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dc.contributor.author Sims, Daniel A.
dc.contributor.author Rahman, Abdullah F.
dc.contributor.author Cordova, Vicente D.
dc.contributor.author El-Masri, Bassil Z.
dc.contributor.author Baldocchi, Dennis D.
dc.contributor.author Flanagan, Larry B.
dc.contributor.author Goldstein, Allen H.
dc.contributor.author Hollinger, David Y.
dc.contributor.author Misson, Laurent
dc.contributor.author Monson, Russell K.
dc.contributor.author Oechel, Walter C.
dc.contributor.author Schmid, Hans P.
dc.contributor.author Wofsy, Steven C.
dc.contributor.author Xu, Liukang
dc.date.accessioned 2019-08-27T20:01:43Z
dc.date.available 2019-08-27T20:01:43Z
dc.date.issued 2006
dc.identifier.citation Sims, D. A., Rahman, A. F., Cordova, V. D., El-Masri, B. Z., Baldocchi, D. D., Flanagan, L. B.,...Xu, Liukang. (2006). On the use of MODIS EVI to assess gross primary productivity of North American ecosystems. Journal of Geophysical Research (Biogeosciences), 111, G04015. doi:10.1029/2006JG000162 en_US
dc.identifier.uri https://hdl.handle.net/10133/5526
dc.description Sherpa Romeo green journal. Permission to archive final published version en_US
dc.description.abstract Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote-sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote-sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote-sensing data en_US
dc.language.iso en_US en_US
dc.publisher American Geophysical Union en_US
dc.subject Remote sensing en_US
dc.subject Flux modeling en_US
dc.subject Eddy covariance en_US
dc.subject Light use efficiency
dc.subject Enhanced vegetation index
dc.subject Gross primary productivity
dc.subject.lcsh Photosynthesis
dc.title On the use of MODIS EVI to assess gross primary productivity of North American ecosystems en_US
dc.type Article en_US
dc.publisher.faculty Arts and Science en_US
dc.publisher.department Department of Biological Sciences en_US
dc.description.peer-review Yes en_US
dc.publisher.institution Ball State University en_US
dc.publisher.institution Texas Tech University en_US
dc.publisher.institution University of California en_US
dc.publisher.institution University of Lethbridge en_US
dc.publisher.institution Northeastern Research Station en_US
dc.publisher.institution University of Colorado at Boulder en_US
dc.publisher.institution San Diego State University en_US
dc.publisher.institution Indiana University en_US
dc.publisher.institution Havard University en_US
dc.publisher.institution Licor Incorporated Environmental en_US
dc.publisher.url https://dx.doi.org/10.1029/2006JG000162


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