The　extraction　of　impervious　surfaces　from　satellite　imagery　has　been　a　hot　topic　in　the　remote　sensing　field　over　the　past　decade.　Nevertheless,　whether　the　impervious　surface　information　extracted　from　different　sensor　images　is　comparable　is　still　unknown.　This　paper　implemented　a　complementary　study　based　on　a　comparison　of　the　retrieved　impervious　surface　information　from　Landsat　ETM+　and　EO-1ALI　sensor　data.　Impervious　surface　features　were　derived　from　a　date-coincident　image　pair　of　the　two　sensors　by　using　linear　spectral　mixture　analysis　(LSMA).　The　accuracy　of　retrieved　impervious　surface　information　of　the　two　sensors　was　assessed　and　compared.　The　results　show　that　the　ALI　image　has　higher　accuracy　than　ETM+,　as　suggested　by　its　higher　overall　accuracy　and　Kappa　coefficient　and　lower　root　mean　square　error　and　systematic　error　(in　absolute　value).　The　differences　in　spectral　resolution　and　radiometric　resolution　between　the　two　sensors　are　believed　to　be　the　main　factors　causing　these　differences　when　retrieving　impervious　surfaces.　An　increase　in　spectral　information　in　ALI　sensor　can　be　of　help　when　distinguishing　differences　between　land　cover　types,　while　the　enhancement　in　radiometric　resolution　in　the　ALI　sensor　can　make　the　sensor　more　sensitivite　when　detecting　ground　surface　features.