Water Surface

Research on water surfaces focuses on accurately measuring and modeling various aspects of surface water, from the microscopic scale of pesticide delivery on plant leaves to the macroscopic scale of river water elevation and pollutant transport across entire watersheds. Current research employs advanced image processing techniques, including deep learning models like convolutional neural networks, to analyze data from sources such as UAV photogrammetry and video footage, improving the accuracy and automation of water surface measurements. These advancements are crucial for applications ranging from precision agriculture to improved flood prediction and pollution monitoring, ultimately enhancing our understanding and management of hydrological systems.