Speaker
Description
River monitoring increasingly relies on hyperspatial imagery capable of resolving geomorphological and ecological features at centimeter scales. Although UAVs and other low-altitude airborne platforms have made such data more accessible, resulting datasets often remain dispersed across individual projects, inconsistently documented, and rarely accompanied by reusable spatial annotations. This limits comparative analysis, reproducibility, and the development of transferable machine-learning methods for river environments. Here, we present RiverTiles, an open-access geospatial platform for the curation, visualization, and dissemination of ultra-high-resolution river imagery and hierarchical geomorphological annotations. RiverTiles combines a lightweight web architecture for interactive exploration of large raster datasets with a GUS-inspired annotation framework organized across macro-units, geomorphic units, and finer structural elements. The platform supports curated community contributions, standardized metadata, and publication of both visualization-ready and analysis-ready assets. RiverTiles brings imagery, terrain products, annotations, provenance information, and archival records into a common geospatial framework, providing shared infrastructure for reproducible river monitoring, geomorphological analysis, and future computer-vision workflows.