In this study, a model for estimating crop gross primary production (GPP) using the product of a chlorophyll-related vegetation index (VI) and incident photosynthetically active radiation (PARin) was developed and tested. This model was tested using radiometric data taken 6 m above the top of the canopy and Landsat and MODIS satellites data for GPP estimation in both maize and soybean, crop types that differ in leaf structure and canopy architecture, under different crop management and climatic conditions. The model was capable of estimating GPP accurately in three Nebraska, USA sites during growing seasons 2001 through 2008. The developed model was successfully applied to measure GPP of vegetation (crops, grasslands and deciduous forests) where total chlorophyll content is closely tied to the seasonal dynamic of GPP. The techniques described open new possibilities for accurate estimation of crop GPP at different scales, from close-range (just above the canopy in the field) to satellite altitudes.