Mapping Water Bodies and Wetlands from Multispectral and SAR Data for the Cross-Border River Basins of the Polish–Ukrainian Border

Abstract

Using remote sensing data to accurately record water surface changes over large areas is crucial in monitoring water resources. However, mapping water surfaces from remote sensing data has its advantages and disadvantages. This study presents a method for mapping water surfaces and wetlands based on Sentinel-1/-2 data over a study area of more than 26,000 km2 in three river basins, the Bug, Dniester, and San, located along the Polish–Ukrainian border. To achieve this goal, an image processing algorithm with additional options was developed (special filters, type classification, and post-classification), which minimized the shortcomings and increased the accuracy of the method. As a result, by using optical and radar data, it was possible to create maps of water bodies in the study area in the driest month of the year from 2018 to 2021. The results were evaluated numerically and graphically. The accuracy of the method was assessed using the Kappa coefficient. For optical data, the lowest value was 76.28% and the highest was 88.65%; for radar data, these values were 87.61% and 97.18%, respectively. When assessing accuracy, the highest values were achieved for overall accuracy (OA), with a maximum of 0.95 (for SAR) and 0.91 (for optical data). The highest values were in user accuracy (UA), with a maximum value of 1 for both SAR and optical data.

Keywords

• water surface
• remote sensing
• Sentinel-1/-2
• optical data
• SAR data
• Lee filter