A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)

Abstract

Abstract Lake Urmia is one of the largest saline lakes in the world, and has a great effect on its surrounding ecosystems as well as the economic, social, and even cultural condition of its basin inhabitants. Hence, continuous monitoring of lake area changes is necessary and unavoidable for better land management and prevention of its degradation. In this study, by using Landsat 8 images and by preforming some essential pre-processing tasks, the area of the lake was estimated using the number of traditional spectral indices and a new one and the automatic Otsu's thresholding method for 5 years (2013–2017). The results showed that this index shows more accurate results than other indices when estimating the area of the lake and can separate water class from land one with an average overall accuracy of 96%.