This paper aims to improve our knowledge of the complex vegetation-climate relationship in subtropical humid region in the context of global warming, by taking into considerations of spatio-temporal variation of both vegetation and climate change. A multi-resolution analysis (MRA) based on the wavelet transform (WT) is applied to examine the vegetation growth and its relationship with climate factors based on 250m 16-day composites MODIS vegetation EVI dataset in subtropical humid region of China over the period 2001-2010. A general greening up (68%) was observed over the period 2001-2010, as well as rather local negative trends. A trend toward global warming was also observed for the whole study region, whereas no obvious trend of precipitation is examined in most areas. Temperature generally has a positive influence on vegetation; with only very few negative EVI-temperature coefficients observed on the south portion principally due to changes in land use, land degradation, and cloud noise. However, nearly equally positive and negative EVI-rainfall relationship is observed on the inter-annual level, with negative coefficients principally observed in the northwest portion with abundant precipitation. Very strong positive relationship is observed between both EVI-temperature and EVI-precipitation at seasonal level. It is revealed that spatio-temporal variation of both vegetation and climate should be taken into considerations when analyzing the long-term effects of global climate change. Interactions between vegetation dynamics and climate variability must be studied through spatially and temporally explicit multi-scale analysis to investigate the influence of long-term climate change on the vegetation growth.