Quantifying Understory Fuels Using Lidar Data in the Superior National Forest

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The Wildland Fuels Research project at the USGS Earth Resources Observation and Science Center seeks to develop novel applications of remotely sensed data to better quantify and map wildland fuels in support of wildfire planning and response.  A new initiative has begun in collaboration with the Superior National Forest (SNF) in northern Minnesota to quantify understory fuels using airborne lidar data.  In many areas of the SNF, small balsam fir trees make up a substantial portion of the understory vegetation and contribute to fire behavior when these areas burn.  However, existing vegetation and fuels maps do not typically capture understory since only dominant overstory species are represented.  This deficiency limits the ability of SNF managers to accurately predict fire behavior and fire effects.

USGS scientists are conducting field work to quantify the amount and distribution of understory fuels in the SNF, particularly focusing on balsam fir trees.  They will then use these data with existing airborne lidar to derive models of understory vegetation structure.  Landsat and other image sources will be utilized to extrapolate the understory fuels maps throughout the SNF and potentially other areas.  The goals are to provide SNF with a comprehensive quantification of balsam fir understory fuels structure throughout the forest and to develop mapping methodologies applicable to other parts of the region experiencing similar conditions.  Several ground-based fuels mapping methods are being investigated and the collection and use of terrestrial lidar data are also being considered.

Example of lidar-derived metric products of canopy structure from northern Cook County, Minnesota. A) Image showing an area characterized by varied forest strands.  (Red box shows where profile data in E were taken.) B) Lidar-derived maximum canopy height.  C) Lidar-derived height of low- to medium-height vegetation beneath the overstory canopy. D) Density of vegetation at 2–4 m within the canopy.  Note how spatial patterns shift between B, C, and D.  E) Profile of lidar returns showing taller canopy with relatively little vegetation and mid and low elevations to the left and canopy with denser near-surface vegetation to the right.

Example of lidar-derived metric products of canopy structure from northern Cook County, Minnesota. A) Image showing an area characterized by varied forest strands.  (Red box shows where profile data in E were taken.) B) Lidar-derived maximum canopy height.  C) Lidar-derived height of low- to medium-height vegetation beneath the overstory canopy. D) Density of vegetation at 2–4 m within the canopy.  Note how spatial patterns shift between B, C, and D.  E) Profile of lidar returns showing taller canopy with relatively little vegetation and mid and low elevations to the left and canopy with denser near-surface vegetation to the right.

Author Name
Kurtis Nelson
Author Email
knelson@usgs.gov