Satellite-based mapping of annual canopy height and aboveground biomass in African dense forests

Liang Wan; Philippe Ciais; Aurélien de Truchis; Ewan Sean; Fabian Jörg Fischer; David Purnell; Gabriel Belouze; Ibrahim Fayad; Martin Schwartz; Yidi Xu; Yang Su; Maxime Réjou-Méchain; Nicolas Barbier; Paul Tresson; Jean-François Bastin; Jan Bogaert; Arthur Vander Linden; Antoine Plumacker; Bhely Angoboy Ilondea; Dieu-Merci Assumani; Thales de Haulleville; Le Bienfaiteur Sagang; Laurent Durieux; Youngryel Ryu; Tackang Yang; Conan Vassily Obame; Thomas Bossy; Frédéric Frappart; Marc Peaucelle; Jean-Pierre Wigneron; Jerome Chave; Aida Cuni-Sanchez; Wannes Hubau; Hans Verbeeck; Pascal Boeckx; Jean-Remy Makana; Corneille Ewango; Elizabeth Kearsley; Bonaventure Sonké; Moses Libalah; Pierre Ploton

doi:10.3389/frsen.2025.1724950

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Satellite-based mapping of annual canopy height and aboveground biomass in African dense forests

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Satellite-based mapping of annual canopy height and aboveground biomass in African dense forests

Liang Wan, Philippe Ciais, Aurélien de Truchis, Ewan Sean, Fabian Jörg Fischer, David Purnell, Gabriel Belouze, Ibrahim Fayad, Ibrahim Fayad, Martin Schwartz, …

Frontiers in remote sensing, Vol.6

01/12/2025

DOI: https://doi.org/10.3389/frsen.2025.1724950

Résumé

aboveground biomass

African dense forests

forest height

GEDI

Sentinel-1

Sentinel-2

Accurate maps of canopy height (CH) and aboveground biomass (AGB) are needed for monitoring forests over large regions. Producing such data is particularly challenging over the complex, diverse and dense humid tropical forests of Africa where signal saturation observed from optical and radar satellites and complex responses in LiDAR data require advanced mapping techniques to capture high biomass and tall height values. Here, we trained a deep learning (U-Net) model to generate the first annual maps (2019–2022) of top CH at 10 m resolution over the African dense forest region, using Sentinel-1/-2 images trained on LiDAR-derived height data from the Global Ecosystem Dynamics Investigation mission (GEDI). To predict AGB from CH on a 30-m grid, we calibrated allometric models combining AGB data from field inventories, CH from our map, and wood density from a new high-resolution (1 km) map. The CH map has a mean absolute error (MAE) of 4.54 m and an underestimation bias of 1.54 m compared to independent airborne LiDAR data (5.93 m and 1.40 m compared to independent GEDI data). Evaluation of the AGB map against independent measurements from field sites suggests an improved accuracy (MAE = 79.65 Mg/ha, bias = 6.47 Mg/ha) compared to recent datasets such as ESA-CCI, NCEO, and GEDI L4B. Our map also captures the large-scale spatial gradients of AGB across African dense forests, as observed in a comprehensive dataset of forest concession measurements aggregated at a 1-km scale. Interpretable machine learning was used to assess the contribution of ancillary variables (e.g., climate, soil, forest type) to biomass prediction. While some variables were relevant, their inclusion failed to improve AGB estimates in high and low biomass extremes and introduced spatial artifacts, limiting their utility for consistent annual mapping. Together, our annual CH and AGB maps offer an open, scalable tool for monitoring forest disturbances and interannual biomass dynamics. Future work will focus on refining biomass–height relationships to further improve AGB estimation.

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Titre: Satellite-based mapping of annual canopy height and aboveground biomass in African dense forests
Créateurs - sans rôle: Liang Wan - Laboratoire des Sciences du Climat et de l'Environnement
Philippe Ciais - Laboratoire des Sciences du Climat et de l'Environnement
Aurélien de Truchis - Kayrros SAS, Paris, France
Ewan Sean - Kayrros SAS, Paris, France
Fabian Jörg Fischer - TUM School of Life Sciences, Ecosystem Dynamics and Forest Management, Technical University of Munich, Freising, Germany
David Purnell - Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris Saclay, Gif-sur-Yvette, France
Gabriel Belouze - Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris Saclay, Gif-sur-Yvette, France
Ibrahim Fayad - Laboratoire des Sciences du Climat et de l'Environnement
Ibrahim Fayad - Kayrros SAS, Paris, France
Martin Schwartz - Laboratoire des Sciences du Climat et de l'Environnement
Yidi Xu - Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris Saclay, Gif-sur-Yvette, France
Yang Su - Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris Saclay, Gif-sur-Yvette, France
Maxime Réjou-Méchain - AMAP, University Montpellier, IRD, CIRAD, CNRS, INRAE, Montpellier, France
Nicolas Barbier - AMAP, University Montpellier, IRD, CIRAD, CNRS, INRAE, Montpellier, France
Paul Tresson - AMAP, University Montpellier, IRD, CIRAD, CNRS, INRAE, Montpellier, France
Jean-François Bastin - TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Université de Liège, Gembloux, Belgium
Jan Bogaert - Gembloux Agro-Bio Tech
Arthur Vander Linden - TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Université de Liège, Gembloux, Belgium
Antoine Plumacker - TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Université de Liège, Gembloux, Belgium
Bhely Angoboy Ilondea - Institut National pour l’Etude et la Recherche Agronomiques, Kinshasa-Gombe, Democratic Republic of Congo
Bhely Angoboy Ilondea - Université Pédagogique Nationale, Kinshasa-Ngaliema, Democratic Republic of Congo
Dieu-Merci Assumani - Faculté de Gestion des Ressources Naturelles Renouvelables, Université de Kisangani, Kisangani, Democratic Republic of Congo
Dieu-Merci Assumani - Institut National pour l’Etude et la Recherche Agronomiques (INERA - Yangambi), Yangambi, Democratic Republic of Congo
Thales de Haulleville - Gembloux Agro-Bio Tech
Thales de Haulleville - 0Ghent University, Faculty of Bioscience Engineering, Department of Environment, Ghent, Belgium
Le Bienfaiteur Sagang - 1Institute of the Environment and Sustainability, UCLA, Los Angeles, CA, United States
Laurent Durieux - UAR Data Terra
Youngryel Ryu - Seoul National University
Tackang Yang - 4Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul, Republic of Korea
Conan Vassily Obame - 5Agence Gabonaise d’Etudes et d’Observations Spatiales (AGEOS), Libreville, Gabon
Thomas Bossy - Laboratoire des Sciences du Climat et de l'Environnement
Thomas Bossy - 6ISPA, UMR 1391 INRAE/Bordeaux Science Agro, Villenave d’Ornon, France
Frédéric Frappart - 6ISPA, UMR 1391 INRAE/Bordeaux Science Agro, Villenave d’Ornon, France
Marc Peaucelle - 6ISPA, UMR 1391 INRAE/Bordeaux Science Agro, Villenave d’Ornon, France
Jean-Pierre Wigneron - 6ISPA, UMR 1391 INRAE/Bordeaux Science Agro, Villenave d’Ornon, France
Jerome Chave - Institut National Polytechnique de Toulouse
Aida Cuni-Sanchez - Norwegian University of Life Sciences
Aida Cuni-Sanchez - 9Department of Environment and Geography, University of York, York, United Kingdom
Wannes Hubau - 0Ghent University, Faculty of Bioscience Engineering, Department of Environment, Ghent, Belgium
Wannes Hubau - 0Royal Museum for Central Africa, Service of Wood Biology, Tervuren, Belgium
Hans Verbeeck - Ghent University
Pascal Boeckx - 2Ghent University, Faculty of Bioscience Engineering, Department of Green Chemistry, Ghent, Belgium
Jean-Remy Makana - 3Université de Kisangani, Faculté des Sciences, Laboratoire d’écologie et aménagement forestier, Kisangani, Democratic Republic of Congo
Corneille Ewango - 4Université de Kisangani, Faculty of Renewable Natural Resources Management, Kisangani, Democratic Republic of Congo
Elizabeth Kearsley - 5BlueGreen Labs, Melsele, Belgium
Bonaventure Sonké - 6Plant Systematics and Ecology Laboratory, Higher Teachers’ Training College, University of Yaoundé I, Yaoundé, Cameroon
Moses Libalah - 6Plant Systematics and Ecology Laboratory, Higher Teachers’ Training College, University of Yaoundé I, Yaoundé, Cameroon
Pierre Ploton - AMAP, University Montpellier, IRD, CIRAD, CNRS, INRAE, Montpellier, France
Détails de publication: Frontiers in remote sensing, Vol.6
Éditeur: Frontiers Media S.A
Identifiants: 99149149409311
Unité académique: BotAnique et Modélisation de l'Architecture des Plantes et des végétations - AMAP
Langue: English
Type de ressource: Journal article