On the use of MODIS EVI to assess gross primary productivity of North American ecosystems

[1] 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.

[1]  J. Monteith.  SOLAR RADIATION AND PRODUCTIVITY IN TROPICAL ECOSYSTEMS , 1972 .

[2]  David J. Hicks,et al.  The Ecology of Leaf Life Spans , 1982 .

[3]  Ray D. Jackson,et al.  Diurnal Patterns of Wheat Spectral Reflectances , 1983, IEEE Transactions on Geoscience and Remote Sensing.

[4]  R. D. Jackson,et al.  Sun-angle and canopy-architecture effects on the spectral reflectance of six wheat cultivars , 1985 .

[5]  F. Woodward.  Climate and plant distribution , 1987 .

[6]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[7]  S. Goward,et al.  Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model , 1992 .

[8]  Gérard Dedieu,et al.  Methodology for the estimation of terrestrial net primary production from remotely sensed data , 1994 .

[9]  J. Hunt,et al.  Relationship between woody biomass and PAR conversion efficiency for estimating net primary production from NDVI , 1994 .

[10]  José M. Paruelo,et al.  REGIONAL PATTERNS OF NORMALIZED DIFFERENCE VEGETATION INDEX IN NORTH AMERICAN SHRUBLANDS AND GRASSLANDS , 1995 .

[11]  C. Field,et al.  Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types , 1995 .

[12]  D. Baldocchi,et al.  CO2 fluxes over plant canopies and solar radiation: a review , 1995 .

[13]  J. Peñuelas,et al.  Assessment of photosynthetic radiation‐use efficiency with spectral reflectance , 1995 .

[14]  J. Peñuelas,et al.  Relationship between photosynthetic radiation-use efficiency of barley canopies and the photochemical reflectance index (PRI) , 1996 .

[15]  J. William Munger,et al.  Measurements of carbon sequestration by long‐term eddy covariance: methods and a critical evaluation of accuracy , 1996 .

[16]  John Moncrieff,et al.  Seasonal variation of carbon dioxide, water vapor, and energy exchanges of a boreal black spruce forest , 1997 .

[17]  J. Gamon,et al.  The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels , 1997, Oecologia.

[18]  Josep Peñuelas,et al.  Comparative field study of spring and summer leaf gas exchange and photobiology of the mediterranean trees Quercus ilex and Phillyrea latifolia , 1998 .

[19]  José M. Paruelo,et al.  Interannual variability of NDVI and its relationship to climate for North American shrublands and grasslands , 1998 .

[20]  E. Davidson,et al.  Seasonal patterns and environmental control of carbon dioxide and water vapour exchange in an ecotonal boreal forest , 1999 .

[21]  S. T. Gower,et al.  Direct and Indirect Estimation of Leaf Area Index, fAPAR, and Net Primary Production of Terrestrial Ecosystems , 1999 .

[22]  Hans Peter Schmid,et al.  Measurements of CO2 and energy fluxes over a mixed hardwood forest in the mid-western United States , 2000 .

[23]  Ye Qi,et al.  Effects of climate variability on the carbon dioxide, water, and sensible heat fluxes above a ponderosa pine plantation in the Sierra Nevada (CA) , 2000 .

[24]  T. A. Black,et al.  Remote sensing of photosynthetic-light-use efficiency of boreal forest , 2000 .

[25]  Martha C. Anderson,et al.  An analytical model for estimating canopy transpiration and carbon assimilation fluxes based on canopy light-use efficiency , 2000 .

[26]  Dar A. Roberts,et al.  Modeling spatially distributed ecosystem flux of boreal forest using hyperspectral indices from AVIRIS imagery , 2001 .

[27]  R. Monson,et al.  Carbon sequestration in a high‐elevation, subalpine forest , 2001 .

[28]  D. Whitehead,et al.  The photochemical reflectance index as a measure of photosynthetic light use efficiency for plants with varying foliar nitrogen contents , 2002 .

[29]  Lawrence B. Flanagan,et al.  Seasonal and interannual variation in evapotranspiration, energy balance and surface conductance in a northern temperate grassland , 2002 .

[30]  Hans Peter Schmid,et al.  Footprint modeling for vegetation atmosphere exchange studies: a review and perspective , 2002 .

[31]  Lawrence B. Flanagan,et al.  Seasonal and interannual variation in carbon dioxide exchange and carbon balance in a northern temperate grassland , 2002 .

[32]  Caroline J. Nichol,et al.  Remote sensing of photosynthetic-light-use efficiency of a Siberian boreal forest , 2002 .

[33]  Markus Reichstein,et al.  Ecosystem respiration in two Mediterranean evergreen Holm Oak forests: drought effects and decomposition dynamics , 2002 .

[34]  Elizabeth Pattey,et al.  Impact of nitrogen and environmental conditions on corn as detected by hyperspectral reflectance , 2002 .

[35]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[36]  A. Arneth,et al.  Remote sensing of photosynthetic-light-use efficiency of a Siberian boreal forest , 2002 .

[37]  W. Oechel,et al.  Seasonal patterns of reflectance indices, carotenoid pigments and photosynthesis of evergreen chaparral species , 2002, Oecologia.

[38]  Emilio A. Laca,et al.  Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem , 2003 .

[39]  W. Cohen,et al.  Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation , 2003 .

[40]  John E. Erickson,et al.  Foliar morphology and canopy nitrogen as predictors of light-use efficiency in terrestrial vegetation , 2003 .

[41]  Brent N. Holben,et al.  Accuracy of the AVHRR vegetation index as a predictor of biomass, primary productivity and net CO2 flux , 1989, Vegetatio.

[42]  Christopher B. Field,et al.  Assessing photosynthetic downregulation in sunflower stands with an optically-based model , 2004, Photosynthesis Research.

[43]  E. Davidson,et al.  Satellite-based modeling of gross primary production in an evergreen needleleaf forest , 2004 .

[44]  Dennis D. Baldocchi,et al.  Seasonal variation in carbon dioxide exchange over a Mediterranean annual grassland in California , 2004 .

[45]  Hans Peter Schmid,et al.  Potential of MODIS ocean bands for estimating CO2 flux from terrestrial vegetation: A novel approach , 2004 .

[46]  S. Wofsy,et al.  Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data , 2004 .

[47]  E. Davidson,et al.  Spatial and temporal variability in forest–atmosphere CO2 exchange , 2004 .

[48]  C. Tucker,et al.  North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer , 1985, Vegetatio.

[49]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[50]  S. Frolking,et al.  Satellite-based modeling of gross primary production in a seasonally moist tropical evergreen forest , 2005 .

[51]  W. Cohen,et al.  Site‐level evaluation of satellite‐based global terrestrial gross primary production and net primary production monitoring , 2005 .

[52]  S. Wofsy,et al.  Midday values of gross CO2 flux and light use efficiency during satellite overpasses can be used to directly estimate eight-day mean flux , 2005 .

[53]  Maosheng Zhao,et al.  Improvements of the MODIS terrestrial gross and net primary production global data set , 2005 .

[54]  D. Sims,et al.  Potential of MODIS EVI and surface temperature for directly estimating per‐pixel ecosystem C fluxes , 2005 .

[55]  Maosheng Zhao,et al.  Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses , 2006 .

[56]  D. Roberts,et al.  Use of Hyperspectral Reflectance Indices for Estimation of Gross Carbon Flux and light use Efficiency Crossdiverse Vegetation Types , 2006 .

[57]  W. Oechel,et al.  Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem , 2006 .

[58]  Ramakrishna R. Nemani,et al.  Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations , 2006, IEEE Transactions on Geoscience and Remote Sensing.