Evaluation of alternative approaches for landscape-scale biomass estimation in a mixed-species northern forest
Evaluation of alternative approaches for landscape-scale biomass estimation in a mixed-species northern forest
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DOI：
10.1016/j.foreco.2017.11.040
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发表时间：
2018-02
影响因子：
3.7
通讯作者：
C. Hoover;M. Ducey;R. Andy Colter;M. Yamasaki
中科院分区：
文献类型：
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作者：
C. Hoover;M. Ducey;R. Andy Colter;M. Yamasaki
人们对估计和绘制大面积森林的生物量和碳含量越来越感兴趣。基于激光雷达的清查方法越来越普遍，并已在多种森林类型中成功实施。阿斯纳等人。 （2011）开发了一种简单的热带森林通用森林碳估算方法，减少了所需的实地测量量。我们在新罕布什尔州怀特山脉北部以硬木为主的流域测试了这种方法以及标准回归和随机森林建模技术。其他目标包括评估不同库存地块设计和 GPS 精度的影响。由于冠层高度和林分断面积之间缺乏明确的关系，通用模型在这种森林景观中表现不佳。简单的回归模型也会产生较差的模型拟合度；随机森林模型比通用模型或回归模型产生了更好的生物量预测，并且通过 R2 测量的预测能力较低，但均方根误差与复杂森林中其他研究的结果相当。调查与资源级 GPS 单位的位置精度影响很小，不同地块设计的影响也很小，尽管使用较大的基础面积系数时误差通常会增加。
There is growing interest in estimating and mapping biomass and carbon content of forests across large landscapes. LiDAR-based inventory methods are increasingly common and have been successfully implemented in multiple forest types. Asner et al. (2011) developed a simple universal forest carbon estimation method for tropical forests that reduces the amount of required field measurements. We tested this approach, along with standard regression and Random Forest modeling techniques, in a northern hardwood-dominated watershed in the White Mountains of New Hampshire. Additional objectives included assessing the effects of different inventory plot designs and GPS accuracy. The universal model performed poorly in this forested landscape due to the lack of a clear relationship between canopy height and stand basal area. Simple regression modeling also produced poor model fits; the Random Forest models produced somewhat better biomass predictions than either the universal or regression models, and had low predictive power as measured by R2but root mean squared errors were comparable to those from other studies in complex forests. Effects of positional accuracy from survey vs. resource grade GPS units were slight, as were the effects of varying plot designs, although errors generally increased when larger basal area factors were used.