Towards Spatially Explicit Quantification of Pre- and Postfire Fuels and Fuel Consumption from Traditional and Point Cloud Measurements

Methods to accurately estimate spatially explicit fuel consumption are needed because consumption relates directly to fire behavior, effects, and smoke emissions. Our objective was to quantify sparkleberry (Vaccinium arboretum Marshall) shrub fuels before and after six experimental prescribed fires at Fort Jackson in South Carolina. We used a novel approach to characterize shrubs non-destructively from three-dimensional (3D) point cloud data collected with a terrestrial laser scanner. The point cloud data were reduced to 0.001 m(-3) voxels that were either occupied to indicate fuel presence or empty to indicate fuel absence. The density of occupied voxels was related significantly by a logarithmic function to 3D fuel bulk density samples that were destructively harvested (adjusted R-2 = .32, P < .0001). Based on our findings, a survey-grade Global Navigation Satellite System may be necessary to accurately associate 3D point cloud data to 3D fuel bulk density measurements destructively collected in small (submeter) shrub plots. A recommendation for future research is to accurately geolocate and quantify the occupied volume of entire shrubs as 3D objects that can be used to train models to map shrub fuel bulk density from point cloud data binned to occupied 3D voxels. Study Implications: Public health concerns stemming from smoke emissions from prescribed fires are a major constraint for land managers on when, where, and how to burn. Fire and fuel managers would benefit greatly from remote sensing methods to quantify fuels loads, one of the major determinants of whether to prescribe a fire, and under what conditions. Methods that account for fuel heterogeneity are needed to do this more reliably because current operational fire and smoke models assume homogeneous fuel distributions. Although fire behavior, fire effects, and smoke emissions from fires relate to fuel structure and composition, they even more directly relate to fuel consumption. Estimation of fuel consumption requires research beyond quantification of fuel loads, whether prefire for purposes of fuel and fire planning, or postfire as a way to assess and predict fire effects. Our approach and findings advance the characterization of spatially complex shrub fuels in 3D, at the scales at which they vary using terrestrial laser scanning technology, so we can enhance the capabilities of fire and smoke models needed by managers and planners. Improved quantification of fuels and fuel consumption also will provide better, spatially explicit information to fire, fuel, and smoke managers and modelers, and policymakers.