The decision question — where, and when, do people converge?
Retail timing · facility siting · headway optimization all hinge on hourly demand.
We read the city through the flow of time, not by district area or totals. Using Seoul Metro's hourly boarding/alighting open data, we traced the commuter tide — sucked in by morning, poured back out by evening.
At Gangnam Station, morning alighting (09–10h) explodes into the 310,000 range, then the flow flips with evening boarding (18–19h). Viewed along the time axis rather than as a total, a single point shifts from an inflow hub to an outflow hub within a single day — and that is where retail hours, headways, and facility circulation design diverge.
09–10h alighting 313,737 ↔ 18–19h boarding 208,495 (May 2026 monthly aggregate)The busiest station is Jamsil (Line 2) at a daily average of 156,000, followed by Hongik Univ. and Gangnam in a three-pole structure. Meanwhile, Dorimcheon Station on the same Line 2 averages 2,615 a day — a weight gap of roughly 60× between the busiest and the quietest station. Even on the same line, demand at each station lives on an entirely different scale.
Jamsil 156,177 · Hongik Univ. 150,369 · Gangnam 149,757 vs Dorimcheon 2,615 (2024 daily average)Line 2 moves 1.96 million people a day — more than the metro systems of Busan, Daegu, Incheon, Gwangju, and Daejeon combined. The imbalance between lines reveals the real load that area-based averages hide when setting priorities for investment, added trains, and congestion relief.
Line 2: 1,964,128 / day (2024) — single line > five regional cities combinedWe frame "when and where do people converge?" through the lenses of retail timing, facility siting, and headway/congestion relief.
We refine OA-12252 hourly boarding/alighting data and visualize it as a station network, a 24-hour heatmap, and commuter directional flows.
We hand over an hourly-demand report plus a reproducible pipeline that automatically reflects the monthly data refresh.
How to read these figures — The Gangnam Station hourly figures in the hero chart are a monthly aggregate (not a daily average) from OA-12252 (May 2026). Line and station rankings are based on Seoul Metro's published daily averages. To avoid mixing daily-average and monthly-aggregate bases, each chart states its unit. Figures are based on Lines 1–8 (operated by Seoul Metro); Line 9, KORAIL, and Airport Railroad segments are supplemented with separate datasets. This case study is for sales-asset demonstration purposes.
We read hourly demand from data and turn it into decisions on operations, siting, and headways.
Hourly demand analysis — free 30-min consultation →