Satellite Imagery in Hydraulic Research

This study, conducted in the framework of the Future Lab Water project funded by the Federal State of Lower Saxony, Germany, explores the potential of satellite imagery in hydraulic research, focusing on floodplain vegetation roughness.A Machine Learning (ML) framework will be developed to derive accurate estimates of vegetation parameters, such as Leaf Area Index (LAI) and vegetation height, from Moderate-resolution Imaging Spectroradiometer (MODIS) and ICESat-2 via high resolution Sentinel data.These parameters will be used to calculate vegetation roughness maps through formulas developed for flexible, foliated vegetation, enhancing