We contrast a new continuous approach (CA) for estimating plot-level above-ground biomass (AGB) in forest inventories with the current approach of estimating AGB exclusively from the tree-level AGB predicted for each tree in a plot, henceforth called DA (discrete approach). With the CA, the AGB in a forest is modelled as a continuous surface and the AGB estimate for a fixed-area plot is computed as the integral of the AGB surface taken over the plot area. Hence with the CA, the portion of the biomass of in-plot trees that extends across the plot perimeter is ignored while the biomass from trees outside of the plot reaching inside the plot is added. We use a sampling simulation with data from a fully mapped two hectare area to illustrate that important differences in plot-level AGB estimates can emerge. Ideally CA-based estimates of mean AGB should be less variable than those derived from the DA. If realized, this difference translates to a higher precision from field sampling, or a lower required sample size. In our case study with a target precision of 5% (i.e. relative standard error of the estimated mean AGB), the CA required a 27.1% lower sample size for small plots of 100 m2 and a 10.4% lower sample size for larger plots of 1700 m2. We examined sampling induced errors only and did not yet consider model errors. We discuss practical issues in implementing the CA in field inventories and the potential in applications that model biomass with remote sensing data. The CA is a variation on a plot design for above-ground forest biomass; as such it can be applied in combination with any forest inventory sampling design.

中文翻译：

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通过替代地块生物量来提高地上生物量的现场库存估算的准确性

我们对比了一种新的连续方法（CA）来估计森林清单中的地块级地上生物量（AGB），而目前的方法是仅根据针对该地块中每棵树预测的树级AGB来唯一地估算AGB。离散方法）。使用CA，将森林中的AGB建模为连续表面，并将固定面积样地的AGB估算值计算为样地面积上AGB地表的积分。因此，在使用CA的情况下，忽略了在积木中穿过积木周界延伸的生物量部分，而增加了积木中树木外生物量到达积木内部的生物量。我们使用来自完全映射的两公顷区域的数据进行抽样模拟，以说明在地块级AGB估算中可能会出现重要差异。理想情况下，基于CA的平均AGB估算值应比从DA得出的估算值变化较小。如果意识到，这种差异将转化为现场采样的更高精度，或者更低的所需样本量。在我们的案例研究中，目标精度为5％（即，估计平均AGB的相对标准误差），对于100 m2的小块地块，CA需要减少27.1％的样本量，而对于1700块大块地块则需要低10.4％的样本量平方米 我们仅检查了采样引起的误差，尚未考虑模型误差。我们讨论了在现场清单中实施CA的实际问题，以及在利用遥感数据对生物质进行建模的应用中的潜力。CA是针对地上森林生物量的样地设计的变体。因此，它可以与任何森林清查抽样设计结合使用。