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 R2 = .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.

中文翻译：

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从传统和点云测量中对火前和火后燃料和燃料消耗量进行空间明确量化

需要准确估计空间明确燃料消耗的方法，因为消耗与火灾行为、影响和烟雾排放直接相关。我们的目标是在南卡罗来纳州杰克逊堡的六次实验性规定火灾之前和之后量化 Sparkleberry（Vaccinium arboretum Marshall）灌木燃料。我们使用了一种新颖的方法，通过地面激光扫描仪收集的三维 (3D) 点云数据无损地表征灌木。点云数据减少到 0.001 m-3 体素，这些体素要么被占用以指示燃料存在，要么被占用以指示燃料不存在。占用体素的密度与破坏性收集的 3D 燃料体积密度样品的对数函数显着相关（调整后的 R2 = .32，P < .0001）。根据我们的发现，可能需要测量级全球导航卫星系统，才能将 3D 点云数据与在小型（亚米级）灌木丛中破坏性收集的 3D 燃料体积密度测量值准确关联。对未来研究的建议是将整个灌木的占用体积准确地定位和量化为 3D 对象，这些对象可用于训练模型以映射灌木燃料体积密度从分箱到占用 3D 体素的点云数据。