USDA Forest Service
 

Adaptive Management Services

 
 

United States Department of Agriculture Forest Service, Enterprise

United States Department of Agriculture USDA Forest Service Enterprise - Reinvention Lab

Projects

Joint Fire Science / NASA Project

Project Summary

Background

Fusion of data from several remote sensors is planned including: optical multispectral scanner (such as Landsat TM), airborne laser altimetry (LIDAR such as SLICER and LVIS), orbital synthetic aperture radar (such as SIR-C/X, ERS ½, JERS-1, Radarsat), and airborne synthetic aperture radar (JPS AirSAR). Little work has been done in applying all but the Landsat TM sensor to fuel modeling. However, the lidar and radar sensors provide direct measure of canopy height (Dobson et al. 1995, Dobson et al. in review) and in the case of lidar, canopy profiles (Lefsky et al. 1998a, 1998b). The applications with these two imagery have focused to date on estimation of biomass, old-growth characteristics, and canopy profile diversity. At a recent remote sensing workshop to address inventory and monitoring needs, these two remote sensors were identified as being the most promising to test for mapping crown fuels (Hunsaker et al. in preparation). Radar also shows promise in detecting differences in the amount of dead versus live crown fuels and possible crown fuels moisture levels (Dobson, pers. communication).

There are two likely advantages from using the lidar and radar remote sensors in mapping crown fuels over the currently used Landsat TM sensors and associated ground data. If this pilot proves successful, these techniques could be useful in improving fuel mapping throughout the western United States. One advantage is that some of the crown characteristics are measured directly (i.e. canopy height and canopy profile), resulting in greater accuracy in estimation of crown fuels. Secondly, if there is a good ability to estimate crown fuel characteristics directly in the future without associated ground sampling (as is currently necessary with Landsat TM derived data), then the ability to spatially map crown fuels will be greatly increased. Currently, the National Forests of California utilize fuel maps generated from cross-walking plot data associated with forest cover types. This type of indirectly associated and estimated fuel-mapping decreases the spatial application of the fuels data as it is more of a sampling estimate. Current fire behavior models available utilize spatial data. Providing the best possible spatial crown fuel data will enhance the spatial fire behavior modeling. Mapping and modeling crown fuels for the sake of themselves is not common. More often, it is the spatial modeling of potential fire behavior that is most critical to fuels evaluation, monitoring and planning needs.

Works Cited

Sawyer, John and Todd Keeler-Wolf. 1995. A Manual of California Vegetation. California Native Plant Society: Sacramento, CA.

North, Malcolm. 2000. Research Ecologist: USDA Forest Service PSW Research Station. Personal communication.

PROJECT INFO
Project Summary
  Background
  Methods
  Design
  Deliverables
Progress to Date
Planned Work
JFS/NASA Investigators
Study Area Map [ PDF ]
Project [ PDF ]

 

USDA Forest Service - Adaptive Management Services Enterprise Unit
Last Modified: Monday, 16 December 2013 at 14:19:00 CST