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Measurement of Forest Above-Ground Biomass Using Active and Passive Remote Sensing at Large (Subnational to Global) Scales

机译:使用主动和被动遥感大规模(从国家到全球)对森林地上生物量的测量

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摘要

Within the global forest area, a diverse range of forest types exist with each supporting varying amounts of biomass and allocations to different plant components. At country to continental scales, remote sensing techniques have been progressively developed to quantify the above-ground biomass (AGB) of these forests, with these based on optical, radar, and/or light detection and ranging (LiDAR) (airborne and spaceborne) data. However, none have been found to be globally applicable at high (?30 m) resolution, largely because of different forest structures (e.g., heights, covers, allocations of AGB) and varying environmental conditions (e.g., frozen, inundated). For this reason, techniques have varied between the major forest biomes. However, when combined, these estimates provide some insight into the distribution of AGB at country to global levels with associated levels of uncertainty. Comparisons of data and derived products have, in some cases, also contributed to our understanding of changes in carbon stocks across large areas. Further improvements in estimates are anticipated with the launch of new spaceborne LiDAR and SAR that have been specifically designed for better retrieval of forest structure and AGB.
机译:在全球森林区域内,存在着各种各样的森林类型,每种森林都支持不同数量的生物量以及对不同植物组成的分配。在国家到大陆范围内,已经逐步开发了遥感技术来量化这些森林的地上生物量(AGB),这些技术基于光学,雷达和/或光检测和测距(LiDAR)(机载和空载)数据。然而,尚未发现在高分辨率(?30 m)上没有一种适用于全球的情况,主要是由于不同的森林结构(例如高度,覆盖率,AGB的分配)和环境条件的变化(例如冷冻,淹没)。因此,主要森林生物群落之间的技术有所不同。但是,综合起来,这些估计值可以提供一些国家/地区和全球AGB分布的相关信息,以及相关的不确定性。在某些情况下,数据和派生产品的比较也有助于我们了解大面积碳储量的变化。预计将推出专门为更好地获取森林结构和AGB而设计的新型星载LiDAR和SAR,估计值将进一步改善。

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