Assessing interannual variation in MODIS-based estimates of gross primary production

David P. Turner; William David Ritts; Maosheng Zhao; Shirley A. Kurc; Allison L. Dunn; Steven C. Wofsy; Eric E. Small; Steven W. Running

doi:10.1109/TGRS.2006.876027

Assessing interannual variation in MODIS-based estimates of gross primary production

David P. Turner
, William David Ritts
, Maosheng Zhao
, Shirley A. Kurc
, Allison L. Dunn
, Steven C. Wofsy
, Eric E. Small
, Steven W. Running

W. A. Franke College of Forestry and Conservation

Research output: Contribution to journal › Article › peer-review

96 Scopus citations

Abstract

Global estimates of terrestrial gross primary production (GPP) are now operationally produced from Moderate Resolution Imaging Spectrometer (MODIS) imagery at the 1-km spatial resolution and eight-day temporal resolution. In this study, MODIS GPP products were compared with ground-based GPP estimates over multiple years at three sites-a boreal conifer forest, a temperate deciduous forest, and a desert grassland. The ground-based estimates relied on measurements at eddy covariance flux towers, fine resolution remote sensing, and modeling. The MODIS GPP showed seasonal variation that was generally consistent with the in situ observations. The sign and magnitude of year-to-year variation in the MODIS products agreed with that of the ground observations at two of the three sites. Examination of the inputs to the MODIS GPP algorithm - notably the fraction of photosynthetically active radiation (FPAR) that is absorbed by the canopy), minimum temperature scalar, and vapor pressure deficit scalar-provided explanations for cases of disagreement between the MODIS and ground-based GPP estimates. Continued evaluation of interannual variation in MODIS products and related climate variables will aid in assessing potential biospheric feedbacks to climate change.

Original language	English
Article number	1645289
Pages (from-to)	1899-1907
Number of pages	9
Journal	IEEE Transactions on Geoscience and Remote Sensing
Volume	44
Issue number	7
DOIs	https://doi.org/10.1109/TGRS.2006.876027
State	Published - Jul 2006

Funding

Manuscript received October 1, 2004; revised January 23, 2006. This work was supported in part by the National Aeronautics and Space Administration (NASA) Terrestrial Ecology Program and in part by the Department of Energy, NASA, and the National Science Foundation (for the Flux tower measurements). D. P. Turner and W. D. Ritts are with the Department of Forest Science, Oregon State University, Corvallis, OR 97331 USA (e-mail: [email protected]). M. Zhao and S. W. Running are with the School of Forestry, University of Montana, Missoula, MT 59812 USA. S. A. Kurc and E. E. Small are with the Department of Geological Sciences, University of Colorado, Boulder, CO 80309 USA. A. L. Dunn and S. C. Wofsy are with the Department of Earth and Planetary Science, Harvard University, Cambridge, MA 02138 USA. Digital Object Identifier 10.1109/TGRS.2006.876027

Funders
National Aeronautics and Space Administration

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action
SDG 15 Life on Land

Keywords

Fraction of photosynthetically active radiation (FPAR)
Global ecology
Gross primary production (GPP)
Interannual variation
Modeling
Moderate Resolution Imaging Spectrometer (MODIS)
Remote sensing

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10.1109/TGRS.2006.876027

Cite this

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title = "Assessing interannual variation in MODIS-based estimates of gross primary production",

abstract = "Global estimates of terrestrial gross primary production (GPP) are now operationally produced from Moderate Resolution Imaging Spectrometer (MODIS) imagery at the 1-km spatial resolution and eight-day temporal resolution. In this study, MODIS GPP products were compared with ground-based GPP estimates over multiple years at three sites-a boreal conifer forest, a temperate deciduous forest, and a desert grassland. The ground-based estimates relied on measurements at eddy covariance flux towers, fine resolution remote sensing, and modeling. The MODIS GPP showed seasonal variation that was generally consistent with the in situ observations. The sign and magnitude of year-to-year variation in the MODIS products agreed with that of the ground observations at two of the three sites. Examination of the inputs to the MODIS GPP algorithm - notably the fraction of photosynthetically active radiation (FPAR) that is absorbed by the canopy), minimum temperature scalar, and vapor pressure deficit scalar-provided explanations for cases of disagreement between the MODIS and ground-based GPP estimates. Continued evaluation of interannual variation in MODIS products and related climate variables will aid in assessing potential biospheric feedbacks to climate change.",

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AB - Global estimates of terrestrial gross primary production (GPP) are now operationally produced from Moderate Resolution Imaging Spectrometer (MODIS) imagery at the 1-km spatial resolution and eight-day temporal resolution. In this study, MODIS GPP products were compared with ground-based GPP estimates over multiple years at three sites-a boreal conifer forest, a temperate deciduous forest, and a desert grassland. The ground-based estimates relied on measurements at eddy covariance flux towers, fine resolution remote sensing, and modeling. The MODIS GPP showed seasonal variation that was generally consistent with the in situ observations. The sign and magnitude of year-to-year variation in the MODIS products agreed with that of the ground observations at two of the three sites. Examination of the inputs to the MODIS GPP algorithm - notably the fraction of photosynthetically active radiation (FPAR) that is absorbed by the canopy), minimum temperature scalar, and vapor pressure deficit scalar-provided explanations for cases of disagreement between the MODIS and ground-based GPP estimates. Continued evaluation of interannual variation in MODIS products and related climate variables will aid in assessing potential biospheric feedbacks to climate change.

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Assessing interannual variation in MODIS-based estimates of gross primary production

Abstract

Funding

UN SDGs

Keywords

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