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The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations

Santoro, Maurizio, Cartus, Oliver, Carvalhais, Nuno, Rozendaal, Danaë M. A., Avitabile, Valerio, Araza, Arnan, de Bruin, Sytze, Herold, Martin, Quegan, Shaun, Rodríguez-Veiga, Pedro, Balzter, Heiko, Carreiras, João, Schepaschenko, Dmitry, Korets, Mikhail, Shimada, Masanobu, Itoh, Takuya, Moreno Martínez, Álvaro, Cavlovic, Jura, Cazzolla Gatti, Roberto, da Conceição Bispo, Polyanna, Dewnath, Nasheta, Labrière, Nicolas, Liang, Jingjing, Lindsell, Jeremy, Mitchard, Edward T. A., Morel, Alexandra, Pacheco Pascagaza, Ana Maria, Ryan, Casey M., Slik, Ferry, Vaglio Laurin, Gaia, Verbeeck, Hans, Wijaya, Arief, Willcock, Simon·2021·Earth System Science Data
DOI 10.5194/essd-13-3927-2021

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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).

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  • The main objective of the GEDI mission is to provide high-accuracy and high global coverage data on canopy structure, which can be used to estimate biomass and canopy height.

    “The main objective of the GEDI mission is to provide high-accuracy and high global coverage data on canopy structure, which can be used to estimate biomass [39][40][41] and canopy height [30,38,42].”

    From ANADEM: A Digital Terrain Model for South America (2024) · cites this paper as [41]

    Section 5 (Discussion and conclusions; page unavailable) says future spaceborne lidar is expected to provide more detail on forest vertical structure and help improve biomass estimates. Section 2.1 (Satellite data; page unavailable) describes using ICESat/GLAS, not GEDI, to estimate forest height and support biomass retrieval. Our copy does not state GEDI’s mission objective or claim high accuracy and global coverage for its canopy-structure data. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

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Authors
Santoro, M., Cartus, O., Carvalhais, N., Rozendaal, D. M. A., Avitabile, V., Araza, A., de Bruin, S., Herold, M., Quegan, S., Rodríguez-Veiga, P., Balzter, H., Carreiras, J., Schepaschenko, D., Korets, M., Shimada, M., Itoh, T., Moreno Martínez, Á., Cavlovic, J., Cazzolla Gatti, R., da Conceição Bispo, P., Dewnath, N., Labrière, N., Liang, J., Lindsell, J., Mitchard, E. T. A., Morel, A., Pacheco Pascagaza, A. M., Ryan, C. M., Slik, F., Vaglio Laurin, G., Verbeeck, H., Wijaya, A., & Willcock, S.
ORCID
Venue
Earth System Science Data
Publisher
Copernicus GmbH
Published
2021-08-11
Volume
13
Issue
8
Pages
3927-3950
ISSN
1866-3516
DOI
10.5194/essd-13-3927-2021
Cited by
338
References
6
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • European Space Agency (ESRIN contract No. 4000113100/14/I-NB)
  • Russian Science Foundation (19-77-30015)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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