Fires have become intense and more frequent in the United States. Improving the
accuracy of mapping fuel models is essential for fuel management decisions and explicit
fire behavior prediction for real-time support of suppression tactics and logistics
decisions. This study has two main objectives. The first objective is to develop the use
of LIght Detection and Ranging (LIDAR) remote sensing to assess fuel models in East
Texas accurately and effectively. More specific goals include: (1) developing LIDAR
derived products and the methodology to use them for assessing fuel models; (2)
investigating the use of several techniques for data fusion of LIDAR and multispectral
imagery for assessing fuel models; (3) investigating the gain in fuels mapping accuracy
with LIDAR as opposed to QuickBird imagery alone; and, (4) producing spatially
explicit digital fuel maps. The second objective is to model fire behavior using
FARSITE (Fire Area Simulator) and to investigate differences in modeling outputs using
fuel model maps, which differ in accuracy, in east Texas.
Estimates of fuel models were compared with in situ data collected over 62 plots.
Supervised image classification methods provided better accuracy (90.10%) with the
fusion of airborne LIDAR data and QuickBird data than with QuickBird imagery alone (76.52%). These two fuel model maps obtained from the first objective were used to see
the differences in fire growth with fuel model maps of different accuracies. According
to our results, LIDAR derived data provides accurate estimates of surface fuel
parameters efficiently and accurately over extensive areas of forests. This study
demonstrates the importance of using accurate maps of fuel models derived using new
LIDAR remote sensing techniques.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-1118 |
| Date | 15 May 2009 |
| Creators | Mutlu, Muge |
| Contributors | Popescu, Sorin C. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
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