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Allometric equations for integrating remote sensing imagery into forest monitoring programmes
Authors:Tommaso Jucker  John Caspersen  Jérôme Chave  Cécile Antin  Nicolas Barbier  Frans Bongers  Michele Dalponte  Karin Y van Ewijk  David I Forrester  Matthias Haeni  Steven I Higgins  Robert J Holdaway  Yoshiko Iida  Craig Lorimer  Peter L Marshall  Stéphane Momo  Glenn R Moncrieff  Pierre Ploton  Lourens Poorter  Kassim Abd Rahman  Michael Schlund  Bonaventure Sonké  Frank J Sterck  Anna T Trugman  Vladimir A Usoltsev  Mark C Vanderwel  Peter Waldner  Beatrice M M Wedeux  Christian Wirth  Hannsjörg Wöll  Murray Woods  Wenhua Xiang  Niklaus E Zimmermann  David A Coomes
Affiliation:1. Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Cambridge, UK;2. Faculty of Forestry, University of Toronto, Toronto, ON, Canada;3. Swiss Federal Research Institute WSL, Birmensdorf, Switzerland;4. Laboratoire Evolution et Diversité Biologique, UMR5174, CNRS/Université Paul Sabatier Batiment 4R1, Toulouse, France;5. Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France;6. Institut Fran?ais de Pondichéry, UMIFRE CNRS‐MAE 21, Puducherry, India;7. Forest Ecology and Forest Management Group, Wageningen University, AA Wageningen, the Netherlands;8. Department of Sustainable Agro‐ecosystems and Bioresources, Research and Innovation Centre, San Michele all'Adige, Italy;9. Department of Geography and Planning, Queen's University, Kingston, ON, Canada;10. Chair of Silviculture, Faculty of Environment and Natural Resources, Freiburg University, Freiburg, Germany;11. Department of Botany, University of Otago, Dunedin, New Zealand;12. Landcare Research, Lincoln, New Zealand;13. Kyushu Research Center, Forestry and Forest Products Research Institute, Kumamoto, Japan;14. Department of Forest and Wildlife Ecology, University of Wisconsin‐Madison, Madison, WI, USA;15. Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada;16. Laboratoire de Botanique systématique et d'Ecologie, Département des Sciences Biologiques, Ecole Normale Supérieure, Université de Yaoundé I, Yaoundé, Cameroon;17. Fynbos Node, South African Environmental Observation Network (SAEON), Centre for Biodiversity Conservation, Kirstenbosch Gardens, Cape Town, South Africa;18. Forest Research Institute of Malaysia, Selangor, Malaysia;19. Department of Earth Observation, Friedrich‐Schiller University, Jena, Germany;20. Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA;21. Botanical Garden of the Russian Academy of Sciences (Ural branch), Russia and Ural State Forest Engineering University, Yekaterinburg, Russia;22. Department of Biology, University of Regina, Regina, SK, Canada;23. Systematic Botany and Functional Biodiversity, Institute of Biology, University of Leipzig, Leipzig, Germany;24. German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig, Leipzig, Germany;25. Conservation and Natural Resources Management, Bad Aussee, Austria;26. Ontario Ministry of Natural Resources, North Bay, ON, Canada;27. Faculty of Life Science and Technology, Central South University of Forestry and Technology, Changsha, China
Abstract:Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large‐scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.
Keywords:aboveground biomass  airborne laser scanning  carbon mapping  crown architecture  height–  diameter allometry  stem diameter distributions
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