Nineteen percent of the global population may face a high probability of subsidence

Landslides in reservoir contexts are a well-recognised hazard that may lead to dangerous situations regarding infrastructures and people’s safety. Satellite-based radar interferometry is proving to be a reliable method to monitor the activity of landslides in such contexts. Here, we present a DInSAR (Differential Interferometric Synthetic Aperture Radar) analysis of Sentinel-1 images that exemplifies the usefulness of the technique to recognize and monitor landslides in the Rules Reservoir (Southern Spain). The integration of DInSAR results with a comprehensive geomorphological study allowed us to understand the typology, evolution and triggering factors of three active landslides: Lorenzo-1, Rules Viaduct and El Arrecife. We could distinguish between rotational and translational landslides and, thus, we evaluated the potential hazards related to these typologies, i.e., retrogression (Lorenzo-1 and Rules Viaduct landslides) or catastrophic slope failure (El Arrecife Landslide), respectively. We also observed how changes in the water level of the reservoir influence the landslide’s behaviour. Additionally, we were able to monitor the stability of the Rules Dam as well as detect the deformation of a highway viaduct that crosses a branch of the reservoir. Overall, we consider that other techniques must be applied to continue monitoring the movements, especially in the El Arrecife Landslide, in order to avoid future structural damages and fatalities.

Slope failures occur in open-pit mining areas worldwide producing considerable damage and economic losses. Identifying the triggering factors and detecting unstable slopes and precursory displacements, which can be achieved by exploiting remote sensing data, is critical to reduce their impact. Here we present a methodology that

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This work describes the set of tools developed, tested, and put into production in the context of the H2020 project Multi-scale Observation and Monitoring of Railway Infrastructure Threats (MOMIT). This project, which ended in 2019, aimed to show how the use of various remote sensing techniques could help to improve the monitoring of railway infrastructures, such as tracks or bridges, and thus, consequently, improve the detection of ground instabilities and facilitate their management. Several lines of work were opened by MOMIT, but the authors of this work concentrated their efforts in the design of tools to help the detection and identification of ground movements using synthetic aperture radar interferometry (InSAR) data. The main output of this activity was a set of tools able to detect the areas labelled active deformation areas (ADA), with the highest deformation rates and to connect them to a geological or anthropogenic process. ADAtools is the name given to the aforementioned set of tools. The description of these tools includes the definition of their targets, inputs, and outputs, as well as details on how the correctness of the applications was checked and on the benchmarks showing their performance. The ADAtools include the following applications: ADAfinder, los2hv, ADAclassifier, and THEXfinder. The toolset is targeted at the analysis and interpretation of InSAR results. Ancillary information supports the semi-automatic interpretation and classification process. Two real use-cases illustrating this statement are included at the end of this paper to show the kind of results that may be obtained with the ADAtools.