Application of deep learning in water surface detection for Dong Hoi city using Sentinel-1 images - Nguyen Cam Van (Thuy loi University, 2024)
Efficient water resource management is a critical mandate for governmental authorities, as it directly impacts the effective utilization of this invaluable natural resource. The expeditious and accurate extraction of water surfaces significantly impacts governmental decision-making. Leveraging the advanced capabilities of high-resolution satellite imagery and the precise orbital data return, this study employs state-of-the-art deep learning techniques to enhance the efficiency of water surface detection. Specifically, Sentinel-1 data acquired from Google Earth Engine is utilized as a primary input for proposed machine-learning models. With the satellite images covering the entire of Quang Binh province, the analysis detects 15.96 km of water surfaces along the Nhat Le River and 2.8 km2 surface area of the Phu Vinh reservoir. The evaluation metrics, i.e., Overall Accuracy and Kappa, approach 0.9 approximately, indicate the robustness and potential of the results.