belirlenen optimum sonuç ile geçirimsiz yüzey çıkarım başarısının artırılabileceğini ortaya koymuştur.

Anahtar Kelimeler

• geçirimsiz yüzey indeksi
• Sentinel-2
• Landsat-9
• doğruluk
• karşılaştırma

Kaynakça

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