As　the　most　important　component　of　the　urban　surface,　impervious　surface　has　been　recognized　as　a　main　indicator　of　urban　heat　island　effect.　However,　the　quantitative　relationship　between　impervious　surface　area　(ISA)　and　land　surface　temperature　(LST)　is　still　unclear　as　different　studies　achieved　different　results.　Therefore,　the　present　paper　selected　six　cities　from　different　geographical　regions　of　China　to　further　investigate　the　quantitative　relationship　between　ISA　and　LST.　The　cities　involved　are　Shanghai,　Guangzhou,　Beijing,　Changsha,　Lanzhou　and　Fuzhou.　The　ISAs　of　the　six　cities　were　derived　from　Landsat　ETM+　images　by　using　linear　spectral　mixture　analysis　and　the　LSTs　of　the　cities　were　retrieved　from　the　thermal　infrared　band　of　the　images.　Multivariate　regression　analysis　with　a　large　amount　of　samples　was　implemented　to　examine　quantitative　relationship　between　ISA　and　LST.　Results　show　that　the　ISAs　of　the　six　cities　are　all　positively　correlated　to　the　LST,　but　with　an　exponential　relationship　being　the　best　fit　model.　This　suggests　that　the　area　with　high　percent　ISA　could　accelerate　LST　rise.　The　weaker　transpiration　evaporation　and　lower　vegetation　cover　are　the　main　factors　contributing　to　the　higher　LST　rise　in　the　high　percent　ISA　area.