Detecting and monitoring slow-moving landslides in the Eastern San Francisco Bay Area using Permanent Scatterer InSAR methods

Synthetic Aperture Radar Interferometry (InSAR) has been used to detect surface displacements with millimeter-level precision. While the spatial and temporal resolution of acquired SAR data is on the order of meters and months, respectively, this resolution is necessarily reduced to moderate noise that is due to, for example, the changing configuration and/or electromagnetic properties of ground targets that scatter the radar signal, atmospheric changes between scenes that lead to signal delays, and digital topography errors. As a result of this reduction in resolution, imaging small features such as individual landslides that often display strongly seasonal deformation has proven difficult. In this contribution, we present the results of Permanent Scatterer InSAR (PS-InSAR) analyses that image the temporal and spatial details of motion of large, slow- moving landslides in the eastern San Francisco Bay Area during the time period spanning 1992-2001. This method identifies objects that show phase-stable, radar-bright behavior in a large number of scenes, and uses only these targets to estimate ground displacements, atmospheric delays, and digital topography errors. By using only this subset of points, the spatial and temporal resolution of the SAR scenes can be maintained under the urban conditions present in the San Francisco Bay Area. Using this dataset, we identify the location and extent of three previously mapped, km-scale slow-moving landslides in the area, and demonstrate that their motion shows a strong seasonality. Using the line-of-sight (LOS) displacements provided by the PS-InSAR data, we estimate that time-averaged displacement rates are between 5-38 mm/yr, depending on the assumed direction of landslide motion. Data collected from a different LOS direction allow us to better resolve the displacement components of landslide motion. During an El Niño season between 1997-1998, precipitation was approximately twice as much as the average during our study period, and this caused LOS displacements to increase to as much as 11 mm/yr. Our results show that PS-InSAR methods can resolve the details of seasonal deformation of km-scale landslides over broad areas and may potentially be used in the future to identify and monitor slow-moving landslides, or detect changes in landslide displacement rates that may precede catastrophic failure.