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.　©　2015　IEEE.