Recent developments in the fields of geographical object-based image analysis (GEOBIA) and ensemble learning (EL) have led the way to the development of automated processing frameworks suitable to tackle large-scale problems. Mapping riverscape units has been recognized in fluvial remote sensing as an important concern for understanding the macrodynamics of a river system and, if applied at large scales, it can be a powerful tool for monitoring purposes. In this study, the potentiality of GEOBIA and EL algorithms were tested for the mapping of key riverscape units along the main European river network. The Copernicus VHR Image Mosaic and the EU Digital Elevation Model (EU-DEM)—both made available through the Copernicus Land Monitoring Service—were integrated within a hierarchical object-based architecture. In a first step, the most well-known EL techniques (bagging, boosting and voting) were tested for the automatic classification of water, sediment bars, riparian vegetation and other floodplain units. Random forest was found to be the best-to-use classifier, and therefore was used in a second phase to classify the entire object-based river network. Finally, an independent validation was performed taking into consideration the polygon area within the accuracy assessment, hence improving the efficiency of the classification accuracy of the GEOBIA-derived map, both globally and by geographical zone. As a result, we automatically processed almost 2 million square kilometers at a spatial resolution of 2.5 meters, producing a riverscape-units map with a global overall accuracy of 0.915, and with per-class F1 accuracies in the range 0.79–0.97. The obtained results may allow for future studies aimed at quantitative, objective and continuous monitoring of river evolutions and fluvial geomorphological processes at the scale of Europe.

The Balkan region has some of the best conserved rivers in Europe, but is also the location of ~3,000 planned hydropower dams that are expected to help decarbonise energy production. A conflict between policies that promote renewable hydropower and those that prioritise river conservation has ensued, which can only be resolved with the help of reliable information. Using ground-truthed barrier data, we analysed the extent of current river fragmentation on the longitudinal dimension in the Balkan region and simulated nine dam construction scenarios that varied depending on the number, location and size of the planned dams. Balkan rivers are currently fragmented by 83,017 barriers and have an average barrier density of 0.33 barriers/km after correcting for barrier underreporting; this is 2.2 times lower than the mean barrier density found across Europe and serves to highlight the relatively unfragmented nature of these rivers. However, our analysis shows that all simulated dam construction scenarios would result in a significant loss of connectivity compared to existing conditions. The largest loss of connectivity (-47%), measured as reduction in barrier-free length, would occur if all planned dams were built, 20% of which would impact on protected areas. The smallest loss of connectivity (-8%) would result if only large dams (>10 MW) were built. In contrast, building only small dams (<10 MW) would cause a 45% loss of connectivity while only contributing 32% to future hydropower capacity. Hence, the construction of many small hydropower plants will cause a disproportionately large increase in fragmentation that will not be accompanied by a corresponding increase in hydropower. At present, hydropower development in the Balkan rivers does not require Strategic Environmental Assessment, and does not consider cumulative impacts. We encourage planners and policy makers to explicitly consider trade-offs between gains in hydropower and losses in river connectivity.