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Allometric equations for integrating remote sensing imagery into forest monitoring programmes.

Authors :
Jucker T
Caspersen J
Chave J
Antin C
Barbier N
Bongers F
Dalponte M
van Ewijk KY
Forrester DI
Haeni M
Higgins SI
Holdaway RJ
Iida Y
Lorimer C
Marshall PL
Momo S
Moncrieff GR
Ploton P
Poorter L
Rahman KA
Schlund M
Sonké B
Sterck FJ
Trugman AT
Usoltsev VA
Vanderwel MC
Waldner P
Wedeux BM
Wirth C
Wöll H
Woods M
Xiang W
Zimmermann NE
Coomes DA
Source :
Global change biology [Glob Chang Biol] 2017 Jan; Vol. 23 (1), pp. 177-190. Date of Electronic Publication: 2016 Jul 06.
Publication Year :
2017

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.<br /> (© 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

Details

Language :
English
ISSN :
1365-2486
Volume :
23
Issue :
1
Database :
MEDLINE
Journal :
Global change biology
Publication Type :
Academic Journal
Accession number :
27381364
Full Text :
https://doi.org/10.1111/gcb.13388