The Tibetan Plateau is the highest plateau in the world, and is one of the most sensitive areas to the global climate change. Accurate estimation of the spatio-temporal variation in net ecosystem exchange (NEE) for this area is important for studying the reponse of terrestrial ecosystems to future climate change. In this paper, we develop a Net Carbon Budget Model ( NCBM) to estimate the dynamic change of NEE in the Tibetan Plateau. The NCBM is only driven by the Enhanced Vegetation Index ( EVI) and the Land Surface Water Index ( LSWI) from MODIS image, and air temperature and shortwave radiation from ground observations. The long-term eddy CO_2 flux data of three vegetation types ( including alpine shrubland,alpine marsh and alpine meadow-steppe) in the Tibetan Plateau from ChinaFLUX were chosen for model calibration and validation. At model calibration site-years, the NCBM could estimate about 81% of the variation in the flux-observed NEE, with the root mean square error (RMSE) of 0. 03mol C/m~2/d and the model efficiency (EF) of 0. 81. At model validation site-years, the NCBM could predict about 84% of the variation in the flux-observed NEE, with the RMSE of 0. 03mol C/m~2/d and EF of 0. 81. In most cases, the seasonal and interannual variation of the estimated NEE matched well with those of the observed NEE whether at model calibration site-years or at model validation site-years. Above results indicated that the NCBM has a good performance in NEE estimation, and also has a potential to estimate spatial NEE because of its easily obtained variables. However, the performance of the NCBM under the condition of very sparse vegetations needs to be imporved in the further study.