The ASD FieldSpec portable spectrometer was adopted to collect canopy reflectance spectrum data of the 9 main tree species in study area by a long-term observation to get the data of the four seasons Then the smoothed reflectance curve and the first derivation curve from 350 to 1 400 nm and several commonly used vegetation spectral characteristic parameters were generated to analyse seasonal change characteristics and variation of the 9 tree species in visible and near-infrared band and to explore the best band characteristics and period for species identification. The results showed that different trees had different and rather unique spectral features during the four seasons. The spectral characteristics of the deciduous trees have regular changes with the cycle of the seasons, whereas those of the evergreen tree species have no significant changes in one year. As well changes in the spectral characteristics could effectively reflect forest phenology changes, and it is proposed that the optimal strategy for tree species classification may be the integration and analysis of multi-seasonal spectral data. Evergreen trees and deciduous trees in the winter have obvious differences in the canopy spectral characteristics and the best single-season remote sensing data for tree species recognition is in summer.