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Dynamic Landslide Failure Prediction Model Using Remote Sensing Data

Authors: Biescas, E.; Mudd, S.M.; Cooksley, G.; Ruiz Sánchez-Oro, M.; Goodwin, G.; Gailleton, B.;

Dynamic Landslide Failure Prediction Model Using Remote Sensing Data

Abstract

Telespazio VEGA UK Ltd and the University of Edinburgh are developing an operational methodology for determining the probability of slope failure (as 'factor of safety') from rain events by developing a remotely sensed, rainfall driven landslide model approach to slope failure management. The goal is to develop a technical system designed to progress the current science of predicting rain-induced natural slope failure. It creates a Digital Twin of a physical environment utilising Earth Observation datasets, on which various rainfall scenarios can be run to simulate the landscape behaviour. The Geo Information business unit of Telespazio VEGA UK is leading the development. The University of Edinburgh and specifically its School of Science has adapted the landslide model for remote sensing data ingestion and has been in charge of performance and testing. The method is being applied to railway network landslide risk and rail network operators have shown interest in further development.

This work has also been partially funded by ESA GSTP programme in the project Developing Critical Infrastructure Resilience.

Keywords

landslides, remote sensing, earth observation, DInSAR

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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