, Volume 168, Issue 4, pp 1147–1160 | Cite as

A universal airborne LiDAR approach for tropical forest carbon mapping

  • Gregory P. Asner
  • Joseph Mascaro
  • Helene C. Muller-Landau
  • Ghislain Vieilledent
  • Romuald Vaudry
  • Maminiaina Rasamoelina
  • Jefferson S. Hall
  • Michiel van Breugel
Ecosystem ecology - Original Paper


Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height–diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r 2  = 0.80, RMSE = 27.6 Mg C ha−1). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.


Biomass Carbon emissions Forest carbon Light detection and ranging Rain forest REDD Remote sensing 



We thank J. Jacobson, T. Kennedy-Bowdoin, D. Knapp, and the Carnegie Airborne Observatory team for collecting and processing airborne LiDAR data. We thank two anonymous reviewers, N. Buchmann and C. Körner, for comments that improved the manuscript. This study was supported by the Gordon and Betty Moore Foundation. Previous data collections were supported by the Moore Foundation, the John D. and Catherine T. MacArthur Foundation, the HSBC Climate Partnership, Air France, the Smithsonian Tropical Research Institute, the Government of Norway, the Secretaria Nacional de Ciencia, Tecnología e Innovación (SENACYT) of Panama, the Carnegie Institution, and an anonymous donor to the Agua Salud Project. The Carnegie Airborne Observatory is made possible by the W.M. Keck Foundation, the Gordon and Betty Moore Foundation, and William Hearst III.

Supplementary material

442_2011_2165_MOESM1_ESM.docx (147 kb)
Supplementary material 1 (DOCX 146 kb)


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Gregory P. Asner
    • 1
  • Joseph Mascaro
    • 1
    • 2
  • Helene C. Muller-Landau
    • 2
  • Ghislain Vieilledent
    • 3
    • 4
  • Romuald Vaudry
    • 5
  • Maminiaina Rasamoelina
    • 6
  • Jefferson S. Hall
    • 2
  • Michiel van Breugel
    • 2
  1. 1.Department of Global EcologyCarnegie Institution for ScienceStanfordUSA
  2. 2.Smithsonian Tropical Research InstitutePanamaRepublic of Panama
  3. 3.CIRAD, UR105 Forest Ecosystem Goods and ServicesMontpellier Cedex 5France
  4. 4.DRP Forêt et BiodiversitéAntananarivoMadagascar
  5. 5.GoodPlanet FoundationParisFrance
  6. 6.World Wide Fund for NatureAntananarivoMadagascar

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