This　research　designs　a　new　approach　by　modifying　the　Fast-Newman　algorithm　for　better　implementing　the　process　of　detecting　functional　urban　areas　(FUAs)　and　further　revealing　the　spatiotemporal　patterns　of　functional　urban　polycentricity　through　20　view-windows　of　each　FUA　in　the　Tokyo　metropolitan　area　(TMA)　by　using　geo-tagged　big　data.　Through　the　20　view-windows　of　our　GIS　microscope,　it　is　possible　to　uncover　patterns　of　functional　connections　and　daily　urban　rhythms　under　the　same　layout　of　the　functional　urban　structure　in　the　TMA.　Furthermore,　our　findings　can　elucidate　the　double-sided　thinking　by　combining　the　explanations　of　functional　urban　polycentricity　with　the　policy　effects　of　the　Tokyo　Master　Plan　(TMP)　from　the　perspective　of　area-byarea　analysis　across　the　entire　TMA.　Our　results　imply　that　the　functional　urban　structure　of　the　TMA　is　a　four-level,　annular　pattern.　The　TMP　still　has　room　for　the　improvement　toward　sustainable　urban　planning　in　the　TMA.　Based　on　the　investigation　on　the　patterns　of　functional　urban　polycentricity,　this　research　has　obtained　many　hints　and　clues　for　improving　the　TMP.　Rethinking　the　effectiveness　of　the　TMP　can　also　provide　trustworthy　academic　verification　and　provide　suggestions　about　concrete　amendments　that　can　enlighten　future　urban　planning.