Understanding　the　travel　behaviour　of　transport　hub　users　is　vital　for　improving　transport　services.　Although　previous　research　has　explored　passenger　behaviour　in　and　around　transport　hubs,　there　is　a　lack　of　comprehensive　studies　on　travel　patterns　within　hub　station　areas.　To　this　end,　this　study　harnessed　mobile　phone　data　to　analyse　the　travel　behaviour　within　a　hub　station　area,　using　Beijing　South　Railway　Station　as　a　representative　case.　A　series　of　recognition　criteria　was　set　up　based　on　spatio-temporal　information　to　categorize　users　within　the　station　area.　We　categorised　station　area　users　into　transport　hub　users　(THU)　and　non-transport-hub　users　(NTHU)　and　examined　their　distinct　travel　patterns.　The　results　reveal　distinct　travel　patterns　for　THU　and　NTHU.　NTHU　are　predominantly　concentrated　in　and　around　the　station　area.　THU,　however,　display　longer　trip　distances　and　more　widely　distributed　endpoints.　In　terms　of　travel　time　distribution,　NTHU　show　evident　morning　and　evening　peak　phenomena,　while　the　travel　time　distribution　of　THU　fluctuates　throughout　the　day.　The　study　also　employed　association　rule　analysis　to　illustrate　strong　connections　between　the　station　area,　Beijing＇s　core,　central　areas,　and　even　urban　fringe　areas.　The　results　reveal　that　the　station　area　is　most　closely　connected　to　the　core　and　central　areas　of　Beijing,　from　where　many　users　are　attracted　to　the　station　area.　In　addition,　some　urban　fringe　areas　also　have　strong　connections　with　the　station　area.　These　findings　inform　urban　transport　planning　and　personalised　travel　services.