Abstract

Assessing Southern California Wildfire Hazard using GIS and Remote-Sensing
Track: Parks and Natural Reserves
Author(s): Philip Dennison

Southern California possesses a combination of fire-adapted
vegetation, extreme weather, and residential development that
creates high wildfire hazard. This talk summarizes recent
research using GIS and remote sensing to measure fuel
properties, predict fire susceptibility, and model fire behavior for
community evacuation. Moderate Resolution Imaging
Spectrometer (MODIS) data can be used to monitor changes in
live fuel moisture over time. Higher spatial resolution
hyperspectral Airborne Visible Infrared Imaging Spectrometer
(AVIRIS) data can retrieve live fuel moisture and fuel type, often
to the species level. Using relative precipitation, new predictive
models of live fuel moisture trends allow forecasting of wildfire
susceptibility months in advance. Fire modeling and GIS
algorithms can utilize fuels and weather information to create
'evacuation trigger buffers' indicating when an active fire may
approach an endangered community, allowing timely evacuation
or sheltering. Operational products from these areas of research
will improve wildfire hazard knowledge and emergency
preparedness.

Philip Dennison
University of Utah
Department of Geography
260 S. Central Campus Dr. Rm 270
Salt Lake City , Utah 84112
United States
Phone: 801-585-1805
E-mail: dennison@geog.utah.edu