@article {KNZ001152,
	title = {Evaluation of MODIS NPP and GPP products across multiple biomes},
	journal = {Remote Sensing of Environment},
	volume = {102},
	year = {2006},
	pages = {282 -292},
	abstract = {Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of NPP over the surrounding landscape offer opportunities for validating the MODIS NPP and GPP products, but these flux measurements must be scaled over areas on the order of 25 km2 to make effective comparisons to the MODIS products. Here, we report results for such comparisons at 9 sites varying widely in biome type and land use. The sites included arctic tundra, boreal forest, temperate hardwood forest, temperate conifer forest, tropical rain forest, tallgrass prairie, desert grassland, and cropland. The ground-based NPP and GPP surfaces were generated by application of the Biome-BGC carbon cycle process model in a spatially-distributed mode. Model inputs of land cover and leaf area index were derived from Landsat data. The MODIS NPP and GPP products showed no overall bias. They tended to be overestimates at low productivity sites {\textemdash} often because of artificially high values of MODIS FPAR (fraction of photosynthetically active radiation absorbed by the canopy), a critical input to the MODIS GPP algorithm. In contrast, the MODIS products tended to be underestimates in high productivity sites {\textemdash} often a function of relatively low values for vegetation light use efficiency in the MODIS GPP algorithm. A global network of sites where both NPP and GPP are measured and scaled over the local landscape is needed to more comprehensively validate the MODIS NPP and GPP products and to potentially calibrate the MODIS NPP/GPP algorithm parameters.},
	keywords = {LTER-KNZ, biomes, Global, Gross primary production, Landsat, MODIS, Monitoring, Net primary production, Validation},
	doi = {10.1016/j.rse.2006.02.017},
	author = {Turner, D.P. and Ritts, W.D. and Cohen, W.B. and Gower, S.T. and Running, SW. and Zhao, M. and Costa, M.H. and Kirschbaum, A. and J.M. Ham and Saleska, S. and Ahl, D.E.}
}
@article {KNZ001153,
	title = {MODIS land cover and LAI collection 4 product quality across nine sites in the western hemisphere},
	journal = {IEEE Transactions in Geosciences and Remote Sensing},
	volume = {44},
	year = {2006},
	pages = {1843 -1857},
	abstract = {Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS products. We present an updated BigFoot project protocol for developing 25-m validation data layers over 49-km2 study areas. Results from comparisons of MODIS and BigFoot land cover and LAI products at nine contrasting sites are reported. In terms of proportional coverage, MODIS and BigFoot land cover were in close agreement at six sites. The largest differences were at low tree cover evergreen needleleaf sites and at an Arctic tundra site where the MODIS product overestimated woody cover proportions. At low leaf biomass sites there was reasonable agreement between MODIS and BigFoot LAI products, but there was not a particular MODIS LAI algorithm pathway that consistently compared most favorably. At high leaf biomass sites, MODIS LAI was generally overpredicted by a significant amount. For evergreen needleleaf sites, LAI seasonality was exaggerated by MODIS. Our results suggest incremental improvement from Collection 3 to Collection 4 MODIS products, with some remaining problems that need to be addressed},
	keywords = {LTER-KNZ},
	doi = {10.1109/TGRS.2006.876026},
	author = {Cohen, W.B. and Maiersperger, T.K. and Turner, D.P. and Ritts, W.D. and Pflugmacher, D. and Kennedy, R.E. and Kirschbaum, A. and Running, S.W. and Costa, M. and Gower, S.T.}
}
@article {KNZ001151,
	title = {Comparison of hyperspectral and multispectral data for estimating leaf area index in four biomes},
	journal = {Remote Sensing of Environment},
	volume = {91},
	year = {2004},
	pages = {508 -520},
	abstract = {Motivated by the increasing importance of hyperspectral remote sensing data, this study sought to determine whether current-generation narrow-band hyperspectral remote sensing data could better track vegetation leaf area index (LAI) than traditional broad-band multispectral data. The study takes advantage of a unique dataset, wherein field measurements of LAI were acquired at the same general time and grain size as both Landsat ETM+ and AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) imagery in four different biomes. Biome types sampled included row-crop agriculture, tallgrass prairie, mixed hardwood-conifer forest, and boreal conifer forest. The effects of bandwidth, band placement, and number of bands were isolated from radiometric quality by comparing regression models derived from individual AVIRIS channels with those derived from simulated ETM+ and MODIS channels using the AVIRIS data. Models with selected subsets of individual AVIRIS channels performed better to predict LAI than those based on the broadband datasets, although the potential to overfit models using the large number of available AVIRIS bands is a concern. Models based on actual ETM+ data were generally stronger than those based on simulated ETM+ data, suggesting that, for predicting LAI, ETM+ data suffer no penalty for having lower radiometric quality. NDVI was generally not sensitive to LAI at the four sites. Band placement of broad-band sensors (e.g., simulated ETM+ and MODIS) did not affect relationships with LAI, suggesting that there is no inherent advantage to MODIS spectral properties over those of ETM+ for estimating LAI. Spectral channels in the red-edge and shortwave-infrared regions were generally more important than those in the near-infrared for predicting LAI.},
	keywords = {LTER-KNZ, Hyperspectral, LAI, Multispectral},
	doi = {10.1016/j.rse.2004.04.010},
	author = {Lee, K-S. and Cohen, W.B. and Kennedy, R.E. and Maiersperger, T.K. and Gower, S.T.}
}
@article {KNZ001150,
	title = {Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS products},
	journal = {Remote Sensing of Environment},
	volume = {88},
	year = {2003},
	pages = {221 -362},
	abstract = {The MODIS land science team produces a number of standard products, including land cover and leaf area index (LAI). Critical to the success of MODIS and other sensor products is an independent evaluation of product quality. In that context, we describe a study using field data and Landsat ETM+ to map land cover and LAI at four 49-km2 sites in North America containing agricultural cropland (AGRO), prairie grassland (KONZ), boreal needleleaf forest, and temperate mixed forest. The purpose was to: (1) develop accurate maps of land cover, based on the MODIS IGBP (International Geosphere{\textendash}Biosphere Programme) land cover classification scheme; (2) derive continuous surfaces of LAI that capture the mean and variability of the LAI field measurements; and (3) conduct initial MODIS validation exercises to assess the quality of early (i.e., provisional) MODIS products. ETM+ land cover maps varied in overall accuracy from 81\% to 95\%. The boreal forest was the most spatially complex, had the greatest number of classes, and the lowest accuracy. The intensive agricultural cropland had the simplest spatial structure, the least number of classes, and the highest overall accuracy. At each site, mapped LAI patterns generally followed patterns of land cover across the site. Predicted versus observed LAI indicated a high degree of correspondence between field-based measures and ETM+ predictions of LAI. Direct comparisons of ETM+ land cover maps with Collection 3 MODIS cover maps revealed several important distinctions and similarities. One obvious difference was associated with image/map resolution. ETM+ captured much of the spatial complexity of land cover at the sites. In contrast, the relatively coarse resolution of MODIS did not allow for that level of spatial detail. Over the extent of all sites, the greatest difference was an overprediction by MODIS of evergreen needleleaf forest cover at the boreal forest site, which consisted largely of open shrubland, woody savanna, and savanna. At the agricultural, temperate mixed forest, and prairie grassland sites, ETM+ and MODIS cover estimates were similar. Collection 3 MODIS-based LAI estimates were considerably higher (up to 4 m2 m-2) than those based on ETM+ LAI at each site. There are numerous probable reasons for this, the most important being the algorithms{\textquoteright} sensitivity to MODIS reflectance calibration, its use of a prelaunch AVHRR-based land cover map, and its apparent reliance on mainly red and near-IR reflectance. Samples of Collection 4 LAI products were examined and found to consist of significantly improved LAI predictions for KONZ, and to some extent for AGRO, but not for the other two sites. In this study, we demonstrate that MODIS reflectance data are highly correlated with LAI across three study sites, with relationships increasing in strength from 500 to 1000 m spatial resolution, when shortwave-infrared bands are included.},
	keywords = {LTER-KNZ, BigFoot, ETM, IGBP, Land cover, Leaf area index, MODIS, Validation},
	doi = {10.1016/j.rse.2003.06.006},
	author = {Cohen, W.B. and Maiersperger, T.K. and Yang, Z. and Gower, S.T. and Turner, D.P. and Ritts, W.D. and Berterretche, M. and Running, S.W.}
}
@article {KNZ00860,
	title = {A cross-biome comparison of daily light use efficiency for gross primary production},
	journal = {Global Change Biology},
	volume = {9},
	year = {2003},
	pages = {383 -395},
	abstract = {Vegetation light use efficiency is a key physiological parameter at the canopy scale, and at the daily time step is a component of remote sensing algorithms for scaling gross primary production (GPP) and net primary production (NPP) over regional to global domains. For the purposes of calibrating and validating the light use efficiency (εg) algorithms, the components of εg{\textendash} absorbed photosynthetically active radiation (APAR) and ecosystem GPP {\textendash} must be measured in a variety of environments. Micrometeorological and mass flux measurements at eddy covariance flux towers can be used to estimate APAR and GPP, and the emerging network of flux tower sites offers the opportunity to investigate spatial and temporal patterns in εg at the daily time step. In this study, we examined the relationship of daily GPP to APAR, and relationships of εg to climatic variables, at four micrometeorological flux tower sites {\textendash} an agricultural field, a tallgrass prairie, a deciduous forest, and a boreal forest. The relationship of GPP to APAR was close to linear at the tallgrass prairie site but more nearly hyperbolic at the other sites. The sites differed in the mean and range of daily εg, with higher values associated with the agricultural field than the boreal forest. εg decreased with increasing APAR at all sites, a function of mid-day saturation of GPP and higher εg under overcast conditions. εg was generally not well correlated with vapor pressure deficit or maximum daily temperature. At the agricultural site, a εg decline towards the end of the growing season was associated with a decrease in foliar nitrogen concentration. At the tallgrass prairie site, a decline in εg in August was associated with soil drought. These results support inclusion of parameters for cloudiness and the phenological status of the vegetation, as well as use of biome-specific parameterization, in operational εg algorithms.},
	keywords = {LTER-KNZ, Primary production},
	doi = {10.1046/j.1365-2486.2003.00573.x},
	author = {Turner, D.P. and Urbanski, D. and D. Bremer and Wofsy, S.C. and Meyers, T. and Gower, S.T. and Gregory, M.}
}
