Abstract
Identifying precursor events that allow the timely forecasting of landslides, thereby enabling risk reduction, is inherently difficult. Here we present a novel, low cost, flow visualization technique using time-lapsed imagery (TLI) that allows real time analysis of slope movement. This approach is applied to the Rest and Be Thankful slope, Argyle, Scotland, where past debris flows have blocked the A83 or forced preemptive closure. TLI of the Rest and Be Thankful are taken from a fixed station, 28 mm lens, time lapse camera every 15 min. Imagery is filtered to counter the effects of misalignment from wind induced vibration of the camera, asymmetric lighting, and fog. Particle image velocimetry (PIV) algorithms are then run to produce slope movement velocity vectors. PIV generated vectors are automatically post-processed to separate vectors generated by slope movement from false positives generated by harsh environmental conditions. Results for images over a 20-day period indicated precursor slope movement initiated by a rainfall event, a period of quiescence for 10 days, followed by a large landslide failure during proceeding rainfall where over 3000 tons of sediment reached the road. Results suggest low cost, live streamed TLI and this novel PIV approach correctly detect and, importantly, report precursor slope movement, allowing early warning, effective management and landslide impact mitigation. Future applications of this technique will allow the development of an effective decision-making tool for asset management of the A83, reducing the risk to life of motorists. The technique can also be applied to other critical infrastructure sites, allowing hazard risk reduction.
Highlights
Slope failures pose a significant threat to human lives, infrastructure, and accessibility of assets
A real-time landslide monitoring solution has been presented by employing Particle image velocimetry (PIV), a powerful fluid visualization technique that works on the principles of cross-correlation between images
time-lapsed imagery (TLI), which require pre-processing for contrast equalization, intensity thresholding, and image registration to account for low or variable light levels, windy conditions, and raindrops on the camera lens
Summary
Slope failures pose a significant threat to human lives, infrastructure, and accessibility of assets. Spatial and temporal variability in both forcing events such as rainfall delivery and ground saturation levels and in the complex responses of slope materials result in severe challenges to operational management decisions when assets or people are at risk. The initiation and subsequent development of landslides can be considerably removed from identifiable triggering events posing significant challenges to the identification of areas where slopes are undergoing the early stages of deformation and failure. Seismic monitoring systems have proven effective for the development of deep-seated failure processes or the live detection of events, but are limited in the identification and location of precursory movement, which. High resolution terrestrial laser scanning [3]
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