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.
关键词
高寒草甸总初级生产力光能利用率模型MODIS涡动相关观测系统
Keywords
alpine meadowgross primary productivitylight use efficiency modelMODISeddy covariance