The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations
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Published:2021-08-11
Issue:8
Volume:13
Page:3927-3950
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ISSN:1866-3516
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Container-title:Earth System Science Data
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language:en
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Short-container-title:Earth Syst. Sci. Data
Author:
Santoro MaurizioORCID, Cartus Oliver, Carvalhais NunoORCID, Rozendaal Danaë M. A., Avitabile ValerioORCID, Araza ArnanORCID, de Bruin SytzeORCID, Herold Martin, Quegan Shaun, Rodríguez-Veiga PedroORCID, Balzter Heiko, Carreiras João, Schepaschenko DmitryORCID, Korets Mikhail, Shimada MasanobuORCID, Itoh Takuya, Moreno Martínez ÁlvaroORCID, Cavlovic Jura, Cazzolla Gatti Roberto, da Conceição Bispo PolyannaORCID, Dewnath Nasheta, Labrière Nicolas, Liang Jingjing, Lindsell Jeremy, Mitchard Edward T. A.ORCID, Morel Alexandra, Pacheco Pascagaza Ana Maria, Ryan Casey M., Slik Ferry, Vaglio Laurin Gaia, Verbeeck HansORCID, Wijaya AriefORCID, Willcock SimonORCID
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).
Funder
European Space Agency Russian Science Foundation
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
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