Small dams: determining the minimum waterbody surface area that can be successfully detected using Sentinel-1 SAR imagery

Abstract

Water is a scarce resource in South Africa, and approximately 62% of the water used in South Africa is for irrigation. This water is stored in many small dams scattered across the country. If not managed correctly, they could have a negative effect on catchment areas and on the availability of water. As such, there is a need for a new monitoring and management system to be developed. This study determined the minimum surface area that would be required for a waterbody to be detected on Sentinel-1 Synthetic Aperture Radar imagery. A Random Forest classifier was used to detect waterbodies on a Sentinel-1 image calculated from a time series of imagery taken over a period of three months. Steep incidence angles outperformed shallow incidence angles, with the classification having an overall accuracy of 80%. Detection rates were almost 90% for waterbodies of one hectare and greater, with no false positives, and a 10% false negative rate. These findings provide the foundation for developing a detection and monitoring system, which would allow for the better management of water resources in South Africa.