Using Simulated 3D Surface Fuelbeds and Terrestrial Laser Scan Data to Develop Inputs to Fire Behavior Models
Using Simulated 3D Surface Fuelbeds and Terrestrial Laser Scan Data to Develop Inputs to Fire Behavior Models
复制标题
使用模拟 3D 表面燃料层和地面激光扫描数据开发火灾行为模型的输入
DOI：
10.1080/07038992.2016.1220827
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发表时间：
2016
影响因子：
2.6
通讯作者：
Joseph J. O’Brien
中科院分区：
文献类型：
--
作者：
E. Rowell;E. L. Loudermilk;C. Seielstad;Joseph J. O’Brien
摘要 随着基于物理的火灾行为模型推动了对更高分辨率数据的需求，了解林下燃料的精细变化变得越来越重要。 3D 描述燃料床对于确定燃料元素和质量的垂直和水平分布至关重要，特别是在经常燃烧的松树生态系统中，其中精细的燃料布置会提高火灾强度并产生火灾效应。在这里，我们描述了涉及使用高分辨率 3D 模型的研究。我们使用根据现场测量设计的单独的草、枯枝落叶和松果模型来创建燃料床。这些燃料模型分布在整个燃料层中，以复制每个地块拍摄的校正最低点摄影中的燃料分布。模拟的燃料床被转换成体素阵列，并且根据计算的每个体素的网格顶点之间的表面积来估计生物量。我们将基于现场的燃料深度和生物量与模拟估计进行比较，以证明相似点和差异。使用威布尔形状参数（r = 0.86），模拟燃料床和地面激光扫描数据之间的生物量分布具有良好的相关性。我们的研究结果表明，现场、模拟和地面激光扫描仪数据的集成将改善燃料质量、类型和空间分配的表征，这些是基于物理的火灾行为模型的重要输入。
Abstract Understanding fine-scale variability in understory fuels is increasingly important as physics-based fire behavior models drive needs for higher-resolution data. Describing fuelbeds 3Dly is critical in determining vertical and horizontal distributions of fuel elements and the mass, especially in frequently burned pine ecosystems where fine-scale fuels arrangement drives fire intensity and resulting fire effects. Here, we describe research involving the use of highly resolved 3D models. We create fuelbeds using individual grass, litter, and pinecone models designed from field measurements. These fuel models are distributed throughout the fuelbed to replicate fuel distribution in rectified nadir photography taken for each plot. The simulated fuelbeds are converted into voxel arrays and biomass is estimated from calculated surface area between mesh vertices for each voxel. We compare field-based fuel depth and biomass with simulated estimates to demonstrate similarities and differences. Biomass distributions between simulated fuel beds and terrestrial laser scan data correlated well using Weibull shape parameters (r = 0.86). Our findings indicate that integration of field, simulated, and terrestrial laser scanner data will improve characterization of fuel mass, type, and spatial allocations that are important inputs to physics-based fire behavior models.
影响因子：
13.5
作者：
Disney, M. I.;Kalogirou, V.;Pfeifer, M.
通讯作者：
Pfeifer, M.
影响因子：
8.2
作者：
M. Disney;Philip Lewis;M. Bouvet;A. Prieto-Blanco;S. Hancock
通讯作者：
M. Disney;Philip Lewis;M. Bouvet;A. Prieto-Blanco;S. Hancock