Knowledge　of　both　vegetation　distribution　pattern　and　phenology　changes　is　very　important.　Their　complicated　relationship　with　elevation　and　accessibility　were　explored　through　a　geographically　weighted　regression　(GWR)　framework　in　Fujian　province,　China.　The　16-day　time　series　of　250　m　Moderate　Resolution　Imaging　Spectroradiometer　(MODIS)　Enhanced　Vegetation　Index　(EVI)　dataset　from　2000　to　2010　was　applied.　Wavelet　transform　method　was　adopted　to　decompose　the　original　time　series　and　construct　the　annual　maximum　EVI　and　amplitude　of　the　annual　phenological　cycle　(Delta　EVI).　Candidate　explaining　factors　included　topographic　conditions,　accessibility　variables　and　proportions　of　primary　vegetation　types.　Results　revealed　very　strong　positive　influence　from　parameters　of　elevation　and　accessibility　to　big　rivers　and　negative　effect　from　accessibility　to　resident　on　both　maximum　EVI　and　phenological　magnitude　through　ordinary　linear　least　square　(OLS)　regression　analysis.　GWR　analysis　revealed　that　spatially,　the　parameters　of　topography　and　accessibility　had　a　very　complex　relationship　with　both　maximum　EVI　and　phenology　magnitude,　as　a　result　of　the　various　combinations　of　environmental　factors,　vegetation　composition　and　also　intensive　anthropogenic　impact.　Apart　from　the　continuously　increasing　trend　of　phenology　magnitude　with　increasing　altitude,　the　influence　of　topography　and　accessibility　on　maximum　EVI　and　phenological　magnitude　generally　decreased,　even　from　strongly　positive　to　negative,　with　increasing　altitude　or　distance.　Specially,　the　most　rapid　change　of　correlation　coefficient　between　them　was　observed　within　a　low　elevation　or　close　distance;　less　variation　was　discovered　within　a　certain　range　of　medium　altitude　or　distance　and　their　relationship　might　change　above　this　range.　Non-stationary　approaches　are　needed　to　better　characterize　the　complex　vegetation　dynamic　pattern　in　Mountain-hill　Region.