Integrated monitoring of urban landslide hazards using geophysics, remote sensing, and wireless sensor networks

Growing urbanization is pushing communities further into areas of known landslide hazard, elevating the risk posed to these communities. Hence, there is an increasing need to develop approaches that can characterize and monitor landslide hazards in urban areas. Here, we present recent developments in the rapid characterization of the landslide hazard using geophysics and remote sensing. We use this approach to parametrize hydromechanical models to assess the probability of failure across a site in the highly populated Berkeley Hills, California. The results highlight various areas of elevated landslide hazard. Focusing on one such area, we used geophysical monitoring data to link changes in subsurface properties with slope instabilities and found that rainfall-induced increases in pore pressure drive slope deformation. Changes in seismic properties occurred up to 5h before actual soil displacements commenced. To monitor the hazard across the entire study site and to further increase our understanding of their triggering factors, we developed and installed a dense wireless network of deformation, soil moisture, and pore pressure sensors. Using machine learning, we use this data to predict subsurface conditions critical to slope failure. The data obtained from these studies is starting to be used for site management and operations.

Uhlemann (2023) Integrated monitoring of urban landslide hazards using geophysics, remote sensing, and wireless sensor networks, USGS Landslide Hazards Seminar, 08 February 2023