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Surveys in Geophysics

, Volume 40, Issue 4, pp 881–911 | Cite as

Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them

  • Maxime Réjou-MéchainEmail author
  • Nicolas Barbier
  • Pierre Couteron
  • Pierre Ploton
  • Grégoire Vincent
  • Martin Herold
  • Stéphane Mermoz
  • Sassan Saatchi
  • Jérôme Chave
  • Florian de Boissieu
  • Jean-Baptiste Féret
  • Stéphane Momo Takoudjou
  • Raphaël Pélissier
Article

Abstract

Forest biomass monitoring is at the core of the research agenda due to the critical importance of forest dynamics in the carbon cycle. However, forest biomass is never directly measured; thus, upscaling it from trees to stand or larger scales (e.g., countries, regions) relies on a series of statistical models that may propagate large errors. Here, we review the main steps usually adopted in forest aboveground biomass mapping, highlighting the major challenges and perspectives. We show that there is room for improvement along the scaling-up chain from field data collection to satellite-based large-scale mapping, which should lead to the adoption of effective practices to better control the propagation of errors. We specifically illustrate how the increasing use of emerging technologies to collect massive amounts of high-quality data may significantly improve the accuracy of forest carbon maps. Furthermore, we discuss how sources of spatially structured biases that directly propagate into remote sensing models need to be better identified and accounted for when extrapolating forest carbon estimates, e.g., through a stratification design. We finally discuss the increasing realism of 3D simulated stands, which, through radiative transfer modelling, may contribute to a better understanding of remote sensing signals and open avenues for the direct calibration of large-scale products, thereby circumventing several current difficulties.

Keywords

Biomass Calibration Carbon Error propagation Field data Modelling 

Notes

Acknowledgements

We gratefully thank the organizers of the Workshop held at ISSI Bern in November 2017 that was at the origin of this Special Issue. This review has been conducted under the project 3DForMod funded by ERA-GAS (ANR-17-EGAS-0002-01, NWO-3DForMod-5160957540) and has also benefited from the “Investissement d’Avenir” programs managed by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01).

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Maxime Réjou-Méchain
    • 1
    Email author
  • Nicolas Barbier
    • 1
  • Pierre Couteron
    • 1
  • Pierre Ploton
    • 1
  • Grégoire Vincent
    • 1
  • Martin Herold
    • 2
  • Stéphane Mermoz
    • 3
    • 8
  • Sassan Saatchi
    • 4
  • Jérôme Chave
    • 5
  • Florian de Boissieu
    • 6
  • Jean-Baptiste Féret
    • 6
  • Stéphane Momo Takoudjou
    • 1
    • 7
  • Raphaël Pélissier
    • 1
  1. 1.AMAP, IRD, CNRS, CIRAD, INRAUniv MontpellierMontpellier Cedex 05France
  2. 2.Laboratory of Geo-Information Science and Remote SensingWageningen University and ResearchWageningenThe Netherlands
  3. 3.CESBIO, CNES/CNRS, IRD/UPSUniversité de ToulouseToulouseFrance
  4. 4.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA
  5. 5.CNRS, ENFA; UMR5174 EDB (Laboratoire Evolution et Diversité Biologique)Université Paul SabatierToulouseFrance
  6. 6.TETIS, Irstea, AgroParisTech, CIRAD, CNRSUniversity of MontpellierMontpellierFrance
  7. 7.Plant Systematic and Ecology Laboratory, Higher Teacher’s Training CollegeUniversity of Yaoundé IYaoundéCameroon
  8. 8.GlobEOToulouseFrance

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