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

Abstract

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