Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the “true” flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include “tall tower” instrumentation), one grassland site, and one… More

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Yield monitor data contain systematic and random errors, which must be removed for creating accurate yield maps. A general procedure for assessing yield data cleaning methods was applied to a new postprocessing algorithm in which six common types of erroneous yield monitor values were removed: (1) combine header status up; (2) start-/end-pass delays; (3) grain… More

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Leaf area index (LAI) is an important variable for climate modeling, estimates of primary production, agricultural yield forecasting, and many other diverse studies. Remote sensing provides a considerable potential for estimating LAI at local to regional and global scales. Several spectral vegetation indices have been proposed, but their capacity to estimate LAI is highly reduced… More

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Solar radiation and dew point temperature are important input variables for many crop growth ecological, hydrological, and meteorological models. It is also well known that solar radiation and dew point temperature (and relative humidity) data are not readily available for most locations over the globe. To use the above models, estimation of these input variables… More

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Net ecosystem CO2 exchange (NEE) was measured in maize-based agroecosystems in eastern Nebraska, USA, during the growing season in 2001. The objective of this study was to quantify and contrast NEE in irrigated and rainfed maize (Zea maize L.) fields. Daytime NEE showed a strong dependence on incident light at different stages of crop growth…. More

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A new maize (Zea mays L.) simulation model, Hybrid-Maize, was developed by combining the strengths of two modeling approaches: the growth and development functions in maize-specific models represented by CERES-Maize, and the mechanistic formulation of photosynthesis and respiration in generic crop models such as INTERCOM and WOFOST. It features temperature-driven maize phenological development, vertical canopy… More

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Yield maps reflect systematic and random sources of yield variation as well as numerous errors caused by the harvest and mapping procedures used. A general framework for processing of multi-year yield map data was developed. Steps included (1) raw data screening, (2) standardization, (3) interpolation, (4) classification of multi-year yield maps, (5) post-classification spatial filtering… More

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Monitoring crop phenology is required for understanding intra- and interannual variations of agroecosystems, as well as for improving yield prediction models. The objective of this paper is to remotely evaluate the phenological development of maize (Zea mays L.) in terms of both biomass accumulation and reproductive organ appearance. Maize phenology was monitored by means of… More

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Synoptic monitoring of vegetation dynamics relies on satellite observations of the distinctive spectral contrast between red and near infrared reflectance that photosynthetically active green vegetation exhibits. It has long been recognized that the Normalized Difference Vegetation Index (NDVI) suffers a rapid decrease of sensitivity at moderate-to-high densities of photosynthetic green biomass. This decrease can conceal… More

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