@article{fdi:010079426,
  title = {{A} map of {A}frican humid tropical forest aboveground biomass derived from management inventories},
  author = {{P}loton, {P}ierre and {M}ortier, {F}. and {B}arbier, {N}icolas and {C}ornu, {G}. and {R}{\'e}jou-{M}{\'e}chain, {M}axime and {R}ossi, {V}. and {A}lonso, {A}. and {B}astin, {J}. {F}. and {B}ayol, {N}. and {B}enedet, {F}. and {B}issiengou, {P}. and {C}huyong, {G}. and {D}emarquez, {B}. and {D}oucet, {J}. {L}. and {D}roissart, {V}incent and {K}amdem, {N}. {G}. and {K}enfack, {D}. and {M}emiaghe, {H}. and {M}oses, {L}. and {S}onke, {B}. and {T}exier, {N}icolas and {T}homas, {D}. and {Z}ebaze, {D}. and {P}{\'e}lissier, {R}apha{\¨e}l and {G}ourlet-{F}leury, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}orest biomass is key in {E}arth carbon cycle and climate system, and thus under intense scrutiny in the context of international climate change mitigation initiatives (e.g. {REDD}+). {I}n tropical forests, the spatial distribution of aboveground biomass ({AGB}) remains, however, highly uncertain. {T}here is increasing recognition that progress is strongly limited by the lack of field observations over large and remote areas. {H}ere, we introduce the {C}ongo basin {F}orests {AGB} ({C}o{F}or-{AGB}) dataset that contains {AGB} estimations and associated uncertainty for 59,857 1-km pixels aggregated from nearly 100,000 ha ofin situforest management inventories for the 2000 - early 2010s period in five central {A}frican countries. {A} comprehensive error propagation scheme suggests that the uncertainty on {AGB} estimations derived from c. 0.5-ha inventory plots (8.6-15.0%) is only moderately higher than the error obtained from scientific sampling plots (8.3%). {C}o{F}or-{AGB} provides the first large scale view of forest {AGB} spatial variation from field data in central {A}frica, the second largest continuous tropical forest domain of the world.},
  keywords = {{AFRIQUE} {CENTRALE} ; {ZONE} {TROPICALE}},
  booktitle = {},
  journal = {{S}cientific {D}ata},
  volume = {7},
  numero = {1},
  pages = {art. 221 [13p.]},
  year = {2020},
  DOI = {10.1038/s41597-020-0561-0},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079426},
}