Urban　landscape　patterns　significantly　impact　land　surface　temperature　(LST)　and　the　urban　heat　island　(UHI)　effect.　This　study　employs　the　boosted　regression　tree　(BRT)　model　and　variance　partitioning　analysis　to　examine　the　contributions　and　relationships　of　two-dimensional　and　three-dimensional　building　and　vegetation　patterns　to　LST,　and　their　marginal　effects　at　different　heights.　The　results　show　that　the　dominant　indicators　affecting　LST　differ　between　buildings　and　vegetation,　with　three-dimensional　building　features　being　slightly　more　important　than　two-dimensional　features　(percentage　of　landscape　of　buildings)　and　two-dimensional　vegetation　features　(three-dimensional　green　index)　having　a　greater　impact　than　three-dimensional　features.　When　both　buildings　and　vegetation　are　considered,　building　patterns　still　have　significant　explanatory　power.　Building　height　differences　influence　each　indicator＇s　contribution　and　marginal　effects　on　LST,　with　lower-height　areas　seeing　a　joint　dominance　of　buildings　and　vegetation　on　LST　changes,　and　higher-height　areas　showing　greater　impact　from　vegetation　indicators.　Increasing　the　percentage　of　landscape　of　vegetation　(PLAND_V)　provides　the　best　cooling　effect　in　lower-building-height　areas,　but　in　higher-building-height　areas,　the　cooling　effect　weakens,　requiring　additional　vegetation　indicators　to　assist　in　cooling.