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Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass
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Joetzjer_et_al-2017-Geophysica ...
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FInal Published Version
Author
Joetzjer, E.Pillet, M.
Ciais, P.
Barbier, N.
Chave, J.
Schlund, M.
Maignan, Fabienne
Barichivich, J.
Luyssaert, S.
Hérault, B.
von Poncet, F.
Poulter, B.
Affiliation
Univ Arizona, Dept Ecol & Evolut BiolIssue Date
2017-07-16
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AMER GEOPHYSICAL UNIONCitation
Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass 2017, 44 (13):6823 Geophysical Research LettersJournal
Geophysical Research LettersRights
© 2017. American Geophysical Union. All Rights Reserved.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.Note
6 month embargo; published online: 11 July 2017ISSN
00948276Version
Final published versionSponsors
Gordon and Betty Moore Foundation NERC Consortium Grants "AMAZONICA" [NE/F005806/1]; Investissement d'Avenir [ANR-10-LABX-25-01, TULIP: ANR-10-LABX-0041, ANAEE-France: ANR-11-INBS-0001]; European Union Climate KIC grant FOREST Specific Grant [EIT/CLIMATE KIC/SGA2016/1CNES]; European Research Council Synergy grant [ERC-2013-SyG-610028 IMBALANCE]; (CR)2 Chile [CONICYT/FONDAP/15110009]Additional Links
http://doi.wiley.com/10.1002/2017GL074150ae974a485f413a2113503eed53cd6c53
10.1002/2017GL074150