Detecting Water Surface Borders on Satellite Images

In the process of climate change, methods used for environmental monitoring are becoming more and more necessary. Changes in water surfaces can be used as an indicator of these changes, including drought and flood. In this paper, methods for detecting water surface borders on satellite images using manual and automatic approaches were investigated. The approaches were tested on true color images and Normalized Difference Water Index (NDWI) images with enhanced water surfaces. The manual algorithm (MSDA) marks pixel values within a specified tolerance from the initial pixel. Additionally, two automatic Shoreline Detection Algorithms (SDA) were developed. The first one, SDA1, is based on the Suzuki algorithm, and the second one, SDA2, is based on the Canny algorithm in combination with the Suzuki algorithm. The results indicate minimal differences between SDA1 and SDA2 in marking water surface borders, with better performance observed with NDWI images compared to true color images. While MSDA is suitable for precise and adjustable marking, it should be noted that manual marking is more time-consuming. The automatic algorithms can be used for analysis of a larger number of satellite images with minimal user input and, as such, give a good overview of possible changes in the water surface borders.