In　this　era　of　population　aging,　it　is　essential　to　understand　the　spatial　distribution　patterns　of　the　elderly.　Based　on　the　smart　card　data　of　the　elderly,　this　study　aims　to　detect　the　home　location　and　examine　the　spatial　distribution　patterns　of　the　elderly　cardholders　in　Beijing.　A　framework　is　proposed　that　includes　three　methods.　First,　a　rule-based　approach　is　proposed　to　identify　the　home　location　of　the　elderly　cardholders　based　on　individual　travel　pattern.　The　result　has　strong　correlation　with　the　real　elderly　population.　Second,　the　clustering　method　is　adopted　to　group　bus　stops　based　on　the　elderly　travel　flow.　The　center　points　of　clusters　are　utilized　to　construct　a　Voronoi　diagram.　Third,　a　quasi-gravity　model　is　proposed　to　reveal　the　elderly　mobility　between　regions,　using　the　public　facilities　index.　The　model　measures　the　elderly　travel　number　between　regions,　according　to　public　facilities　index　on　the　basis　of　the　total　number　of　point　of　interest　(POI)　data.　Beijing　is　used　as　an　example　to　demonstrate　the　applicability　of　the　proposed　methods,　and　the　methods　can　be　widely　used　for　urban　planning,　design　and　management　regarding　the　aging　population.