The 15-minute city, measured in footfall
The 15-minute city is an idea about how urban districts should work. Measuring whether they do requires anonymous data on how people actually move through them, collected at scale and over time.
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A city planner stands at the corner of a high street that, on paper, has everything: a pharmacy, a GP surgery, a supermarket, three cafés, a library, a primary school. By every conventional measure it is well served, and yet the street feels quiet. The cafés are half-empty on weekday mornings and the library reports falling visits. Residents say the place feels dead.
The problem lies in what is happening, or not happening, in the space between the map and the people who supposedly live within 15 minutes of it. Footfall data is built to close that gap.
The idea behind the 15-minute city
The concept belongs to Carlos Moreno, an urban scientist at the Université Paris 1 Panthéon-Sorbonne. Moreno articulated it around 2016: a city works well when residents can reach the six essential functions of urban life (living, working, commerce, healthcare, education and entertainment) within 15 minutes on foot or bicycle. Residents need neither a long commute nor a car, and no neighbourhood serves only one purpose at one time of day.
Paris gave the concept institutional weight when Mayor Anne Hidalgo adopted it as a planning framework. Then the pandemic made it tangible: millions of people spent months discovering what it actually meant to live within a 15-minute radius, for better or worse.
The gap between design and reality
The 15-minute city is an accessibility concept. Planners can model it from maps (how many residents are within 15 minutes’ walk of a supermarket?), but accessibility is not the same as use.
A neighbourhood can be complete on paper and almost lifeless in practice.
A transit hub can sit in a 15-minute zone without connecting to destinations people actually want to reach.
Planning decisions about where to invest, which streets to pedestrianise, where to add cycle infrastructure, and which commercial units to activate need to rest on how people actually move. The question shifts from “is the pharmacy within 15 minutes?” to “do people walk to the pharmacy, or do they drive to the one on the ring road?”
Town centre footfall analytics starts from that second question. A site selection analysis built on real movement data instead of modelled demographics lets a planning vision be tested before money is committed.
What district-scale movement data shows
The flows through an urban district have a structure: the routes people habitually take, the nodes where they gather, and the edges of the neighbourhood where movement drops off sharply. They also have a rhythm: morning peaks, lunchtime pulses, evening surges, weekend patterns that look nothing like weekdays, and seasonal variations that tell you whether the high street is actually serving its local population or drawing visitors from further away.
Cellular network analytics captures this at a scale that no manual survey can match. As mobile devices interact with 4G and 5G network infrastructure throughout the day, those interactions, aggregated and anonymised, resolve into a detailed picture of movement across a whole district. The data shows origin as well as volume: do the people on the high street come from the surrounding district, or from further afield?
For cities and municipalities making decisions about pedestrianisation, market days, or where to concentrate business improvement district spending, urban footfall analytics at district scale is a different order of information from a traffic count or a survey. Outdoor & DOOH advertising uses the same district-scale flows to value street-level audiences.
The high-street health check
High streets across Europe have spent years dealing with the shift to e-commerce, changes in anchor tenants, and the aftershocks of the pandemic. The conversation about high-street health tends to be dominated by vacancy rates and business rate receipts: lagging indicators that confirm something went wrong long after the damage was done.
Footfall is a leading indicator.
A street that is losing visitors before it loses tenants gives planners and local authorities the chance to respond while there is still something to respond to. Dwell time rising while visitor numbers flatten suggests the mix is right and people are staying longer. The same visitor count with falling dwell time tells a very different story: people are passing through without finding a reason to stop.
The data deliverables from a district-level analytics programme typically include zone-level volume, peak hours, dwell-time distributions, and catchment analysis of where visitors come from. That combination lets planners answer a question that footfall counts alone cannot: is this street serving its own neighbourhood, or is it surviving on visitors from outside it?
The 15-minute city, measured
The gap between planning ideal and lived experience is a reason to measure the 15-minute city concept rather than dismiss it. If the vision is a neighbourhood where residents meet everyday needs within a short walk, the evidence of whether that is working sits in how people actually move. The planning documents only say how they should.
Measuring the pulse
A healthy neighbourhood has a pulse: a daily and weekly rhythm of movement.
It shows in the morning movement to schools and transport, the lunchtime animation of the high street, the after-work peak, and a weekend pattern that looks nothing like the weekday. A neighbourhood that has lost its rhythm, with a flat pattern and the peaks gone, is telling you something that vacancy rates will only confirm later.
Reading that pulse means measuring flows anonymously and at scale, and keeping a longitudinal record that shows change over time. It is the only footfall method in Europe approved by a data protection authority that captures the movement of a district without identifying a single person who walked through it. The data deliverables from a programme like this give cities and municipalities the evidence they need to plan.
Sources
- Moreno, C., Allam, Z., Chabaud, D., Gall, C., & Pratlong, F. (2021). Introducing the “15-Minute City”: Sustainability, resilience and place identity in future post-pandemic cities. Smart Cities, 4(1), 93–111. https://doi.org/10.3390/smartcities4010006
Curious what this looks like for your venue?
- 15 minutes
- Walk or cycle to daily essentials
- six
- Essential functions of urban life
Frequently asked questions
What is the 15-minute city concept?
The 15-minute city is an urban planning idea associated with Paris-based professor Carlos Moreno, developed around 2016, in which every resident can reach the essentials of daily life (work, food, healthcare, education, culture) within a 15-minute walk or cycle from their home. The concept gained wide attention after Paris Mayor Anne Hidalgo adopted it as a policy framework, and accelerated further during the pandemic when short-radius living became the norm for millions of people.
How do you measure whether a district is a 15-minute city?
Partly by mapping infrastructure to check whether the services are physically there, but also by measuring how people actually move. If residents are still driving across the city for everyday errands even though local amenities exist, the neighbourhood has not functionally achieved 15-minute status. Footfall and mobility data at district scale shows the real patterns of movement behind the theoretical accessibility.
What is cellular network analytics and how does it measure urban flows?
Cellular network analytics aggregates signals from mobile devices as they interact with 4G and 5G network infrastructure. Because nearly everyone carries a phone, this method captures movement across a whole district without cameras, apps or identification of individuals. It reveals the volume and direction of flows between zones, the times of day when a high street is busy, and how those patterns shift across seasons or after a new development opens.
Can footfall data help with high-street health assessments?
Yes. Volume and dwell-time data shows which parts of a high street are busy, which are in decline, and which recover after interventions like pedestrianisation, a new anchor tenant, or a public event. Tracking that over months and years gives planners and property owners evidence for investment decisions, so they do not have to rely on business rate data, which lags by years.