Continuous and automatic monitoring of canopy phenology is of increasing scientific interest as a tool to investigate the multiple implications of vegetation dynamics on ecosystem carbon fluxes. For this purpose, we initiated research on winter wheat ecosystem northern China in 2011, belonging to Chinese Terrestrial Ecosystem Flux Observation and Research Network (ChinaFLUX), and evaluated the applicability of digital camera imagery for monitoring and modeling crop phenology and physiology. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the YuCheng ChinaFLUX site. Images were collected in growing season every 30 min from 9:30 a.m to 5:00 p.m each day. Red, green, and blue color channel brightness data for a region-of-interest (ROI) were extracted from each image (ROI is the subset of image, can better describe the target's characters. The size of ROI for winter wheat is 380*260 pixels). Since a temporal series of original brightness data can't capture the changes at different canopy development stages, we compared different indices (ratio greenness index, excess greenness index, and relative greenness index) composed of different channel brightness data. Ratio greenness index (G/R), can reflect the size of leaf area index and variations in chlorophyll content of winter wheat, proved to be the index best describing the green-up signals of the vegetation, was calculated by dividing green channel brightness by red channel brightness, and extracted from chronically digital images. Phenological date was defined as the date on which the curvature of G/R reaches its peak and compared to field-measured phenological date. The results confirmed that G/R was useful to monitor canopy phenology. We further investigated the relationship between G/R and carbon exchange capacity (i.e., gross ecosystem exchange ) of vegetation using eddy covariance CO₂ flux data. A strong relationship (GEE: r²=0.66) between ratio greenness and photosynthesis was observed for winter wheat. At the same time, we used the daily NEE and PAR data collected from Eddy covariance technique, employed the Michaelis-Menten equationt, and obtained the curve of Amax. The result demonstrated a positive relationship between G/R and Amax, and suggested that G/R is able to reflect the plant phenological activity in physiological level. We concluded that digital camera images not only provide a reliable measure of plant phenology at high tempo-spatial resolutions, but also act as a complementary role of CO₂ flux measurements, and improve our knowledge of ecosystem processes. Digital cameras have been installed at eight typical terrestrial ecosystem sites of ChinaFLUX for phenological observations, constituting of the Chinese Digital Camera Phenology Observation Network. This platform will provide an unprecedented opportunity to obtain an improved understanding of vegetation responses to climate change in China. With high tempo-spatial resolution phenological data, we can bring insights into the process of biologically mediated carbon sources and sinks, and better understand the uncertainties of the role of terrestrial ecosystems in the global carbon cycle.