Collaborative Research: Climatological, vegetational, and human-related controls on channelization and shallow landsliding quantified through objective analysis of LiDAR data

Lead PI: Dr. Colin P. Stark

Unit Affiliation: Marine and Polar Geophysics, Lamont-Doherty Earth Observatory (LDEO)

August 2011 - January 2015
Asia ; East Asia ; Japan
Project Type: Research

DESCRIPTION: The project worked to develop LiDAR DTM tools in GeoNet, finding suitable sites in Japan, and examining landscape evolution. Using these data the team worked on developing new algorithms to model landscape evolution.

OUTCOMES: The advent of one meter-resolution topographic data is revolutionizing the study of geomorphic processes. For the first time, the topographic patterns of surface flow, channelization, and landsliding can be resolved over large areas at resolutions commensurate with the scales of the governing processes. Such data provide an exciting opportunity to quantify these patterns and to investigate their dependence on climate, land cover, anthropogenic disturbance, and geology. At the same time, recently developed tools allow the objective extraction of geomorphic features and related attributes from the enormous amount of information contained in LiDAR digital terrain models (DTMs). The overall goal of this research project is to exploit this powerful combination of new data and new methods to deepen basic understanding of hillslope-channel process and form and to evaluate the dynamic interactions with vegetation, hydrologic response, and human-related disturbance. The investigators will employ new methods of geomorphic feature extraction and morphological analysis to a large inventory of LiDAR DTMs across Japan from the typhoon-dominated southwest to the temperate north in combination with detailed ground validation at key watersheds.

This project will yield a deeper quantitative understanding of the ecogeomorphic processes that affect the evolution of humid upland landscapes, especially the process of initiating channels in such environments. Project results will provide valuable information and insights to enable planners and decision makers to address issues of critical social relevance, such as flood and landslide hazard assessment, the ecogeomorphological effects of climate variability, and land-use management in montane environments subject to extreme events.


National Science Foundation (NSF)




University of Tokyo, University of Tsukuba, University of Texas at Austin, Zhejian University, Chang Jung Christian University, National Cheng-Kung Universiy



models lidar hazards landslides data water channelization hazards and risk reduction