Crown fires, the fastest spreading of all forest fires, can occur in any forest type
throughout the United States and the world. The occurrence of crown fires has become
increasingly frequent and severe in recent years. The overall aim of this study is to
estimate the forest canopy fuel parameters including crown base height (CBH) and
crown bulk density (CBD), and to investigate the potential of using airborne lidar data in
east Texas. The specific objectives are to: (1) propose allometric estimators of CBD and
CBH and compare the results of using those estimators to those produced by the
CrownMass/FMAPlus software at tree and stand levels for 50 loblolly pine plots in
eastern Texas, (2) develop a methodology for using airborne light detection and ranging
(lidar) to estimate CBD and CBH canopy fuel parameters and to simulate fire behavior
using estimated forest canopy parameters as FARSITE inputs, and (3) investigate the use
of spaceborne ICEsat /GLAS (Ice, Cloud, and Land Elevation Satellite/Geoscience Laser
Altimeter System) lidar for estimating canopy fuel parameters. According to our results
from the first study, the calculated average CBD values, across all 50 plots, were 0.18 kg/m³ and 0.07 kg/m³, respectively, for the allometric equation proposed herein and
the CrownMass program. Lorey’s mean height approach was used in this study to
calculate CBH at plot level. The average height values of CBH obtained from Lorey’s
height approach was 10.6 m and from the CrownMass program was 9.1 m. The results
obtained for the two methods are relatively close to each other; with the estimate of CBH
being 1.16 times larger than the CrownMass value. According to the results from the
second study, the CBD and CBH were successfully predicted using airborne lidar data
with R² values of 0.748 and 0.976, respectively. The third study demonstrated that
canopy fuel parameters can be successfully estimated using GLAS waveform data; an R²
value of 0.84 was obtained. With these approaches, we are providing practical methods
for quantifying these parameters and making them directly available to fire managers.
The accuracy of these parameters is very important for realistic predictions of wildfire
initiation and growth.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-12-8810 |
| Date | 2010 December 1900 |
| Creators | Mutlu, Muge |
| Contributors | Popescu, Sorin C. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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