George Mason University
George Mason University Mason
George Mason University

Contour Connection Method for Automated Identification and Classification of Landslide Deposits

by Burak Tanyu

Publication Details MORE LESS

  • Published Date: October 1, 2014
  • Publisher: Elsevier Publication

Abstract

Landslides are a common hazard worldwide that result in major economic, environmental and social impacts. Despite their devastating effects, inventorying existing landslides, often the regions at highest risk of reoccurrence, is challenging, time-consuming, and expensive. Current landslide mapping techniques include field inventorying, photogrammetric approaches, and use of bare-earth (BE) lidar digital terrain models (DTMs) to highlight regions of instability. However, many techniques do not have sufficient resolution, detail, and accuracy for mapping across landscape scale with the exception of using BE DTMs, which can reveal the landscape beneath vegetation and other obstructions, highlighting landslide features, including scarps, deposits, fans and more. Current approaches to landslide inventorying with lidar to create BE DTMs include manual digitizing, statistical or machine learning approaches, and use of alternate sensors (e.g., hyperspectral imaging) with lidar.

Other Contributors

Ben Leshchinsky, Michael Olsen
Expertise