Combining radar and optical satellite data to gather a comprehensive regional-scale dataset of the activity of slow-moving landslides in diverse tropical landscapes

Slow-moving landslides (SML; mm year−1 to 100 m year−1) can be a ubiquitous geomorphic process in tropical mountain landscapes. Yet, answer to crucial questions such as what landscape characteristics exert the most important control on their spatial distribution (e.g., slope, connection to rivers, climate, lithology, tectonic setting, recent deforestation, degree of anthropogenic activity, etc.), or how does their dynamic behaviour responds to landscape changes (urbanisation, deforestation, etc.), remains elusive – and is typically relying on information collected on single or a few landslide(s). Intrinsically complex, obtaining large-scale datasets with dense surface displacement measurements is even more so in the tropics, where field access is typically difficult, and rapid vegetation changes and persistent cloud cover hamper the use of satellite remote sensing. In this work, we attempt to overcome these limitations by exploiting synergies between spaceborne sensors (i.e., radar and optical) and deformation measurement techniques (i.e., interferometry and sub-pixel image correlation), to obtain multi-year datasets of the activity of SML in the western branch of the East African Rift (wEAR). Characterised by a large natural landscape and climatic diversity, the wEAR is exemplative of many tropical mountain regions, i.e., i) affected by large-scale land use changes and ii) disproportionately high landslide impacts and iii) largely overlooked in landslide research.  We collected a spatio-temporal inventory containing characterised by varying level of activity and behaviours, and located in contrasting environments. This regional-scale dataset will form the foundation for untangling the intricate influences of climate, lithology, tectonics and man-made environmental changes on the occurrence and activity of SML. By investigating their interaction with river system, we also aim at estimating how they contribute to controls on river sediment budgets, regional erosion rates, channel network evolution and flooding patterns – key for our understanding of landscape evolution, sediment budgets and geo-hydrological hazards. Overall, this work aims at moving forward our understanding of a key geomorphic process in severely under-researched types of environments subject to rapid changes. This is not only essential for a better hazard assessment, but also for comprehending how (human-induced and/or natural) environmental changes affect these landscapes and the sediment dynamics.