Big Earth observation for geomorphic mapping and monitoring

Geomorphic analysis is essential for understanding landscape dynamics. Remote sensing and Earth observation (EO) data play key roles in monitoring geomorphic changes and natural hazards. EO data cubes (EODCs) enable the efficient storage, organisation, and analysis of these data. Advanced image analysis techniques combined with artificial intelligence methods allow the extraction of multitemporal vector features. These features can be organised into vector data cubes for spatio- temporal analysis, enhancing accuracy assessments and uncertainty analysis. MorphEO aims to investigate, adapt, and integrate raster and vector data cubes for spatio-temporal mapping and monitoring of geomorphic features to better understand how landscapes change over time. In doing so, we aim to improve the analysis of spatial and temporal relationships in geomorphic dynamics. The project focuses on distinct study areas (Iceland, New Zealand, Taiwan, and Ecuador) and various geomorphic features (water- and volcanic-related and erosion features). These regions are characterised by highly dynamic landscapes and frequent changes driven by geomorphic processes and natural hazards. We apply remote sensing, image processing, spatial and time series analysis, and advanced visualisation methods to study the evolution of dynamic geomorphic features. We use optical and radar satellite imagery, aerial photography, and topographic data as primary data sources. Cutting- edge image analysis technology and artificial intelligence will be used to detect and map geomorphic features and enhance geomorphic inventories. Validation and uncertainty quantification will include field verification, expert feedback collection, and comparisons with manual delineations. This project enhances our ability to monitor and understand changes in the Earths surface, thereby supporting disaster management. It also contributes to a better understanding of cascading hazards and their interactions.