A workflow to identify and monitor slow-moving landslides through spaceborne optical feature tracking

Abstract. Identifying and monitoring unstable slopes is essential for preventing both direct and cascading disasters triggered by landslides. To this end, we introduce TerraTrack, an open-source, cloud-based, end-to-end optical feature tracking tool for slow-moving landslide detection and monitoring. The tool is designed to run on the Sentinel-2 Level 1 harmonized collection. Users can define the area of interest, automatically download and pre-process Sentinel-2 data, and compute displacements using different feature tracking techniques. Outputs include a landslide binary mask, velocity maps and time series. The tool can operate entirely in the Google Colaboratory cloud environment. Hence, it removes the need for local computational resources and for a fast internet connection, avoids software conflicts, and is accessible even to those with limited experience in Python programming. We validated the workflow on cases with independent displacement measurements, including the Slumgullion, Chaos Canyon, and Tessina-Lamosano landslides, showing that its results are consistent with independent estimates. Owing to its ease of use and versatility, the tool is a valuable resource for the multi-hazard and landslide communities, complementing InSAR for monitoring surface motion in space and time. The tool can estimate motion shortly after the satellite imagery is acquired, making it an asset for early warning systems that rely on time of failure estimates (i.e., inverse velocity) or predictive modelling of future motion, within the limitations of satellite-based approaches. Lastly, its capacity to identify unstable slopes can guide targeted, detailed investigations into landslide dynamics, enhancing situational awareness and supporting risk mitigation at scale.