This　paper　utilized　the　one-week　smart　card　data　(SCD)　and　the　control　passenger　flow　survey　to　analyze　the　commute　travel　time　and　the　passenger　flow　distribution　in　the　multi-mode　public　transport.　To　research　the　commute　pattern　of　the　central　business　district　(CBD),　there　were　three　large-scale　residence　communities　selected　for　the　survey　areas.　Based　on　SCD　in　the　double　ticket　system,　the　average　travel　time　and　the　passenger　volume　were　estimated　through　clustering　＂the　alighting　time＂　and　filling　none　value.　As　a　result,　the　visualization　of　the　station　attraction　and　the　travel　time　under　multi-mode　public　transport　was　presented　through　the　application　of　GIS.　The　analysis　of　the　commute　pattern　is　aimed　to　make　a　scientific　guidance　for　commuters　on　the　traffic　model　choice　as　well　as　provide　a　quantitative　basis　for　the　development　of　the　smart　city.