GSA Connects 2022 meeting in Denver, Colorado

Paper No. 105-6
Presentation Time: 3:30 PM

DETECTING AND MONITORING LANDSLIDES FROM AIR AND SPACE: RAIN OR SHINE, DAY OR NIGHT


HANDWERGER, Alexander1, FIELDING, Eric2, HUANG, Mong-Han3, AMATYA, Pukar M.4 and BEKAERT, David P.S.2, (1)Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109; Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, 90095, (2)Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, (3)Department of Geology, University of Maryland, College Park, 8000 Regents Dr., College Park, MD 20742-0001, (4)GESTAR II, University of Maryland Baltimore County, Baltimore, 21250; Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, 20771

Detecting and monitoring landslides is critical for emergency response, disaster mitigation, and for generally improving our understanding of landslide processes. Satellite-based synthetic aperture radar (SAR) can be used to detect landslides, often within days after triggering events, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Airborne SAR systems can then be used for targeted data acquisitions in areas with high landslide activity. Here we present our work that utilizes SAR and other remote sensing (e.g., optical images, digital elevation models) data to identify and monitor landslides in California and around the world. We first show how SAR backscatter change can be used to detect areas with high landslide density following catastrophic triggering events (e.g., earthquakes, storms). We then show results from a large scale landslide monitoring campaign in California that uses satellite- and airborne-based interferometric SAR (InSAR) to quantify the response and sensitivity of landslides in response to changes in rainfall. Our findings indicate that despite more than an order of magnitude difference in mean annual rainfall, landslides in both wet and dry regions of California were similarly sensitive to seasonal and multi-year changes in precipitation. Our findings confirm landslide sensitivity to rainfall under diverse hydroclimate conditions and highlight the need to establish a long time series of landslide behaviors that can be used to better predict future landslide activity. Together, our SAR-based remote sensing approaches enable rapid and accurate investigations of landslides that have broad applications.