Lidar availability and application for landslide science Josh Roering, University of Oregon 1) What areas are slide-prone? 2) What does landscape form reveal about landslide style, mechanics, and history? opentopography.org Natl. Center for Airborne Laser Mapping (NCALM)
Lidar availability (public) for landslide science 3D Elevation Program (3DEP): Lidar Acquisition Priorities and Coverage Priority Available/in-progress/planned: High-quality (1m DEM): Available/in-progress/planned: Moderate-quality (>2m DEM): Acquisition and management framework with full coverage goal of high-quality lidar for 2022 (currently <10%) Hazard mitigation ranks high on list of benefits Prioritization and increased data quality depend on needs and partners ifsar (AK) 2014 Lead agency: USGS nationalmap.gov/3dep/
Application 1: Lidar for landslide mapping and inventories Puget Sound, WA Lidar landslide maps: Require trained geoscientists and protocols Increase landslide densities by 3 to 200 times Reveal complex landslide geometries Are often more accurate than field surveys Focus field investigations and analysis of archival photos for historical activity Portland, OR Burns & Madin, 2009; Mackey & Roering, 2011; Guzzetti et al., 2012; Schulz, 2007; van den Eeckhaut, 2012
Application 1: Lidar for landslide mapping and inventories Puget Sound, WA Lidar landslide maps: Require trained geoscientists and protocols Increase landslide densities by 3 to 200 times Reveal complex landslide geometries Are often more accurate than field surveys Focus field investigations and analysis of archival photos for historical activity Portland, OR Ardennes, Belgium Burns & Madin, 2009; Mackey & Roering, 2011; Guzzetti et al., 2012; Schulz, 2007; van den Eeckhaut, 2012 Eel River, CA
Application 2: Lidar for automated landslide mapping algorithms South Island, New Zealand Landslide-prone terrain: Tends to be rough relative to stable slopes 1. Roughness can be measured in myriad ways 2. Simple and complex methods work well 3. Landslide style, vegetation, and age of instability produce a range of textures Exhibits different characteristic wavelengths depending on: 1. Landslide style or mechanics 2. Age of activity McKean & Roering, 2004; Glenn et al., 2006; Cavalli et al., 2008; Berti et al., 2013; Booth et al., 2009; Frankel and Dolan, 2007; Tarolli et al., 2010
Application 2: Lidar for automated landslide mapping algorithms South Island, New Zealand Landslide-prone terrain: Tends to be rough relative to stable slopes 1. Roughness can be measured in myriad ways 2. Simple and complex methods work well 3. Landslide style, vegetation, and age of instability produce a range of textures Exhibits different characteristic wavelengths depending on: 1. Landslide style or mechanics 2. Age of activity Apennines, Italy McKean & Roering, 2004; Glenn et al., 2006; Cavalli et al., 2008; Berti et al., 2013; Booth et al., 2009; Frankel and Dolan, 2007; Tarolli et al., 2010
Puget Sound, WA Application 2: Lidar for automated landslide mapping algorithms South Island, New Zealand Landslide-prone terrain: Tends to be rough relative to stable slopes 1. Roughness can be measured in myriad ways 2. Simple and complex methods work well 3. Landslide style, vegetation, and age of instability produce a range of textures Exhibits different characteristic wavelengths depending on: 1. Landslide style or mechanics 2. Age of activity Apennines, Italy McKean & Roering, 2004; Glenn et al., 2006; Cavalli et al., 2008; Berti et al., 2013; Booth et al., 2009; Frankel and Dolan, 2007; Tarolli et al., 2010
Application 3: Lidar for mapping relative age of slope instability Slope failures tend to smooth over time Absolute dating: tephrochronology, radiometric dating, cosmogenic dating, dendrochronology, & others Stillaguamish River, WA Haugerud, 2014; Cerovski-Darriau et al., 2014
Roughness Application 3: Lidar for mapping relative age of slope instability Slope failures tend to smooth over time Absolute dating: tephrochronology, radiometric dating, cosmogenic dating, dendrochronology, & others 1km 1km Stillaguamish River, WA North Island, New Zealand Haugerud, 2014; Cerovski-Darriau et al., 2014 Age (kyr)
Yosemite Valley, CA Thickness Application 4: Lidar for multi-temporal characterization of active landslides France Taiwan Apennines, Italy Link deformation to environmental variables Detection limit for elevation changes: 0.2m (bare, gentle surfaces, 1m DEM) to >1m (forested, steep terrain, 2 to 5m DEM) Used for rockfalls to slow-moving landslides Landslide thickness inverted from velocity fields Robust landslide area-volume scaling relationships for sediment flux estimates Satellite Interferometry San Diego, CA Young, 2015; Zimmer et al., 2012; Burns et al., 2010; Tseng et al., 2013; Booth et al., 2014; Handwerger et al., 2013
Thickness Yosemite Valley, CA Application 4: Lidar for multi-temporal characterization of active landslides France Taiwan E Apennines, Italy Link deformation to environmental variables Detection limit for elevation changes: 0.2m (bare, gentle surfaces, 1m DEM) to >1m (forested, steep terrain, 2 to 5m DEM) Used for rockfalls to slow-moving landslides Landslide thickness inverted from velocity fields Robust landslide area-volume scaling relationships for sediment flux estimates Satellite Interferometry Eel River, CA San Diego, CA Young, 2015; Zimmer et al., 2012; Burns et al., 2010; Tseng et al., 2013; Booth et al., 2014; Handwerger et al., 2013