Internet-of-Things-Based Geotechnical Monitoring Boosted by Satellite InSAR Data

Landslides, often a side effect of mining activities, pose a significant risk to humans and infrastructures such as urban areas, power lines, and dams. Operational ground motion monitoring can help detect the spatial pattern of surface changes and their evolution over time. In this technical note, a commercial, cost-effective method combining a network of geotechnical surface sensors with the InSAR data was reported for the first time to accurately monitor surface displacement. The correlation of both data sets is demonstrated in the Gediminas Castle testbed, where slope failure events were detected. Two specific events were analyzed, and possible causes proposed. The combination of techniques allows one to detect the precursors of the events and characterize the consequences of the failures in different areas in proximity to the castle walls, since the solution allows for the confirmation of long-term drifts and sudden movements in real time. The data from the in situ sensors were also used to refine the satellite data analysis. The results demonstrate that not all events pose a direct threat to the safety of the structure monitored.

Automated summary

Landslides, often a result of mining activities, pose significant risks to humans and infrastructure. A commercial method combining a network of geotechnical surface sensors with InSAR data has been reported for accurate surface displacement monitoring. This combined technique allows for the detection of event precursors and characterization of failure consequences.