More than one quarter of Africa’s tree cover is found outside areas previously classified as forest
2023
Reiner, Florian | Brandt, Martin S. | Tong, Xiaoye | Skole, David L. | Kariryaa, Ankit | Ciais, Philippe | Davies, Andrew B. | Hiernaux, Pierre H.Y. | Chave, Jérôme | Mugabowindekwe, Maurice | Igel, Christian | Oehmcke, Stefan | Gieseke, Fabian Cristian | Li, Sizhuo | Liu, Siyu | Saatchi, Sassan S. | Boucher, Peter Brehm | Singh, Jenia | Taugourdeau, Simon | Dendoncker, Morgane | Song, Xiaopeng | Mertz, Ole | Tucker, Compton James | Fensholt, R. | University of Copenhagen = Københavns Universitet (UCPH) | Michigan State University [East Lansing] ; Michigan State University System | Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE) ; Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) ; Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) | Harvard University | Pastoralisme Conseil (PastoC) | Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT) | Westfälische Wilhelms-Universität Münster = University of Münster (WWU) | SOUtenabilité et RésilienCE (SOURCE) ; Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut de Recherche pour le Développement (IRD [Ile-de-France]) | California Institute of Technology (CALTECH) | Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) | Université Catholique de Louvain = Catholic University of Louvain (UCL) | University of Maryland [College Park] (UMD) ; University System of Maryland | NASA Goddard Space Flight Center (GSFC) | ANR-10-LABX-0041, ANR-10-LABX-25-01; National Aeronautics and Space Administration, NASA: 80NSSC21K0315; Villum Fonden; Horizon 2020 Framework Programme, H2020: 947757; European Research Council, ERC; Danmarks Grundforskningsfond, DNRF; Centre National d’Etudes Spatiales, CNES; Danmarks Frie Forskningsfond, DFF: 9064-00049B | We thank Norway’s International Climate and Forest Initiative (NICFI) satellite data Level 2 programme for providing parts of the very high-resolution satellite imagery for the study. This work was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 947757 TOFDRY). R.F., C.I., and A.K. acknowledge support from Villum Fonden through the project Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics (DeReEco). A.D., P.B., and J.S. acknowledge support from Karingani Holdings for funding the LiDAR data collection and processing for Mozambique. C.I. acknowledges support by the Pioneer Centre for AI, DNRF grant number P1. J.C. acknowledges grants from Investissements d’Avenir (CEBA, ref. ANR-10-LABX-25-01; TULIP, ref. ANR-10-LABX-0041), ESA CCI-Biomass and CNES. D.S. acknowledges support by NASA, grant no. 80NSSC21K0315 from the Land Cover and Land Use Change Program. M.M. was supported by a DFF Sapere Aude grant (no. 9064-00049B). | We thank Norway’s International Climate and Forest Initiative (NICFI) satellite data Level 2 programme for providing parts of the very high-resolution satellite imagery for the study. This work was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 947757 TOFDRY). R.F., C.I., and A.K. acknowledge support from Villum Fonden through the project Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics (DeReEco). A.D., P.B., and J.S. acknowledge support from Karingani Holdings for funding the LiDAR data collection and processing for Mozambique. C.I. acknowledges support by the Pioneer Centre for AI, DNRF grant number P1. J.C. acknowledges grants from Investissements d’Avenir (CEBA, ref. ANR-10-LABX-25-01; TULIP, ref. ANR-10-LABX-0041), ESA CCI-Biomass and CNES. D.S. acknowledges support by NASA, grant no. 80NSSC21K0315 from the Land Cover and Land Use Change Program. M.M. was supported by a DFF Sapere Aude grant (no. 9064-00049B). | ANR-10-LABX-0041,TULIP,Towards a Unified theory of biotic Interactions: the roLe of environmental(2010)
International audience
Afficher plus [+] Moins [-]anglais. The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = −6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies.
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