The　quantitative　relationship　between　the　spatial　variation　of　building＇s　height　and　the　associated　land　surface　temperature　(LST)　change　in　six　Chinese　megacities　is　investigated　in　this　paper.　The　six　cities　involved　are　Beijing,　Shanghai,　Tianjin,　Chongqing,　Guangzhou,　and　Shenzhen.　Based　on　both　remote　sensing　and　building　footprint　data,　we　retrieved　the　LST　using　a　single-channel　(SC)　algorithm　and　evaluate　the　heating/cooling　effect　caused　by　building-height　difference　via　correlation　analysis.　The　results　show　that　the　spatial　distribution　of　high-rise　buildings　is　mainly　concentrated　in　the　center　business　districts,　riverside　zones,　and　newly　built-up　areas　of　the　six　megacities.　In　the　urban　area,　the　number　and　the　floor-area　ratio　of　high　to　super　high-rise　buildings　(＞24m)　account　for　over　5%　and　4.74%,　respectively.　Being　highly　urbanized　cities,　most　of　urban　areas　in　the　six　megacities　are　associated　with　high　LST.　Ninety-nine　percent　of　the　city　areas　of　Shanghai,　Beijing,　Chongqing,　Guangzhou,　Shenzhen,　and　Tianjin　are　covered　by　the　LST　in　the　range　of　30.2　similar　to　67.8　degrees　C,　34.8　similar　to　50.4　degrees　C,　25.3　similar　to　48.3　degrees　C,　29.9　similar　to　47.2　degrees　C,　27.4　similar　to　43.4　degrees　C,　and　33.0　similar　to　48.0　degrees　C,　respectively.　Building＇s　height　and　LST　have　a　negative　logarithmic　correlation　with　the　correlation　coefficients　ranging　from　-0.701　to　-0.853.　In　the　building＇s　height　within　range　of　0　similar　to　66m,　the　LST　will　decrease　significantly　with　the　increase　of　building＇s　height.　This　indicates　that　the　increase　of　building＇s　height　will　bring　a　significant　cooling　effect　in　this　height　range.　When　the　building＇s　height　exceeds　66m,　its　effect　on　LST　will　be　greatly　weakened.　This　is　due　to　the　influence　of　building　shadows,　local　wind　disturbances,　and　the　layout　of　buildings.