LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa

Suraj Reddy Rodda (1, 2) , Rakesh Fararoda (1) , Rajashekar Gopalakrishnan (1) , Nidhi Jha (3) , Maxime Réjou-Méchain (4) , Pierre Couteron (4) , Nicolas Barbier (4) , Alonso Alfonso (5) , Ousmane Bako (6) , Patrick Bassama (6) , Debabrata Behera (7) , Pulcherie Bissiengou (8) , Hervé Biyiha (6) , Warren Y Brockelman (9) , Wirong Chanthorn (10) , Prakash Chauhan (1) , Vinay Kumar Dadhwal (11) , Gilles Dauby (4) , Vincent Deblauwe (12, 13) , Narcis Dongmo (6) , Vincent Droissart (4) , Selvaraj Jeyakumar (7) , Chandra Shekar Jha (14) , Narcisse G Kandem , John Katembo , Ronald Kougue , Hugo Leblanc (4) , Simon Lewis , Moses Libalah , Maya Manikandan , Olivier Martin-Ducup (15) , Germain Mbock , Hervé Memiaghe , Gislain Mofack , Praveen Mutyala , Ayyappan Narayanan (7) , Anuttara Nathalang , Gilbert Oum Ndjock , Fernandez Ngoula , Rama Rao Nidamanuri , Raphaël Pélissier (4) , Sassan Saatchi , Le Bienfaiteur Sagang , Patrick Salla , Murielle Simo-Droissart (16) , Thomas B Smith (13) , Bonaventure Sonké (17, 18) , Tariq Stevart (19) , Danièle Tjomb (6) , Donatien Zebaze (17) , Lise Zemagho (17) , Pierre Ploton (4)

1 ISRO - Indian Space Research Organisation
2 IIST - Indian Institute of Space and Science Technology
3 OSU - Oregon State University
4 UMR AMAP - Botanique et Modélisation de l'Architecture des Plantes et des Végétations
5 Smithsonian Conservation Biology Institute
6 Ecole Nationale des Eaux et Forêts de Mbalmayo
7 IFP - Institut Français de Pondichéry
8 Herbier National du Gabon,
9 Sirindhorn International Institute of Technology, Klong Luang, Pathumthani 12121, Thailand
10 KU - Kasetsart University [Bangkok, Thailand]
11 NIAS - National Institute of Advanced Studies
12 IITA-Cameroon - International Institute of Tropical Agriculture
13 UCLA - University of California [Los Angeles]
14 IIT Hyderabad - Indian Institute of Technology [Hyderabad]
15 URFM - Ecologie des Forêts Méditerranéennes
16 University of Yaoundé [Cameroun]
17 UY1 - Université de Yaoundé I
18 International Joint Laboratory DYCOFAC
19 Missouri Botanical Garden

Accurate mapping and monitoring of tropical forests aboveground biomass (AGB) is crucial to design effective carbon emission reduction strategies and improving our understanding of Earth’s carbon cycle. However, existing large-scale maps of tropical forest AGB generated through combinations of Earth Observation (EO) and forest inventory data show markedly divergent estimates, even after accounting for reported uncertainties. To address this, a network of high-quality reference data is needed to calibrate and validate mapping algorithms. This study aims to generate reference AGB datasets using field inventory plots and airborne LiDAR data for eight sites in Central Africa and five sites in South Asia, two regions largely underrepresented in global reference AGB datasets. The study provides access to these reference AGB maps, including uncertainty maps, at 100 m and 40 m spatial resolutions covering a total LiDAR footprint of 1,11,650 ha [ranging from 150 to 40,000 ha at site level]. These maps serve as calibration/validation datasets to improve the accuracy and reliability of AGB mapping for current and upcoming EO missions (viz., GEDI, BIOMASS, and NISAR).

Mots clés: Carbon capture and storage; Forestry

Domaines: Sciences de l'environnement

Suraj Reddy Rodda, Rakesh Fararoda, Rajashekar Gopalakrishnan, Nidhi Jha, Maxime Réjou-Méchain, et al.. LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa. Scientific Data , 2024, 11, pp.334. ⟨10.1038/s41597-024-03162-x⟩. ⟨hal-04540481⟩