Abstract

Abstract. The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a spatial resolution of 1 ha. Using an extensive database of 110 897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high-carbon-stock forests with AGB >250 Mg ha−1, where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in the literature (426–571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the Global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country's national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps and identified major biases compared to inventory data, up to 120 % of the inventory value in dry tropical forests, in the subtropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon, and socio-economic modelling schemes and provides a crucial baseline in future carbon stock change estimates. The dataset is available at https://doi.org/10.1594/PANGAEA.894711 (Santoro, 2018).

Highlights

  • Above-ground live biomass (AGB) is identified as one of 54 essential climate variables (ECVs) by the Global Climate Observing System (GCOS) because of its major role in the global carbon cycle

  • The spatially explicit estimates of AGB were based on the radar backscattered intensity recorded by the Phased Array-type L-band Synthetic Aperture Radar (PALSAR) instrument, on board the Advanced Land Observing Satellite (ALOS) satellite, and the Advanced Synthetic Aperture Radar (ASAR) instrument operating at C-band, on board the Environmental Satellite (Envisat)

  • The models for retrieving growing stock volume (GSV) and converting it to AGB were developed for woody vegetation, so we evaluated the estimates corresponding just to forest cover by regrouping the classes from the Climate Change Initiative Land Cover (CCI-LC) dataset of 2010 into forest and non-forest land

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Summary

Introduction

Above-ground live biomass (AGB) is identified as one of 54 essential climate variables (ECVs) by the Global Climate Observing System (GCOS) because of its major role in the global carbon cycle. Biomass stores carbon removed from the atmosphere by photosynthesis in long-lived woody pools and yields to carbon emissions to the atmosphere when disturbed. Biomass estimates allow the inference of emissions from forest degradation (Houghton et al, 2009; Li et al, 2017) and assistance with the derivation of emission factors (IPCC, 2006; Herold et al, 2019). Information on biomass directly supports policy by quantifying national carbon stocks in the context of reducing emissions from deforestation and degradation (REDD+), the Paris Agreement

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