Abstract: MODIS data play an important role in global environmental and resource researches. But its low spatial resolution sometimes becomes a regretful factor by some people in pursuit of more precise classification results. In this research, MODIS high temporal resolution was used to improve the accuracy of land cover classification of the North China Plain using MODIS_EVI time-series of 2003. Harmonic Analysis of Time Series(HANTS) was performed on the MODIS_EVI image time series to reduce the cloud or other noise effects. Based on five phenological features derived from EVI profiles, as well as on Land Surface Temperature(LST) and topographic slope, a simple but reasonable decision tree was built to distinguish the ambiguous land cover classifications. The overall accuracy of the final land cover map was 75.5%, and the kappa coefficient is 0.68. While the overall accuracy and kappa coefficient of NASA USGS product are 66.0051% and 0.3209 respectively. When compared with the cropland area from official statistics, the classification in the paper shows much higher consistence with an overall mean square root error of 34.0507 kilo-hectare versus 66.1205 kilo-hectare by USGS product, indicating that land cover classification using MODIS EVI time series and decision tree is feasible and promising.