Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/117891
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- Title
- Assimilating earth observation data into land surface models
- Related
- International Geoscience and Remote Sensing Symposium (7 - 11 July 2008 : Boston, Mass.)
- Related
- 2008 IEEE International Geoscience & Remote Sensing Symposium : proceedings : July 6-11, 2008, John B. Hynes Veterans Memorial Convention Center, Boston, Massachusetts, U.S.A., Vol. 5, p.V-445-V-448
- DOI
- 10.1109/IGARSS.2008.4780124
- Publisher
- Piscataway, N.J : IEEE
- Date
- 2008
- FoR/RFCD Code(s)
-
040600 Physical Geography and Environmental Geoscience
090900 Geomatic Engineering
- Author/Creator
- Quaife, T
- Author/Creator
- Lewis, P
- Author/Creator
- De Kauwe, M
- Description
- Data assimilation techniques such as the ensemble Kalman filter and the sequential Metropolis-Hastings algorithm provide ameans of integrating satellite data with ecosystemmodels to optimally adjust their temporal trajectory. To some extent thesemethods can compensate for poor model parameterisations but a preferable scenario is to calibrate themodelwell in the first instance. This paper explores how a site specific model calibration can be adapted to a different site using only MODIS reflectance data. Results show that, using reflectance data only, estimates of the net carbon budget of a field site can be extended to a nearby site, but that this best facilitated by re-calibration rather than sequential data assimilation.
- Description
- 4 page(s)
- Subject Keyword
- 040600 Physical Geography and Environmental Geoscience
- Subject Keyword
- 090900 Geomatic Engineering
- Subject Keyword
- Bayesian
- Subject Keyword
- data assimilation
- Subject Keyword
- GORT
- Subject Keyword
- NEP
- Resource Type
- conference paper
- Organisation
- Macquarie University. Dept. of Biological Sciences
- Identifier
- http://hdl.handle.net/1959.14/117891
- Identifier
- ISBN:9781424428083
- Identifier
- mq-rm-2010001746
- Language
- eng
- Rights
- Copyright 2008 IEEE. Reprinted from 2008 IEEE International Geoscience & Remote Sensing Symposium : proceedings : July 6-11, 2008, John B. Hynes Veterans Memorial Convention Center, Boston, Massachusetts, U.S.A. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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