Development of remote sensing makes it possible to estimate Gross Primary Productivity（GPP） regionally.In recent years

a lot of researches on GPP estimation based on remote sensing data were conducted.In this study

meteorological and moderate-resolution imaging spectroradiometer（MODIS） data at A’rou（AR） freeze/thaw observation station

which is located in upper stream of Heihe River Basin

was collected to drive four remote-sensing based GPP models:Vegetation Photosynthesis Model（VPM）

Temperature and Greenness model（TG）

Vegetation Index model（VI） and Eddy Covariance-Light Use Efficiency model（EC-LUE）.GPP observed by Eddy Covariance（EC） was used to validate the results from the four models.It is indicated that GPP

NEE and ER at AR station were 804.2 gC/m2/yr

129.6 gC/m2/yr and 673.6 gC/m2/yr

respectively in 2009

indicating that 83.8% of carbon fixed by photosynthesis was released to atmosphere by ecosystem respiration.All the four models can predict GPP of alpine meadow very well.Determination coefficient between observed GPP and predicted GPP was larger than 0.94in 2009

and was larger than 0.84 during growing season.