The　complex　spatiotemporal　vegetation　variability　in　the　subtropical　mountain-hill　region　was　investigated　through　a　multi-level　modeling　framework.　Three　levels　-　parcel,　landscape,　and　river　basin　levels-were　selected　to　discover　the　complex　spatiotemporal　vegetation　variability　induced　by　climatic,　geomorphic　and　anthropogenic　processes　at　different　levels.　The　wavelet　transform　method　was　adopted　to　construct　the　annual　maximum　Enhanced　Vegetation　Index　and　the　amplitude　of　the　annual　phenological　cycle　based　on　the　16-day　time　series　of　250m　Moderate　Resolution　Imaging　Spectroradiometer　Enhanced　Vegetation　Index　datasets　during　2001-2010.　Results　revealed　that　land　use　strongly　influenced　the　overall　vegetation　greenness　and　magnitude　of　phenological　cycles.　Topographic　variables　also　contributed　considerably　to　the　models,　reflecting　the　positive　influence　from　altitude　and　slope.　Additionally,　climate　factors　played　an　important　role:　precipitation　had　a　considerable　positive　association　with　the　vegetation　greenness,　whereas　the　temperature　difference　had　strong　positive　influence　on　the　magnitude　of　vegetation　phenology.　The　multilevel　approach　leads　to　a　better　understanding　of　the　complex　interaction　of　the　hierarchical　ecosystem,　human　activities　and　climate　change.