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首页> 外文期刊>Surveys in Geophysics: An International Review Journal of Geophysics and Planetary Sciences >The Relevance of Forest Structure for Biomass and Productivity in Temperate Forests: New Perspectives for Remote Sensing
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The Relevance of Forest Structure for Biomass and Productivity in Temperate Forests: New Perspectives for Remote Sensing

机译：温带森林生物质结构与生产力的森林结构的相关性：遥感的新观点

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Forests provide important ecosystem services such as carbon sequestration. Forest landscapes are intrinsically heterogeneous-a problem for biomass and productivity assessment using remote sensing. Forest structure constitutes valuable additional information for the improved estimation of these variables. However, survey of forest structure by remote sensing remains a challenge which results mainly from the differences in forest structure metrics derived by using remote sensing compared to classical structural metrics from field data. To understand these differences, remote sensing measurements were linked with an individual-based forest model. Forest structure was analyzed by lidar remote sensing using metrics for the horizontal and vertical structures. To investigate the role of forest structure for biomass and productivity estimations in temperate forests, 25 lidar metrics of 375,000 simulated forest stands were analyzed. For the lidar-based metrics, top-of-canopy height arose as the best predictor for describing horizontal forest structure. The standard deviation of the vertical foliage profile was the best predictor for the vertical heterogeneity of a forest. Forest structure was also an important factor for the determination of forest biomass and aboveground wood productivity. In particular, horizontal structure was essential for forest biomass estimation. Predicting aboveground wood productivity must take into account both horizontal and vertical structures. In a case study based on these findings, forest structure, biomass and aboveground wood productivity are mapped for whole of Germany. The dominant type of forest in Germany is dense but less vertically structured forest stands. The total biomass of all German forests is 2.3Gt, and the total aboveground woody productivity is 43Mt/year. Future remote sensing missions will have the capability to provide information on forest structure (e.g., from lidar or radar). This will lead to more accurate assessments of
机译：森林提供重要的生态系统服务，如碳封存。森林景观是使用遥感的生物量和生产力评估的内在异质问题。森林结构构成有价值的额外信息，以改善这些变量的估计。然而，通过遥感对森林结构的调查仍然是一个挑战，这主要从使用远程感测到来自现场数据的经典结构指标而导出的森林结构度量的差异。要了解这些差异，遥感测量与基于个体的森林模型相关联。利用水平和垂直结构的度量来分析森林结构遥感分析。为了探讨森林结构对温带森林生物量和生产力估算的作用，分析了375,000个模拟森林站点的25个激光雷达度量。对于基于LIDAR的度量，顶面高度作为描述水平森林结构的最佳预测因子。垂直叶子剖面的标准偏差是森林垂直异质性的最佳预测因子。森林结构也是测定森林生物量和地上木材生产率的重要因素。特别是，水平结构对于森林生物量估计至关重要。预测地面木材生产率必须考虑水平和垂直结构。在基于这些发现的案例研究中，森林结构，生物量和地上的木材生产率映射到整个德国。德国的主导森林是密集但较少垂直结构的森林。所有德国森林的总生物量为2.3Gt，地上总木质生产力为43Mt /年。未来的遥感任务将能够提供有关森林结构的信息（例如，从LIDAR或RADAR）。这将导致更准确的评估

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