Gross primary production (GPP), defined as the overall amount of carbon fixed through the process of vegetation photosynthesis, is an important characteristic for climate change and carbon cycle research to reveal the carbon sequestration capacity of a certain ecosystem. The aim of the research is to test a simplified way to remote estimation of gross primary production in maize with remote sensing and carbon flux measurements, through discarding nearly all kinds of complex concepts and focusing on the operation convenience, according to the main principle is based on the concept of LUE-based (light use efficiency) GPP estimation models. And validate whether it is right that “the more complex the method is, the more accurate it will achieve”. Results shows that for single and multi-sites estimations, the two forms of estimation concepts of GPP ∝VI∗SOL and GPP ∝LAI∗VI∗SOL performs different. And the former one seems to be better than the other. This also reveals that to establish the remotely-sensed models, the numbers of input parameters is not the key influence factors. The accuracy of single site estimation is higher than that of multi-sites because of the heterogeneity in different sites.