Abstract: Abstract: Phenology refers to periodic plant life cycle events influenced by climate and other environmental factors, such as sprouting, flowering, fruiting and leaves falling, etc. Different vegetation types have distinct growth characteristics, and phenology can be a good representative parameter to classify vegetation types. Phonological parametric analysis is mainly used to find out significant changes in specific time points and extract corresponding characteristic VI values, by analyzing a time-series vegetation index, e.g., start of season (SOS), end of season (EOS), length of season (LOS), max of EVI (MOE) and amplitude of EVI (AOE). These key phenology parameters can be used to classify vegetation types. Eerguna and Genhe in Hulunbeier city, Inner Mongolia Autonomous Region were selected as the study area. A double logistic function fitting method was used to smooth the time series MODIS-EVI data. The time range was from the summer of 2011 (DOY=209) to the summer of 2013 (DOY=193), and the total number of images was 46. Then, 100 points of each land cover type (grass, forest, crops, other non-vegetation) were chosen as classification samples. Five key phenological parameters mentioned above were extracted and used to build the decision tree classifier. The overall classification accuracy of the results reached to 73.67%. The results show that vegetation in Hulunbeier northern region had obvious unique features. The season of forest started earliest (145-160 days, DOY, hereinafter), and ended quiet early (250-275 days); the season of grass started slightly later than forest (160-170 days), but the length of season was similar to forest, both were from 90 to 120 days. The season of crops started late and ended early, so the season of crops was short and concentrated, the length of the samples was from 60 to 90 days. The classification achieved better results than MODIS land cover products (66.08%). Except for grass' user accuracy being a little lower, producer accuracy and user accuracy of the 4 kinds of land cover types reached to 79%. The phonological information extracted in this paper had a high consistency with existing research results; it is shown that monitoring phenology based on time-series EVI data was reliable. This research can provide a reference to ecological environment evaluation and agriculture, animal husbandry, forestry production activities in the Hulunbeier northern region.