A bird’s-eye view on river floodplains: Mapping and monitoring land cover with remote sensing

Natural lowland rivers are dynamic environments with a high ecological value. However, 90% of the European and North-American river floodplains are in a degraded state. The functions of floodplains are strongly determined by land cover and they often compete for space in narrowed floodplains. Integrated river management (IRM) tries to take care of floodplains in such way that land cover is optimized for multiple functions. For IRM, monitoring is essential to capture the dynamics, to evaluate changes, and to document the state of floodplains over time. The main objective of this thesis was to establish remote-sensing methods for the monitoring of floodplain land cover over multiple spatial and temporal scales. Several remote-sensing based solutions have been developed for the monitoring of land-cover dynamics in river floodplains and tested in floodplains of the lower Rhine. The phenological change of floodplain vegetation over the course of one year was studied using temporal profiles of its height and greenness. Using multitemporal UAV images, vegetation height was determined with an accuracy similar to much more expensive airborne LiDAR data. Multitemporal elevation models yielded meaningful profiles of greenness and vegetation height over time, which enabled discriminating the different land-cover types. The same dataset combined with a powerful machine learning model (Random Forest) yielded unprecedented high classification accuracies for floodplain vegetation (> 90%), even for similar vegetation types such as grassland and herbaceous vegetation. This method is a practical and highly accurate solution for monitoring areas of a few square kilometres. For large-scale monitoring of floodplains, the same method is recommended, but with data from airborne platforms covering larger extents. Land-cover change over the course of five years was studied for a 100-km river section using satellite images. Using an object-based approach, a sequential deviation of a land-c