The monitoring of forested ecosystems relies on an accurate description of forest structure. The Ice, Cloud and land Elevation Satellite-2 (ICESat-2), launched in September 2018, carries the Advanced Topographic Laser Altimeter System (ATLAS), a Light Detection and Ranging (LiDAR) instrument capable of detecting individual photons reflected back from vegetation canopy. ICESat-2 data is delivering global estimates of forest structure; however, analysis of the performance of ICESat-2 on-orbit data across a range of forest conditions remains limited. This study derives structural estimates of (i) canopy height, (ii) canopy cover and (iii) canopy height variability from ICESat-2 data acquired in snow-free and low atmospheric scattering conditions over different boreal forest structural types in Ontario, Canada. ICESat-2 structural estimates were derived from the Global Geolocated Photon Data (ATL03) and Land and Vegetation Height (ATL08) data products and compared against single-photon detection airborne LiDAR (Leica SPL100). An extensive network of ground plots were used to stratify the study area into three distinct forest structural groups, each resulting from different stand development stages. ICESat-2 and SPL100 estimates of canopy height were compared at the ATL03 photon level, whereas estimates of height variability and canopy cover were compared for spatial analysis units (AU; mean size = 1287 m²). ICESat-2 photons returned from the top of the canopy underestimated canopy height relative to SPL100 by an average of 2.3 m overall and corresponded most strongly to the 90th percentile (P90) of coincident airborne SPL100 returns (root mean square difference (RMSD) = 2.9 m and correlation coefficient (r) = 0.84). The lowest average underestimation of SPL P90 was observed in homogeneous stands that were relatively simple, and single-layered with a single dominant species (RMSD = 2.5 m, r = 0.84). We observed the least agreement of ICESat-2 and SPL forest structural metrics in over-mature stands with complex structure and greater variability in canopy heights (RMSD = 3.5 m, r = 0.64). For the AUs, the strength of the relationship between SPL100 and ICESat-2 canopy height percentiles increased with increasing height percentiles (e.g. P25 RMSD% = 77.8%; P95 RMSD% = 23.7%). ICESat-2 generally underestimated canopy height variability relative to the SPL100 data, with both data having similar absolute variability (standard deviation of canopy heights RMSD% = 26.8%, r = 0.75), but lower agreement in relative variability (coefficient of variation of canopy heights RMSD% = 33.9%, r = 0.45). Herein we propose the use of the vegetation fill index as a method to estimate canopy cover with ICESat-2. Comparison of SPL100 and ICESat-2 vegetation fill indices at the AU level resulted in strong agreement overall (RMSD% = 19.7%; r = 0.57). These observations and results contribute to the overall objective of building a comprehensive understanding of the performance of ICESat-2 for characterizing vegetation structure in boreal forest environments.

森林生态系统的监测依赖于对森林结构的准确描述。2018 年 9 月发射的冰、云和陆地高程卫星 2 (ICESat-2) 携带先进地形激光高度计系统 (ATLAS)，这是一种光探测和测距 (LiDAR) 仪器，能够探测从植被反射回来的单个光子天篷。ICESat-2 数据正在提供森林结构的全球估计；但是，在一系列森林条件下对ICESat-2轨道数据性能的分析仍然有限。本研究从加拿大安大略省不同北方森林结构类型的无雪和低大气散射条件下获得的 ICESat-2 数据中推导出 (i) 冠层高度、(ii) 冠层覆盖和 (iii) 冠层高度变化的结构估计。ICESat-2 结构估计来自全球地理定位光子数据 (ATL03) 和土地和植被高度 (ATL08) 数据产品，并与单光子探测机载 LiDAR (Leica SPL100) 进行比较。广泛的地块网络用于将研究区域分为三个不同的森林结构组，每个组都来自不同的林分发展阶段。在 ATL03 光子水平上比较了 ICESat-2 和 SPL100 对冠层高度的估计，而对空间分析单位（AU；平均大小 = 1287 m）的高度变异性和冠层覆盖的估计进行了比较 广泛的地块网络用于将研究区域分为三个不同的森林结构组，每个组都来自不同的林分发展阶段。在 ATL03 光子水平上比较了 ICESat-2 和 SPL100 对冠层高度的估计，而对空间分析单位（AU；平均大小 = 1287 m）的高度变异性和冠层覆盖的估计进行了比较 广泛的地块网络用于将研究区域分为三个不同的森林结构组，每个组都来自不同的林分发展阶段。在 ATL03 光子水平上比较了 ICESat-2 和 SPL100 对冠层高度的估计，而对空间分析单位（AU；平均大小 = 1287 m）的高度变异性和冠层覆盖的估计进行了比较²）。从冠层顶部返回的 ICESat-2 光子相对于 SPL100 总体上低估了冠层高度平均 2.3 m，并且与同时发生的机载 SPL100 返回的第 90 个百分位数 (P90) 的对应最强（均方根差（RMSD）= 2.9 m 和相关系数 ( r ) = 0.84)。SPL P90 的最低平均低估出现在相对简单且具有单一优势物种的单层的均质林分中（RMSD = 2.5 m，r  = 0.84）。我们观察到 ICESat-2 和 SPL 森林结构指标在具有复杂结构和冠层高度变化较大的过度成熟林分中的一致性最低 (RMSD = 3.5 m, r = 0.64）。对于 AU，SPL100 和 ICESat-2 冠层高度百分位数之间的关系强度随着高度百分位数的增加而增加（例如 P25 RMSD% = 77.8%；P95 RMSD% = 23.7%）。ICESat-2 通常低估了相对于 SPL100 数据的冠层高度变异性，这两个数据具有相似的绝对变异性（冠层高度的标准偏差 RMSD% = 26.8%，r  = 0.75），但相对变异性（冠层变异系数）的一致性较低高度 RMSD% = 33.9%，r  = 0.45）。在此，我们建议使用植被填充指数作为一种方法来估计 ICESat-2 的冠层覆盖。SPL100 和 ICESat-2 植被填充指数在 AU 级别的比较导致总体上非常一致（RMSD% = 19.7%；r = 0.57）。这些观察结果和结果有助于全面了解 ICESat-2 用于表征北方森林环境中植被结构的性能的总体目标。