Abstract: Google Earth Engine enables some limitations in the remote sensing monitoring of vegetation to be overcome, including difficult data acquisition, large local storage capacity, and low processing efficiency. Using GEE, the data of satellites Landsat and MODIS (spatial resolution: 30 m and 250 m, respectively), and temperature and precipitation data, this study investigated the spatio-temporal change trends and sustainability of the vegetation in the Nuomuhong alluvial fan in Qinghai Province during 2000—2017. Moreover, this study analyzed the relationships of vegetation between wolfberry plantations and salinized areas on the alluvial fans of different eras and the future changes of the relationships. The results are as follows: ① The average annual maximum synthetic normalized difference vegetation index (NDVI) increased from 0.029 to 0.054 during 2000—2017, with an increased amplitude of 0.025. The average annual enhanced vegetation index (EVI) increased from 0.633 to 0.771 during these years, with an increased amplitude of 0.138. The multiyear average maximum EVI showed that EVI peaks occurred from May to October each year. ② A correlation analysis and a partial correlation analysis were conducted between the average maximum EVI and the temperature and precipitation data. According to the analytical results, the correlation coefficient between the average maximum EVI and temperature was 0.839, indicating a strong positive correlation. Meanwhile, the correlation coefficient between the average maximum EVI and precipitation amount was 0.457, indicating a weak positive correlation. ③ Over 18 years, the vegetation in wolfberry plantations was rapidly improved, while the vegetation in the salinized area degenerated. ④ The future changes in the vegetation in wolfberry planting areas and salinized areas will have strong sustainability. The vegetation growth in wolfberry planting areas will continuously restrict the vegetation in the salinized area to a certain extent in a period in the future.