Development and validation of fuel height models for terrestrial lidar – RxCADRE 2012
Eric M. Rowell A B D , Carl A. Seielstad A B and Roger D. Ottmar C
+ Author Affiliations
- Author Affiliations
A National Center for Landscape Fire Analysis, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA.
B Department of Forest Management, College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA.
C USDA Forest Service, Pacific Wildland Fire Sciences Laboratory, 400 North 34th Street, Suite 201, Seattle, WA 98103, USA.
D Corresponding author. Email: eric.rowell@firecenter.umt.edu
International Journal of Wildland Fire 25(1) 38-47 https://doi.org/10.1071/WF14170
Submitted: 18 September 2014 Accepted: 23 September 2015 Published: 15 December 2015
Abstract
Terrestrial laser scanning (TLS) was used to collect spatially continuous measurements of fuelbed characteristics across the plots and burn blocks of the 2012 RxCADRE experiments in Florida. Fuelbeds were scanned obliquely from plot/block edges at a height of 20 m above ground. Pre-fire blocks were scanned from six perspectives and four perspectives for post-fire at ~2 cm nominal spot spacing. After processing, fuel height models were developed at one meter spatial resolution in burn blocks and compared with field measurements of height. Spatial bias is also examined. The resultant fuel height data correspond closely with field measurements of height and exhibit low spatial bias. They show that field measurements of fuel height from field plots are not representative of the burn blocks as a whole. A translation of fuel height distributions to specific fuel attributes will be necessary to maximise the utility of the data for fire modelling.
Additional keywords: fuels characterisation, grass fuels, prescribed fire, shrub fuels, spatially explicit, terrestrial laser scanner, TLS-based height metrics.
References
Anderson HE (1982) Aids to determining fuel models for estimating fire behavior. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-122. (Ogden, Utah)Burgan RE, Rothermel RC (1984) BEHAVE: fire behavior prediction and fuel modeling system – FUEL subsystem. USDA Forest Service, Intermountain Range and Experiment Station, General Technical Report INT-167. (Ogden, UT)
CloudCompare 2014. CloudCompare: 3D point cloud and mesh processing software: open source project. Available at www.cloudcompare.org [Verified 10 November 2015]
Glenn NF, Spaete LP, Sankey TT, Derryberry DR, Hardegree SP, Mitchell JJ (2011) Errors in lidar-derived shrub height and crown area on sloped terrain. Journal of Arid Environments 75, 377–382.
| Errors in lidar-derived shrub height and crown area on sloped terrain.Crossref | GoogleScholarGoogle Scholar |
Greaves HE, Vierling LA, Eitel J, Boelman NT, Magney TS, Prager CM, Griffin KL (2015) Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial lidar. Remote Sensing of Environment 164, 26–35.
| Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial lidar.Crossref | GoogleScholarGoogle Scholar |
Hiers JK, O’Brien JJ, Mitchell RJ, Grego JM, Loudermilk EL (2009) The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests. International Journal of Wildland Fire 18, 315–325.
| The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests.Crossref | GoogleScholarGoogle Scholar |
Hopkinson C, Chasmer LE, Sass G, Creed IF, Sitar M, Kalbfleisch W, Treitz P (2005) Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment. Canadian Journal of Remote Sensing 31, 191–206.
| Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment.Crossref | GoogleScholarGoogle Scholar |
Hosoi F, Omasa K (2006) Voxel-based 3-D modeling of individual trees for estimating leaf area density using high-resolution portable scanning lidar. IEEE Transactions on Geoscience and Remote Sensing 44, 3610–3618.
| Voxel-based 3-D modeling of individual trees for estimating leaf area density using high-resolution portable scanning lidar.Crossref | GoogleScholarGoogle Scholar |
Hosoi F, Omasa K (2007) Factors contributing to accuracy in the estimation woody canopy leaf area density profile using 3D portable lidar imaging. Journal of Experimental Botany 58, 3463–3473.
| Factors contributing to accuracy in the estimation woody canopy leaf area density profile using 3D portable lidar imaging.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1Kmt77J&md5=2cfed40b8e80c72feccbedd4d64b0ab2CAS | 17977852PubMed |
Hosoi F, Omasa K (2009) Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging. ISPRS Journal of Photogrammetry and Remote Sensing 64, 151–158.
| Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging.Crossref | GoogleScholarGoogle Scholar |
Hudak AT, Dickinson MB, Bright BC, Kremens RL, Loudermilk EL, O'Brien JJ, Hornsby BS, Ottmar RD (2015) Measurements relating fire radiative energy density and surface fuel consumption – RxCADRE 2011 and 2012. International Journal of Wildland Fire
| Measurements relating fire radiative energy density and surface fuel consumption – RxCADRE 2011 and 2012.Crossref | GoogleScholarGoogle Scholar |
Keane RE (2013) Describing wildland surface fuel loading for fire management: a review of approaches, methods and systems. International Journal of Wildland Fire 22, 51–62.
| Describing wildland surface fuel loading for fire management: a review of approaches, methods and systems.Crossref | GoogleScholarGoogle Scholar |
Keane RE, Gray K, Bacciu V (2012) Spatial variability of wildland fuel characteristics in northern Rocky Mountain ecosystems. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-98. (Fort Collins, CO)
Linn R, Reisner J, Colman JJ, Winterkamp J (2002) Studying wildfire behavior using FIRETEC. International Journal of Wildland Fire 11, 233–246.
| Studying wildfire behavior using FIRETEC.Crossref | GoogleScholarGoogle Scholar |
Loudermilk EL, Hiers JK, O’Brien JJ, Mitchell RJ, Singhania A, Fernandez JC, Cropper WP, Slatton KC (2009) Ground-based lidar: a novel approach to quantify fine-scale fuelbed characteristics. International Journal of Wildland Fire 18, 676–685.
| Ground-based lidar: a novel approach to quantify fine-scale fuelbed characteristics.Crossref | GoogleScholarGoogle Scholar |
Mell W, Jenkins MA, Gould J, Cheny P (2007) A physics based approach to modeling grassland fires. International Journal of Wildland Fire 16, 1–22.
| A physics based approach to modeling grassland fires.Crossref | GoogleScholarGoogle Scholar |
Morvan D, Dupuy JL (2004) Modeling the propagation of a wildfire through a Mediterranean shrub using a multiphase formulation. Combustion and Flame 138, 199–210.
| Modeling the propagation of a wildfire through a Mediterranean shrub using a multiphase formulation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXmtlOrurc%3D&md5=3fa78e615863390fdbb0e20cddcd372dCAS |
Olsoy P, Glenn N, Clark P, Derryberry D (2014) Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing 88, 166–173.
| Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning.Crossref | GoogleScholarGoogle Scholar |
Ottmar RD, Hudak AT, Prichard ST, Wright CS, Restaino JC, Kennedy MC, Vihnanek RE (2015) Pre-fire and post-fire surface fuel and cover measurements collected in the south-eastern United States for model evaluation and development – RxCADRE 2008, 2011 and 2012. International Journal of Wildland Fire
| Pre-fire and post-fire surface fuel and cover measurements collected in the south-eastern United States for model evaluation and development – RxCADRE 2008, 2011 and 2012.Crossref | GoogleScholarGoogle Scholar |
Pickett BM, Isackson C, Wunder R, Fletcher TH, Butler BW, Weise DR (2009) Flame interactions and burning characteristics of two live leaf samples. International Journal of Wildland Fire 18, 865–874.
| Flame interactions and burning characteristics of two live leaf samples.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtlWht7fN&md5=c7b9f43ec8f42b27d8fab0e82f773471CAS |
Popescu SC, Wynne RH, Nelson RF (2002) Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture 37, 71–95.
| Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size.Crossref | GoogleScholarGoogle Scholar |
Prince DR, Anderson BT, Cole WJ, Dennis M, Fletcher TH (2010) Modeling a burning shrub with and without wind using a semi-empirical model. Poster prepared for the ‘Association of Wildland Fire 3rd Fire Behavior and Fuels Conference’, 25–29 October 2010, Spokane, Washington, DC.
Riaño D, Chuvieco E, Ustin SL, Salas J, Rodriguez-Pérez JR, Ribeiro LM, Viegas DX (2007) Estimation of shrub height for fuel type mapping combining airborne lidar and simultaneous color infrared ortho imaging. International Journal of Wildland Fire 16, 341–348.
| Estimation of shrub height for fuel type mapping combining airborne lidar and simultaneous color infrared ortho imaging.Crossref | GoogleScholarGoogle Scholar |
Rowell E, Seielstad C (2012) Characterizing grass, litter, and shrub fuels in longleaf pine forest pre-and post-fire using terrestrial LiDAR. In ‘Proceedings of SilviLaser 2012’, 16–19 September 2012, Vancouver, Canada. (Eds NC Coops, MA Wulder) pp. 1–8.
Seielstad C, Stonesifer C, Rowell E, Queen L (2011) Deriving fuel mass by size class in Douglas-fir (Pseudotsuga menziesii) using terrestrial laser scanning. Remote Sensing 3, 1691–1709.
| Deriving fuel mass by size class in Douglas-fir (Pseudotsuga menziesii) using terrestrial laser scanning.Crossref | GoogleScholarGoogle Scholar |
Streutker D, Glenn N (2006) Lidar measurements of sagebrush steppe vegetation heights. Remote Sensing of Environment 102, 135–145.
| Lidar measurements of sagebrush steppe vegetation heights.Crossref | GoogleScholarGoogle Scholar |
Van der Zande D, Hoet W, Jonckheere I, Van Aardt J, Coppin P (2006) Influence of measurement set-up of ground-based lidar for derivation of tree structure. Agricultural and Forest Meteorology 141, 147–160.
| Influence of measurement set-up of ground-based lidar for derivation of tree structure.Crossref | GoogleScholarGoogle Scholar |
Vierling L, Xu Y, Eitel J, Oldow J (2013) Shrub characterization using terrestrial laser scanning and implications for airborne lidar assessment. Canadian Journal of Remote Sensing 38, 709–722.
| Shrub characterization using terrestrial laser scanning and implications for airborne lidar assessment.Crossref | GoogleScholarGoogle Scholar |
