Green　Infrastructure　(GI)　has　garnered　increasing　attention　from　various　regions　due　to　its　potential　to　mitigate　urban　heat　island　(UHI),　which　has　been　exacerbated　by　global　climate　change.　This　study　focuses　on　the　central　area　of　Fuzhou　city,　one　of　the　＂furnace＂　cities,　and　aims　to　explore　the　correlation　between　the　GI　pattern　and　land　surface　temperature　(LST)　in　the　spring　and　autumn　seasons.　The　research　adopts　a　multiscale　approach,　starting　from　the　urban　scale　and　using　urban　geographic　spatial　characteristics,　multispectral　remote　sensing　data,　and　morphological　spatial　pattern　analysis　(MSPA).　Significant　MSPA　elements　were　tested　and　combined　with　LST　to　conduct　a　geographic　weighted　regression　(GWR)　experiment.　The　findings　reveal　that　the　UHI　in　the　central　area　of　Fuzhou　city　has　a　spatial　characteristic　of　＂high　temperature　in　the　middle　and　low　temperature　around,＂　which　is　coupled　with　a　＂central　scattered　and　peripheral　concentrated＂　distribution　of　GI.　This　suggests　that　remote　sensing　data　can　effectively　be　utilised　for　UHI　inversion.　Additionally,　the　study　finds　that　the　complexity　of　GI,　whether　from　the　perspective　of　the　overall　GI　pattern　or　the　classification　study　based　on　the　proportion　of　the　core　area,　has　an　impact　on　the　alleviation　of　UHI　in　both　seasons.　In　conclusion,　this　study　underscores　the　importance　of　a　reasonable　layout　of　urban　green　infrastructure　for　mitigating　UHI.