使用分层混合推断从ICESat-2数据估算北方森林生物量
Estimation of boreal forest biomass from ICESat-2 data using hierarchical hybrid inference
AI总结：
本文提出分层混合推断方法，利用ICESat-2光子计数激光雷达条带数据估算北方森林地上生物量密度，并通过Valtimo训练、Nurmes验证，证明估算结果与机载激光雷达参考值高度一致且不确定性较小。
摘要：
ICESat-2于2018年发射，搭载了ATLAS仪器，这是一种光子计数星载激光雷达，可提供地形上方的条带采样。虽然其主要设计用于冰雪监测，但人们对利用ICESat-2预测森林地上生物量密度（AGBD）产生了极大兴趣。由于ICESat-2处于极地轨道，它为北方森林提供了良好的空间覆盖。本研究旨在评估使用分层建模方法并结合严格统计推断从ICESat-2数据估算平均AGBD的效果。我们提出了一种分层混合推断方法，用于对从ICESat-2激光雷达条带估算的AGBD进行不确定性量化。我们的方法对来自多个建模步骤的误差进行建模，包括用于预测单木水平地上生物量的异速生长模型。为测试该流程，我们使用了两个相邻研究区的数据，分别记为Valtimo和Nurmes，其中Valtimo区域用于模型训练，Nurmes用于验证。在Nurmes验证区，ICESat-2估算的平均AGBD为63.2±1.9 Mg/ha（相对标准误差为2.9%）。基于全覆盖机载激光雷达数据获得的当地参考分层模型估算值为63.9±0.6 Mg/ha（相对标准误差为1.0%）。参考估算值位于ICESat-2分层混合估算值的95%置信区间内。较小的标准误差表明所提方法对AGBD评估是有用的。然而，研究中未考虑某些误差来源，因此实际不确定性可能略大于所报告的值。
英文摘要：
The ICESat-2, launched in 2018, carries the ATLAS instrument, which is a photon-counting spaceborne lidar that provides strip samples over the terrain. While primarily designed for snow and ice monitoring, there has been a great interest in using ICESat-2 to predict forest above-ground biomass density (AGBD). As ICESat-2 is on a polar orbit, it provides good spatial coverage of boreal forests. The aim of this study is to evaluate the estimation of mean AGBD from ICESat-2 data using a hierarchical modeling approach combined with rigorous statistical inference. We propose a hierarchical hybrid inference approach for uncertainty quantification of the AGBD estimated from ICESat-2 lidar strips. Our approach models the errors coming from the multiple modeling steps, including the allometric models used for predicting tree-level AGB. For testing the procedure, we have data from two adjacent study sites, denoted Valtimo and Nurmes, of which Valtimo site is used for model training and Nurmes for validation. The ICESat-2 estimated mean AGBD in the Nurmes validation area was 63.2$\pm$1.9 Mg/ha (relative standard error of 2.9%). The local reference hierarchical model-based estimate obtained from wall-to-wall airborne lidar data was 63.9$\pm$0.6 Mg/ha (relative standard error of 1.0%). The reference estimate was within the 95% confidence interval of the ICESat-2 hierarchical hybrid estimate. The small standard errors indicate that the proposed method is useful for AGBD assessment. However, some sources of error were not accounted for in the study and thus the real uncertainties are probably slightly larger than those reported.
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