New Products for Near Real-Time Enhanced Landslide Identification and Precipitation Monitoring

Thursday, 17 December 2015: 16:30
309 (Moscone South)
Justin Roberts-Pierel, Joint Center for Earth Systems Technology, Baltimore, MD, United States, Aakash Ahamed, Boston College, Earth and Environmental Sciences, Chestnut Hill, MA, United States, Jessica Fayne, University of South Carolina Columbia, Columbia, SC, United States and Amanda Rumsey, SSAI/NASA DEVELOP, Greenbelt, MD, United States
Nepal and the Himalayan region are hotspots for landslide activity due to mountainous topography, complex terrain, and monsoon rains. Current research in landslide modeling and detection generally requires high resolution imagery with software aided classification or manual digitization by analysts. These methods are plagued by low spatial and temporal accuracy. Addressing issues in conventional measurement, this study combined optical data from Landsat 8, a Digital Elevation Model (DEM) generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and precipitation data from the Global Precipitation Measurement Mission (GPM) to create two products. The Sudden Landslide Identification Product (SLIP) uses Landsat 8 and the ASTER DEM to identify landslides in near real-time, and provides damage assessments by mapping landslides triggered by precipitation. Detecting Real-time Increased Precipitation (DRIP) monitors precipitation levels extracted from the GPM-IMERG 30-minute product to create alerts in near real-time when current rainfall levels exceed regional threshold values. After a landslide detection is made by SLIP, historical rainfall data from DRIP is analyzed to estimate a date for the detected landslide. Together, DRIP and SLIP will be used by local and regional organizations in Nepal such as the International Centre for Integrated Mountain Development (ICIMOD), as well as the international scientific community to protect lives, preserve infrastructure, and manage local ecosystems.