Articles | Volume 11, issue 23
Biogeosciences, 11, 6827–6840, 2014
Biogeosciences, 11, 6827–6840, 2014

Research article 08 Dec 2014

Research article | 08 Dec 2014

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

M. Réjou-Méchain et al.

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Revised manuscript accepted for BG
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Cited articles

Agrawal, A., Nepstad, D., and Chhatre, A.: Reducing emissions from deforestation and forest degradation, Annu. Rev. Env. Resour., 36, 373–396, 2011.
Asner, G. P., Powell, G. V. N., Mascaro, J., Knapp, D. E., Clark, J. K., Jacobson, J., Kennedy-Bowdoin, T., Balaji, A., Paez-Acosta, G., Victoria, E., Secada, L., Valqui, M., and Hughes, R. F.: High-resolution forest carbon stocks and emissions in the Amazon, P. Natl. Acad. Sci., 107, 16738–16742,, 2010.
Asner, G. P., Mascaro, J., Anderson, C., Knapp, D. E., Martin, R. E., Kennedy-Bowdoin, T., Breugel, M. van, Davies, S., Hall, J. S., Muller-Landau, H. C., Potvin, C., Sousa, W., Wright, J., and Bermingham, E.: High-fidelity national carbon mapping for resource management and REDD+, Carbon Balance and Management, 8, 1–14,, 2013.
Baccini, A. and Asner, G. P.: Improving pantropical forest carbon maps with airborne LiDAR sampling, Carbon Management, 4, 591–600, 2013.
Baccini, A., Friedl, M. A., Woodcock, C. E., and Zhu, Z.: Scaling field data to calibrate and validate moderate spatial resolution remote sensing models, Photogramm. Eng. Rem. S., 73, 945–954, 2007.
Short summary
Forest carbon mapping may greatly reduce uncertainties in the global carbon budget. Accuracy of such maps depends however on the quality of field measurements. Using 30 large forest plots, we found large local spatial variability in biomass. When field calibration plots are smaller than the remote sensing pixels, this high local spatial variability results in an underestimation of the variance in biomass.
Final-revised paper