We analyze a long term monitoring dataset collected for a deep‐seated rockslide (Ruinon, Lombardy, Italy), which activity is documented by ground‐based and remote sensing data since 1997. The monitoring data allowed to set‐up and update the geological model, to identify rockslide complexities (e.g. uncertain geometry, composite failure mechanisms, seasonal behavior) and their impact on the reliability and early warning potential of monitoring data. GB‐InSAR data allowed to identify different behaviors for sectors characterized by outcropping bedrock, thick debris cover, or close to major structures, and to set‐up a “virtual monitoring network” by a posteriori selection of critical locations. Displacement time series extracted from GB‐InSAR provide a large amount of data even in debris covered areas, when ground‐based instrumentation fails. Such spatially‐distributed, improved information, validated by selected ground‐based measurements, allowed to establish new velocity and displacement thresholds for early warning purposes.
Agliardi, F., Crosta, G., Sosio, R., Rivolta, C., Mannucci, G. (2013). In situ and remote long-term real-time monitoring of a large alpine rock slide. In C. Margottini, P. Canuti, K. Sassa (a cura di), Landslide Science and Practice, Volume 2: Early Warning, Instrumentation and Monitoring (pp. 415-422). Springer [10.1007/978-3-642-31445-2-54].
In situ and remote long-term real-time monitoring of a large alpine rock slide
AGLIARDI, FEDERICOPrimo
;CROSTA, GIOVANNISecondo
;SOSIO, ROSANNAUltimo
;
2013
Abstract
We analyze a long term monitoring dataset collected for a deep‐seated rockslide (Ruinon, Lombardy, Italy), which activity is documented by ground‐based and remote sensing data since 1997. The monitoring data allowed to set‐up and update the geological model, to identify rockslide complexities (e.g. uncertain geometry, composite failure mechanisms, seasonal behavior) and their impact on the reliability and early warning potential of monitoring data. GB‐InSAR data allowed to identify different behaviors for sectors characterized by outcropping bedrock, thick debris cover, or close to major structures, and to set‐up a “virtual monitoring network” by a posteriori selection of critical locations. Displacement time series extracted from GB‐InSAR provide a large amount of data even in debris covered areas, when ground‐based instrumentation fails. Such spatially‐distributed, improved information, validated by selected ground‐based measurements, allowed to establish new velocity and displacement thresholds for early warning purposes.
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