Understanding　intercity　mobility　patterns　is　important　for　future　urban　planning,　in　which　the　intensity　of　intercity　mobility　indicates　the　degree　of　urban　integration　development.　This　study　investigates　the　intercity　mobility　patterns　of　the　Greater　Bay　Area　(GBA)　in　China.　The　proposed　workflow　starts　by　analyzing　intercity　mobility　characteristics,　proceeds　to　model　the　spatial-temporal　heterogeneity　of　intercity　mobility　structures,　and　then　identifies　the　intercity　mobility　patterns.　We　first　conduct　a　complex　network　analysis,　based　on　weighted　degrees　and　the　PageRank　algorithm,　to　measure　intercity　mobility　characteristics.　Next,　we　calculate　the　Normalized　Levenshtein　Distance　for　Population　Mobility　Structure　(NLPMS)　to　quantify　the　differences　in　intercity　mobility　structures,　and　we　use　the　Non-negative　Matrix　Factorization　(NMF)　to　identify　intercity　mobility　patterns.　Our　results　showed　an　evident　＇Core-Periphery＇　differentiation　characterized　by　intercity　mobility,　with　Guangzhou　and　Shenzhen　as　the　two　core　cities.　An　obvious　daily　intercity　commuting　pattern　was　found　between　Guangzhou　and　Foshan,　and　between　Shenzhen　and　Dongguan　cities　at　working　time.　This　pattern,　however,　changes　during　the　holidays.　This　is　because　people　move　from　the　core　cities　to　peripheral　cities　at　the　beginning　of　holidays　and　return　at　the　end　of　holidays.　This　study　concludes　that　Guangzhou　and　Foshan　have　formed　a　relatively　stable　intercity　mobility　pattern,　and　the　Shenzhen-Dongguan-Huizhou　metropolitan　area　has　been　gradually　formed.