Pan, Y. et al. A Large and Persistent Carbon Sink in the World's Forests. Science 333, 988-993 (2011).
Bodansky, D. The Copenhagen Climate Change Conference: A Postmortem. Am. J. Int. Law 104, 230-240 (2010).
Pachauri, R. K. et al. Climate change 2014: synthesis Report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. (IPCC, 2014).
Herold, M. & Skutsch, M. Monitoring, reporting and verification for national REDD+ programmes: two proposals. Environ. Res. Lett. 6, 014002 (2011).
Ene, L. T. et al. Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data. Remote Sens. Environ. 186, 626-636 (2016).
Tomppo, E. et al. National forest inventories. Pathw. Common Report. Eur. Sci. Found. 541-553 (2010).
Saatchi, S. et al. Seeing the forest beyond the trees. Glob. Ecol. Biogeogr. 24, 606-610 (2015).
Mitchard, E. T. et al. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps. Carbon Balance Manag. 8, 10 (2013).
Saatchi, S. S. et al. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl. Acad. Sci. 108, 9899 (2011).
Goetz, S. J. et al. Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance Manag. 4, 2 (2009).
Hansen, M. C. et al. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850-853 (2013).
Hansen, E. H. et al. Relative Efficiency of ALS and InSAR for Biomass Estimation in a Tanzanian Rainforest. Remote Sens. 7, 9865-9885 (2015).
Næsset, E. et al. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision. Remote Sens. Environ. 175, 282-300 (2016).
Chen, Q., McRoberts, R. E., Wang, C. & Radtke, P. J. Forest aboveground biomass mapping and estimation across multiple spatial scales using model-based inference. Remote Sens. Environ. 184, 350-360 (2016).
Tittmann, P., Saatchi, S. & Sharma, B. VCS: Tool for measuring aboveground live forest biomass using remote sensing, https://doi. org/10. 13140/RG. 2. 1. 2351. 8567 (2015).
Zolkos, S. G., Goetz, S. J. & Dubayah, R. A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote Sens. Environ. 128, 289-298 (2013).
Xu, L. et al. Satellite observation of tropical forest seasonality: spatial patterns of carbon exchange in Amazonia. Environ. Res. Lett. 10, 084005 (2015).
Réjou-Méchain, M. et al. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks. Biogeosciences 11, 6827-6840 (2014).
Saarela, S. et al. Hierarchical model-based inference for forest inventory utilizing three sources of information. Ann. For. Sci. 73, 895-910 (2016).
Ståhl, G. et al. Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation. For. Ecosyst. 3, 5 (2016).
Potapov, P. V. et al. Quantifying forest cover loss in Democratic Republic of the Congo, 2000-2010, with Landsat ETM+ data. Remote Sens. Environ. 122, 106-116 (2012).
Mascaro, J. et al. A Tale of Two "Forests": Random Forest Machine Learning Aids Tropical Forest Carbon Mapping. PLoS ONE 9, e85993 (2014).
Schreuder, H. T., Gregoire, T. G. & Wood, G. B. Sampling Methods for Multiresource Forest Inventory (John Wiley & Sons, 1993).
Ståhl, G. et al. Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time. Can. J. For. Res. 41, 96-107 (2010).
Neigh, C. S. R. et al. Taking stock of circumboreal forest carbon with ground measurements, airborne and spaceborne LiDAR. Remote Sens. Environ. 137, 274-287 (2013).
Xu, L., Saatchi, S. S., Yang, Y., Yu, Y. & White, L. Performance of non-parametric algorithms for spatial mapping of tropical forest structure. Carbon Balance Manag. 11, 18 (2016).
Mokany, K., Raison, R. J. & Prokushkin, A. S. Critical analysis of root: shoot ratios in terrestrial biomes. Glob. Change Biol. 12, 84-96 (2006).
Longo, M. et al. Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon. Glob. Biogeochem. Cycles 30, 2016GB005465 (2016).
Choi, S. et al. Application of the metabolic scaling theory and water-energy balance equation to model large-scale patterns of maximum forest canopy height. Glob. Ecol. Biogeogr. 25, 1428-1442 (2016).
Espírito-Santo, F. D. B. et al. Size and frequency of natural forest disturbances and the Amazon forest carbon balance. Nat. Commun. 5, (2014).
Yang, Y. et al. Abiotic Controls on Macroscale Variations of Humid Tropical Forest Height. Remote Sens. 8, 494 (2016).
Bastin, J.-F. et al. Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach. Ecol. Appl. 24, 1984-2001 (2014).
Hughes, R. H., Hughes, J. S. & World Wide Fund for Nature. A directory of African wetlands. (IUCN, The World Conservation Union, 1992).
Dargie, G. C. et al. Age, extent and carbon storage of the central Congo Basin peatland complex. Nature advance online publication (2017).
Lewis, S. L. et al. Above-ground biomass and structure of 260 African tropical forests. Phil Trans R Soc B 368, 20120295 (2013).
Feldpausch, T. R. et al. Tree height integrated into pantropical forest biomass estimates. Biogeosciences 9, 3381-3403 (2012).
Steege, Hter et al. Hyperdominance in the Amazonian Tree Flora. Science 342, 1243092 (2013).
Chave, J. et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Change Biol. 20, 3177-3190 (2014).
Clark, D. A. Sources or sinks? The responses of tropical forests to current and future climate and atmospheric composition. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 359, 477-491 (2004).
Lloyd, J. & Farquhar, G. D. Effects of rising temperatures and [CO2] on the physiology of tropical forest trees. Philos. Trans. R. Soc. B Biol. Sci. 363, 1811-1817 (2008).
Bauters, M. et al. Functional Composition of Tree Communities Changed Topsoil Properties in an Old Experimental Tropical Plantation. Ecosystems 1-11, https://doi. org/10. 1007/s10021-016-0081-0 (2016).
Wood, T. E., Cavaleri, M. A. & Reed, S. C. Tropical forest carbon balance in a warmer world: a critical review spanning microbial-to ecosystem-scale processes. Biol. Rev. 87, 912-927 (2012).
Moles, A. T. et al. Global patterns in plant height. J. Ecol. 97, 923-932 (2009).
QGIS Development Team. QGIS 2. 8 User Guide. QGIS User Guide Available at: http://docs. qgis. org/2. 8/en/docs/user-manual/ (Accessed: 22nd May 2017) (2017).
Mathworks. Mapping Toolbox User's Guide (R2017a). Mapping Toolbox User's Guide-map-ug. pdf Available at: https://www. mathworks. com/products/mapping. html (Accessed: 22nd May 2017) (2017).