In　recent　years,　with　the　development　of　various　types　of　public　transportation,　they　are　also　more　and　more　closely　connected.　Among　them,　subway　transportation　has　become　the　first　choice　of　major　cities.　However,　the　planning　of　subway　stations　is　very　difficult　and　there　are　many　factors　to　consider.　Besides,　few　methods　for　selecting　optimal　station　locations　take　other　public　transport　in　to　consideration.　In　order　to　study　the　relationship　between　different　types　of　public　transportation,　the　authors　collected　and　analyzed　the　travel　data　of　subway　passengers　and　the　passenger　trajectory　data　of　taxis.　In　this　paper,　a　method　based　on　LeaderRank　and　Gaussian　Mixed　Model　(GMM)　is　proposed　to　conduct　subway　station　locations　selection.　In　this　method,　the　author　builds　a　subway-passenger　traffic　zone　weighted　network　and　a　station　location　prediction　model.　First,　we　evaluate　the　nodes　in　the　network,　then　use　the　GPS　track　data　of　taxis　to　predict　the　location　of　new　stations　in　future　subway　construction,　and　analyze　and　discuss　the　land　use　characteristics　in　the　prediction　area.　Taking　the　design　of　the　Beijing　subway　line　as　an　example,　the　suitability　of　this　method　is　illustrated.