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

Author:

Rodda Suraj Reddy,Fararoda Rakesh,Gopalakrishnan Rajashekar,Jha Nidhi,Réjou-Méchain MaximeORCID,Couteron Pierre,Barbier NicolasORCID,Alfonso AlonsoORCID,Bako Ousmane,Bassama Patrick,Behera DebabrataORCID,Bissiengou Pulcherie,Biyiha Hervé,Brockelman Warren Y.,Chanthorn Wirong,Chauhan Prakash,Dadhwal Vinay KumarORCID,Dauby GillesORCID,Deblauwe VincentORCID,Dongmo Narcis,Droissart VincentORCID,Jeyakumar Selvaraj,Jha Chandra Shekar,Kandem Narcisse G.,Katembo John,Kougue Ronald,Leblanc Hugo,Lewis SimonORCID,Libalah Moses,Manikandan Maya,Martin-Ducup OlivierORCID,Mbock Germain,Memiaghe Hervé,Mofack Gislain,Mutyala Praveen,Narayanan Ayyappan,Nathalang Anuttara,Ndjock Gilbert Oum,Ngoula Fernandez,Nidamanuri Rama Rao,Pélissier RaphaëlORCID,Saatchi Sassan,Sagang Le Bienfaiteur,Salla Patrick,Simo-Droissart MurielleORCID,Smith Thomas B.,Sonké Bonaventure,Stevart Tariq,Tjomb Danièle,Zebaze DonatienORCID,Zemagho Lise,Ploton PierreORCID

Abstract

AbstractAccurate 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).

Funder

Indian Space Research Organisation

Institut de Recherche pour le Développement

Publisher

Springer Science and Business Media LLC

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