reflectance, daytime and nighttime LST, EVI, LAI, and fPAR over the period
2000–2006. The processing of these subsets has been described in detail by Xiao
et al. (2008). Average values were extracted for the central 3 9 3 km area within
the 7 9 7 km cutouts to better represent the flux tower footprint (Rahman et al.
2005; Xiao et al. 2008). For each variable, the quality of the value of each pixel
within the area was determined using the quality assurance (QA) flags included in
the product. Each 16-day EVI value was used for the two 8-day intervals corresponding with the compositing interval of other MODIS data products. NDWI was
calculated from band 2 and band 6 of the surface reflectance product.
Wall-to-wall MODIS data (Collection 5) including surface reflectance, daytime
and nighttime LST, LAI, and EVI with 1 km spatial resolution were used for the
estimation of NEE at the continental scale. These data were obtained from
NASA’s Warehouse Inventory Search Tool (WIST) for the period from March
2000 to December 2009. Similarly, for each variable, the quality of the value of
each pixel was determined using the QA flags and replaced the bad-quality value
using a linear interpolation approach (Zhao et al. 2005). The NDWI was calculated
from band 2 (near-infrared, 841–876 nm) and band 6 (shortwave infrared,
1628–1652 nm) of the surface reflectance product (MOD09A1). Each 16-day EVI
composite was used for two 8-day intervals corresponding to the compositing
interval of other MODIS products.
The 1 km MODIS land cover map (Friedl et al. 2002; Fig. 6.1) is used to
specify the vegetation type of each cell across the conterminous U.S. The land
cover map is based on the University of Maryland (UMD) classification scheme.
The vegetation classes of the land cover map are reclassified to seven broad
classes: evergreen forests, deciduous forests, mixed forests, shrublands, savannas,
grasslands, and croplands.
6.3.3 PAR Data
Gridded PAR data were obtained from the Modern Era Retrospective-Analysis for
Research and Applications (MERRA) reanalysis data set. The MERRA time
period covers the modern era of remotely sensed data from 1979 through the
present. MERRA makes use of observations from NASA’s Earth Observing
System satellites and reduce the uncertainty in precipitation and interannual
variability by improving the representation of the water cycle in reanalyses
(Rienecker et al. 2011). MERRA data were obtained from the Global Modeling
and Assimilation Office (GMAO; http://gmao.gsfc.nasa.gov/). This data set has a
spatial resolution of 0.5° 9 0.667°. The PAR data were resampled to 1 km spatial
resolution to match the resolution of other explanatory variables.
6 Assessing Net Ecosystem Exchange
155
2000–2006. The processing of these subsets has been described in detail by Xiao
et al. (2008). Average values were extracted for the central 3 9 3 km area within
the 7 9 7 km cutouts to better represent the flux tower footprint (Rahman et al.
2005; Xiao et al. 2008). For each variable, the quality of the value of each pixel
within the area was determined using the quality assurance (QA) flags included in
the product. Each 16-day EVI value was used for the two 8-day intervals corresponding with the compositing interval of other MODIS data products. NDWI was
calculated from band 2 and band 6 of the surface reflectance product.
Wall-to-wall MODIS data (Collection 5) including surface reflectance, daytime
and nighttime LST, LAI, and EVI with 1 km spatial resolution were used for the
estimation of NEE at the continental scale. These data were obtained from
NASA’s Warehouse Inventory Search Tool (WIST) for the period from March
2000 to December 2009. Similarly, for each variable, the quality of the value of
each pixel was determined using the QA flags and replaced the bad-quality value
using a linear interpolation approach (Zhao et al. 2005). The NDWI was calculated
from band 2 (near-infrared, 841–876 nm) and band 6 (shortwave infrared,
1628–1652 nm) of the surface reflectance product (MOD09A1). Each 16-day EVI
composite was used for two 8-day intervals corresponding to the compositing
interval of other MODIS products.
The 1 km MODIS land cover map (Friedl et al. 2002; Fig. 6.1) is used to
specify the vegetation type of each cell across the conterminous U.S. The land
cover map is based on the University of Maryland (UMD) classification scheme.
The vegetation classes of the land cover map are reclassified to seven broad
classes: evergreen forests, deciduous forests, mixed forests, shrublands, savannas,
grasslands, and croplands.
6.3.3 PAR Data
Gridded PAR data were obtained from the Modern Era Retrospective-Analysis for
Research and Applications (MERRA) reanalysis data set. The MERRA time
period covers the modern era of remotely sensed data from 1979 through the
present. MERRA makes use of observations from NASA’s Earth Observing
System satellites and reduce the uncertainty in precipitation and interannual
variability by improving the representation of the water cycle in reanalyses
(Rienecker et al. 2011). MERRA data were obtained from the Global Modeling
and Assimilation Office (GMAO; http://gmao.gsfc.nasa.gov/). This data set has a
spatial resolution of 0.5° 9 0.667°. The PAR data were resampled to 1 km spatial
resolution to match the resolution of other explanatory variables.
6 Assessing Net Ecosystem Exchange
155