Eddy covariance (EC) technique is the most direct way to measure the exchanges of carbon dioxide (CO₂),water vapor,and energy flux between terrestrial ecosystems and atmosphere, which can be used to explore CO₂ exchanges between terrestrial ecosystems and atmosphere and its controlling mechanism. In this paper,we used the multivariate geographic clustering approach to generate flux-ecoregions with different clustering number(25,50,75,85,100,150,200 clusters) in China based on 11 variables affecting carbon flux,including meteorological factor,soil factor,abiotic factor of topography, actual vegetation (Leaf area index (LAI) and Enhanced vegetation index (EVI)) and vegetation productivity variables (Gross primary productivity,GPP). Based on the spatial distribution pattern of the existing flux observation stations in China and the comparative analysis between newly generated flux ecoregions and the existing geographical regionalization, the results showed that the existing 85 eddy covariance flux observation stations in China cannot reflect the spatial and temporal characteristics of carbon flux of all ecosystems because of the country's complex topography and the diverse ecosystem types. It is also recommended that the number of the flux-ecoregions be 100-150. Considering the building and operating costs of the flux towers, the number of eddy flux tower stations can be added to 150 sites. Thus,the optimized flux network is supposed to represent major ecosystems and facilitate the integration of flux and remote sensing data,consequently, improve the accuracy of upscaling CO₂ and water vapor flux observations from tower to regional scales to better exam the simulation result of the process based ecosystem model.