Skip to Main Content
Application of ground-based LIDAR for fine-scale forest fuel modelingAuthor(s): E. Louise Loudermilk; Abhinav Singhania; Juan C. Fernandez; J. Kevin Hiers; Joseph J. O'Brien; Wendell P. Cropper Jr.; K. Clint Slatton; Robert J. Mitchell
Source: In: Butler, Bret W.; Cook, Wayne, comps. The fire environment--innovations, management, and policy; conference proceedings. 26-30 March 2007; Destin, FL. Proceedings RMRS-P-46CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. CD-ROM. p. 515-523
Publication Series: Proceedings (P)
Station: Rocky Mountain Research Station
PDF: View PDF (1.4 MB)
DescriptionFrequent (1 to 5 year) low intensity fire regimes of longleaf pine (Pinus palustris) savannas of the Southeastern United States create a continuous fuelbed of understory grasses, forbs, flammable pine needle litter, with interstitial hardwood shrubs. Measuring the spatial heterogeneity of these fine-fuels can be difficult, requiring intensive field sampling. Ground-based LIDAR (LIght Detection and Ranging) may prove useful in this aspect, collecting accurate three-dimensional point-clouds of objects at the sub-centimeter level. Here we present the methods and discuss the applicability of using a ground-based LIDAR system, the Mobile Terrestrial Laser Scanner (MTLS), to measure variation in fuelbed structure. The MTLS consists of Optech’s ILRIS 36D ground based laser scanner mounted on a lift atop a mobile platform, which increases its versatility in capturing details about the terrain at multiple angles, vertically and horizontally. We recorded sub-meter, spatially explicit fuel characteristics using the MTLS and manual point-intercept sampling techniques in multiple plots within a longleaf pine woodland. The LIDAR data required additional processing to make it comparable to the field data. This process involved merging individual scans of a plot taken at different angles and cropping out the areas of interest from the point clouds. Preliminary results illustrate that the fuelbeds can be classified into distinct categories with distinct characteristics, such as bulk density. The MTLS may be applicable for measuring spatially explicit plot-to-stand level fuel structure, continuity, and volume. Coupling MTLS derived fuel maps with fire behavior, through thermal imagery and modeling, combine to produce a promising strategy to connect fuels and fire at much finer scales than attempted before. This approach is particularly well suited to pine savannas with high frequency, low intensity fire regimes and other fuel types with fuel heights <10 m.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationLoudermilk, E. Louise; Singhania, Abhinav; Fernandez, Juan C.; Hiers, J. Kevin; O''Brien, Joseph J.; Cropper Jr., Wendell P.; Slatton, K. Clint; Mitchell, Robert J. 2007. Application of ground-based LIDAR for fine-scale forest fuel modeling. In: Butler, Bret W.; Cook, Wayne, comps. The fire environment--innovations, management, and policy; conference proceedings. 26-30 March 2007; Destin, FL. Proceedings RMRS-P-46CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. CD-ROM. p. 515-523
Keywordswildland fire management, LIDAR, LIght Detection and Ranging, fine-scale fuel modeling, longleaf pine savannas, Pinus palustris, Mobile Terrestrial Laser Scanner (MTLS)
- Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics
- Inferring energy incident on sensors in low-intensity surface fires from remotely sensed radiation and using it to predict tree stem injury
- Restoring the ground layer of longleaf pine ecosystems
XML: View XML