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From small-scale forest structure to Amazon-wide carbon estimates

Author

Listed:
  • Edna Rödig

    (UFZ - Helmholtz Centre for Environmental Research
    UFZ - Helmholtz Centre for Environmental Research)

  • Nikolai Knapp

    (UFZ - Helmholtz Centre for Environmental Research)

  • Rico Fischer

    (UFZ - Helmholtz Centre for Environmental Research)

  • Friedrich J. Bohn

    (UFZ - Helmholtz Centre for Environmental Research)

  • Ralph Dubayah

    (University of Maryland, College Park)

  • Hao Tang

    (University of Maryland, College Park)

  • Andreas Huth

    (UFZ - Helmholtz Centre for Environmental Research
    University of Osnabrück
    German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig)

Abstract

Tropical forests play an important role in the global carbon cycle. High-resolution remote sensing techniques, e.g., spaceborne lidar, can measure complex tropical forest structures, but it remains a challenge how to interpret such information for the assessment of forest biomass and productivity. Here, we develop an approach to estimate basal area, aboveground biomass and productivity within Amazonia by matching 770,000 GLAS lidar (ICESat) profiles with forest simulations considering spatial heterogeneous environmental and ecological conditions. This allows for deriving frequency distributions of key forest attributes for the entire Amazon. This detailed interpretation of remote sensing data improves estimates of forest attributes by 20–43% as compared to (conventional) estimates using mean canopy height. The inclusion of forest modeling has a high potential to close a missing link between remote sensing measurements and the 3D structure of forests, and may thereby improve continent-wide estimates of biomass and productivity.

Suggested Citation

  • Edna Rödig & Nikolai Knapp & Rico Fischer & Friedrich J. Bohn & Ralph Dubayah & Hao Tang & Andreas Huth, 2019. "From small-scale forest structure to Amazon-wide carbon estimates," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13063-y
    DOI: 10.1038/s41467-019-13063-y
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    Cited by:

    1. Henniger, Hans & Huth, Andreas & Frank, Karin & Bohn, Friedrich J., 2023. "Creating virtual forests around the globe and analysing their state space," Ecological Modelling, Elsevier, vol. 483(C).

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