González-Ferreiro Eduardo, Arellano-Pérez Stéfano, Castedo-Dorado Fernando, Hevia Andrea, Vega José Antonio, Vega-Nieva Daniel, Álvarez-González Juan Gabriel, Ruiz-González Ana Daría
Unidad de Gestión Forestal Sostenible, Departamento de Ingeniería Agroforestal, Universidad de Santiago de Compostela, Lugo, Spain.
Departamento de Ingeniería y Ciencias Agrarias, Universidad de León, Campus de Ponferrada, Ponferrada, Spain.
PLoS One. 2017 Apr 27;12(4):e0176114. doi: 10.1371/journal.pone.0176114. eCollection 2017.
The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.
燃料复合体变量树冠体积密度和树冠基部高度常被用于预测树冠火的引发和蔓延。直接测量这些变量并不实际，通常通过建模间接估计。预测树冠火行为的最新进展需要准确估计树冠燃料的完整垂直分布。本研究的目的是利用西班牙国家森林清查数据以及低密度机载激光扫描（ALS）指标，对松树林分中可用树冠燃料的垂直剖面进行建模。第一步，使用威布尔概率密度函数对树冠燃料负荷的垂直分布进行建模。第二步，拟合两种不同的模型系统来估计定义垂直分布的树冠变量；第一个系统将这些变量与实地清查中获得的林分变量相关联，第二个系统将树冠变量与机载激光扫描指标相关联。同时拟合每个系统的模型，以补偿树冠变量之间固有跨模型相关性的影响。还分析了异方差性，但在拟合过程中无需进行校正。根据实地变量估计的树冠燃料负荷剖面分别解释了海岸松和辐射松树冠燃料负荷变化的84%和86%；而根据ALS指标估计的树冠燃料负荷剖面分别解释了相同树种变化的52%和49%。所提出的模型可用于评估不同森林管理方案在降低树冠火风险方面的有效性。
