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Allometric equations for integrating remote sensing imagery into forest monitoring programmes.
Jucker, Tommaso; Caspersen, John; Chave, Jérôme; Antin, Cécile; Barbier, Nicolas; Bongers, Frans; Dalponte, Michele; van Ewijk, Karin Y; Forrester, David I; Haeni, Matthias; Higgins, Steven I; Holdaway, Robert J; Iida, Yoshiko; Lorimer, Craig; Marshall, Peter L; Momo, Stéphane; Moncrieff, Glenn R; Ploton, Pierre; Poorter, Lourens; Rahman, Kassim Abd; Schlund, Michael; Sonké, Bonaventure; Sterck, Frank J; Trugman, Anna T; Usoltsev, Vladimir A; Vanderwel, Mark C; Waldner, Peter; Wedeux, Beatrice M M; Wirth, Christian; Wöll, Hannsjörg; Woods, Murray; Xiang, Wenhua; Zimmermann, Niklaus E; Coomes, David A.
Afiliação
  • Jucker T; Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Cambridge, UK.
  • Caspersen J; Faculty of Forestry, University of Toronto, 33 Willcocks Street, Toronto, ON, M5S 3B3, Canada.
  • Chave J; Swiss Federal Research Institute WSL, Zürcherstrasse 111, Birmensdorf, 8903, Switzerland.
  • Antin C; Laboratoire Evolution et Diversité Biologique, UMR5174, CNRS/Université Paul Sabatier Bâtiment 4R1, 118 route de Narbonne, Toulouse, F-31062, France.
  • Barbier N; Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France.
  • Bongers F; Institut Français de Pondichéry, UMIFRE CNRS-MAE 21, Puducherry, India.
  • Dalponte M; Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France.
  • van Ewijk KY; Forest Ecology and Forest Management Group, Wageningen University, PO Box 47, AA Wageningen, 6700, the Netherlands.
  • Forrester DI; Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione E. Mach, Via E. Mach 1, San Michele all'Adige, 38010, Italy.
  • Haeni M; Department of Geography and Planning, Queen's University, Kingston, ON, Canada.
  • Higgins SI; Chair of Silviculture, Faculty of Environment and Natural Resources, Freiburg University, Tennenbacherstr. 4, Freiburg, 79108, Germany.
  • Holdaway RJ; Swiss Federal Research Institute WSL, Zürcherstrasse 111, Birmensdorf, 8903, Switzerland.
  • Iida Y; Department of Botany, University of Otago, PO Box 56, Dunedin, 9016, New Zealand.
  • Lorimer C; Landcare Research, PO Box 69040, Lincoln, 7640, New Zealand.
  • Marshall PL; Kyushu Research Center, Forestry and Forest Products Research Institute, Kumamoto, 860-0862, Japan.
  • Momo S; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA.
  • Moncrieff GR; Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada.
  • Ploton P; Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France.
  • Poorter L; Laboratoire de Botanique systématique et d'Ecologie, Département des Sciences Biologiques, Ecole Normale Supérieure, Université de Yaoundé I, Yaoundé, Cameroon.
  • Rahman KA; Fynbos Node, South African Environmental Observation Network (SAEON), Centre for Biodiversity Conservation, Kirstenbosch Gardens, Private Bag X7, Rhodes Drive, Claremont, Cape Town, 7735, South Africa.
  • Schlund M; Institut de Recherche pour le Développement, UMR AMAP, Montpellier, France.
  • Sonké B; Forest Ecology and Forest Management Group, Wageningen University, PO Box 47, AA Wageningen, 6700, the Netherlands.
  • Sterck FJ; Forest Research Institute of Malaysia, Kepong 52109, Selangor, Malaysia.
  • Trugman AT; Department of Earth Observation, Friedrich-Schiller University, Loebdergraben 32, Jena, 07743, Germany.
  • Usoltsev VA; Laboratoire de Botanique systématique et d'Ecologie, Département des Sciences Biologiques, Ecole Normale Supérieure, Université de Yaoundé I, Yaoundé, Cameroon.
  • Vanderwel MC; Forest Ecology and Forest Management Group, Wageningen University, PO Box 47, AA Wageningen, 6700, the Netherlands.
  • Waldner P; Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, 08544, USA.
  • Wedeux BM; Botanical Garden of the Russian Academy of Sciences (Ural branch), Russia and Ural State Forest Engineering University, Yekaterinburg, 620100, Russia.
  • Wirth C; Department of Biology, University of Regina, 3737 Wascana Pkwy, Regina, SK, S4S 0A2, Canada.
  • Wöll H; Swiss Federal Research Institute WSL, Zürcherstrasse 111, Birmensdorf, 8903, Switzerland.
  • Woods M; Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Cambridge, UK.
  • Xiang W; Systematic Botany and Functional Biodiversity, Institute of Biology, University of Leipzig, Leipzig, Germany.
  • Zimmermann NE; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
  • Coomes DA; Conservation and Natural Resources Management, Sommersbergseestr. 291, Bad Aussee, A-8990, Austria.
Glob Chang Biol ; 23(1): 177-190, 2017 01.
Article em En | MEDLINE | ID: mdl-27381364
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Florestas / Tecnologia de Sensoriamento Remoto / Ciclo do Carbono Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Florestas / Tecnologia de Sensoriamento Remoto / Ciclo do Carbono Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article