Open AccessOn the use of MODIS EVI to assess gross primary productivity of North American ecosystems
Author(s) -
Sims Daniel A.,
Rahman Abdullah F.,
Cordova Vicente D.,
ElMasri Bassil Z.,
Baldocchi Dennis D.,
Flanagan Lawrence B.,
Goldstein Allen H.,
Hollinger David Y.,
Misson Laurent,
Monson Russell K.,
Oechel Walter C.,
Schmid Hans P.,
Wofsy Steven C.,
Xu Liukang
Publication year - 2006
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2006jg000162
Subject(s) - enhanced vegetation index , evergreen , eddy covariance , primary production , environmental science , atmospheric sciences , deciduous , vegetation (pathology) , climatology , flux (metallurgy) , leaf area index , ecosystem , ecology , normalized difference vegetation index , geology , vegetation index , medicine , materials science , pathology , metallurgy , biology
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.