Avitabile, V, Herold, M, Heuvelink, GBM et al. (30 more authors) (2016) An integrated pan-tropical biomass map using multiple reference datasets. Global Change Biology, 22 (4). pp. 1406-1420. ISSN 1354-1013
Abstract
We combined two existing datasets of vegetation aboveground biomass (AGB) (Saatchi et al., 2011; Baccini et al., 2012) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally-calibrated high-resolution biomass maps, harmonized and upscaled to 14,477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N – 23.4 S) of 375 Pg dry mass, 9% - 18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2,118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15 – 21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha−1 vs. 21 and 28 Mg ha−1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 John Wiley & Sons Ltd. This is the peer reviewed version of the following article: Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L., Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N., Berry, N. J., Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A. J., Kearsley, E., Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A., Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J., Ryan, C. M., Ferry, S. J. W., Sunderland, T., Laurin, G. V., Gatti, R. C., Valentini, R., Verbeeck, H., Wijaya, A. and Willcock, S. (2016), An integrated pan-tropical biomass map using multiple reference datasets. Global Change Biology, 22: 1406–1420. doi: 10.1111/gcb.13139, which has been published in final form at http://dx.doi.org/10.1111/gcb.13139. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |
Keywords: | aboveground biomass; carbon cycle; forest plots; tropical forest; forest inventory; REDD+; satellite mapping; remote sensing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Ecology & Global Change (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > River Basin Processes & Management (Leeds) > SOG: water@leeds |
Funding Information: | Funder Grant number EU - European Union 291585 (ERC 2011 ADG) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Nov 2015 16:28 |
Last Modified: | 10 Apr 2019 09:10 |
Published Version: | http://dx.doi.org/10.1111/gcb.13139 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/gcb.13139 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:91551 |