Abstract

Construction of scaled-down landslide models is an important means for landslide study. The objective of this study is to develop an innovative non-contact photogrammetric system to meet the challenge for monitoring the fast surface deformation of a laboratory-simulated landslide, which can detect pre-failure events and the final failure, provide sectional and overall surface deformation patterns, and generate speed maps during the rapid slope failure. We proposed an event detector based on altered surface features in the slower slrc (single-lens-reflex camera) image sequence to detect pre-failure events, while a combined analysis tool used the surface velocity fields and deformation areas based on fast hscs (high-speed stereocamera system) stereo image sequences to reveal fast-changing landslide behavior during the short final failure. The introduced surface change detector uses the percentage of sliding block areas, percentage of changed features, and average speeds. It successfully detected four pre-failure local collapse events and the final slope failure; the extent of surface changes reached its maximum to accumulate energy 1.5seconds before the failure when the average speed of changed features achieved its peak of 0.8m/s. The developed system achieved a position accuracy of 3.8mm and a speed accuracy of 0.11m/s. The analysis result demonstrated a time period of 66minutes before the failure which is confirmed by significant signals from both imaging and contact sensors and is important for landslide early warning. A field implementation scheme in western China will be designed and realized in the near future.

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