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.

翻译：2018年发射的ICESat-2卫星搭载ATLAS传感器，这是一种光子计数星载激光雷达，可提供地表条带采样数据。虽然其主要设计用于雪冰监测，但利用ICESat-2预测森林地上生物量密度（AGBD）的研究兴趣日益浓厚。由于ICESat-2位于极地轨道，能良好覆盖北方森林区域。本研究旨在结合分层建模方法与严谨统计推断，评估基于ICESat-2数据估算平均AGBD的精度。我们提出一种分层混合推断方法，用于量化ICESat-2激光雷达条带数据估算AGBD的不确定性。该方法对多阶段建模误差进行建模，包括用于预测单木AGB的异速生长模型误差。为验证该方法，我们采用两个相邻研究区域（Valtimo和Nurmes）的数据，其中Valtimo区域用于模型训练，Nurmes区域用于验证。ICESat-2在Nurmes验证区域估算的平均AGBD为63.2±1.9 Mg/ha（相对标准误差2.9%）。基于全覆盖机载激光雷达数据的局部参考分层模型估算值为63.9±0.6 Mg/ha（相对标准误差1.0%）。参考估算值落在ICESat-2分层混合估算结果的95%置信区间内。较小的标准误差表明该方法可用于AGBD评估。但需注意，本研究未纳入某些误差来源，因此实际不确定性可能略大于报告值。