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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.Peer reviewe

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