Probabilistic Use of LiDAR Data to Detect and Characterize Landslides

Landslide hazard and its consequences in the transportation network are well-understood, yet current methods of identifying and assessing landslide conditions are inefficient, as they are mostly based on labor-intensive field surveys. This research was performed as a feasibility study, where the potential of airborne Light Detection And Ranging (LiDAR) data for landslide detection was investigated. The primary objective of this pilot study was to develop, implement and validate computer models for automatic detection and assessment of landslides using time-series of airborne LiDAR data. Models have been developed using LiDAR data obtained from SR 666 in Muskingum County (District 5) and independently tested on LiDAR data covering southern Ohio. In this research effort, two techniques, one using single and the other based on multi-temporal surface models, obtained by airborne LiDAR, were proposed, implemented and tested for landslide susceptibility and hazard mapping. Based on a single dataset, 84% of the landslides from the reference inventory map of SR 666 were correctly identified, while using two datasets acquired four years apart, the proposed technique was able to identify 66% of the mapped landslides that are experiencing temporal changes susceptible to slides.

• Record URL:
  • http://www.dot.state.oh.us/Divisions/Planning/SPR/Research/reportsandplans/Reports/2015/Geotechnical/134609_FR.pdf
• 
• Corporate Authors:

  Ohio State University, Columbus

  Department of Civil and Environmental Engineering and Geodetic Science
  2070 Neil Avenue
  Columbus, OH  United States  43210-1275

  Ohio Department of Transportation

  Research Program
  1980 West Broad Street
  Columbus, OH  United States  43223

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Grejner-Brzezinska, Dorota A
  • Toth, Charles K
  • 0000-0001-9461-4887
  • Wu, T H
  • Shakoor, Abdul
• Publication Date: 2015-3

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Photos; References; Tables;
• Pagination: 179p

Subject/Index Terms

• TRT Terms: Detection and identification technologies; Feasibility analysis; Landslides; Laser radar; Validation
• Geographic Terms: Ohio
• Subject Areas: Data and Information Technology; Geotechnology; Highways; I42: Soil Mechanics;

Filing Info

• Accession Number: 01560940
• Record Type: Publication
• Report/Paper Numbers: FHWA/OH-2015/8
• Contract Numbers: SJN 134609
• Files: TRIS, ATRI, USDOT, STATEDOT
• Created Date: Apr 24 2015 10:24AM