Larkin, H, Magnall, N, Thomas, A, Holley, R & McCormack, H 2020, 'Utilising satellite-based techniques to identify and monitor slope
instabilities: the Fagraskógarfjall and Limnes landslides', in PM Dight (ed.), Proceedings of the 2020 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering
, Australian Centre for Geomechanics, Perth, pp. 1455-1466, https://doi.org/10.36487/ACG_repo/2025_100
Slope instabilities can be highly disruptive, leading to damage to infrastructure, halting of mine operations, and, in the worst cases, loss of life. Slope instabilities can range in severity from slow-moving landslides (moving at millimetres per year) to catastrophic mass failure events (moving at many metres per second and involving tens of millions of cubic metres of material). Timely identification of the early stages of slope instability, whether in an artificial or a natural slope, is essential to properly mitigate the impacts of such hazards.
Here we demonstrate how satellite remote sensing can be used to identify and monitor unstable slopes. By applying interferometric synthetic aperture radar (InSAR) processing techniques to open-access Sentinel-1 radar data, we are able to identify and quantify displacement associated with two very different landslides. In the case of the Fagraskógarfjall landslide, Iceland, we are able to monitor a rapidly accelerating slope instability up to the point where mass failure of the slope occurs. For the Limnes landslide, Cyprus, we are able to categorically identify and monitor a slow-moving slope instability that impacted the community living on the slope. Furthermore, we identify clear correlations between meteorological conditions and the rate of
Our results highlight the effectiveness of InSAR and, more broadly, earth observation for monitoring unstable slopes. The increasing proliferation of earth observation missions, and the trend towards open-access data, means that utilising InSAR for slope monitoring is increasingly feasible, and becoming widely adopted.
Keywords: landslide, InSAR, remote sensing, monitoring
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