How many people live within walking distance of a site?

To find how many people live within walking distance of a site, draw the area someone can walk in 10 or 15 minutes along real streets, then add up the residents of the small population hexagons inside it. In xMap Flows that is two blocks: Travel area on foot, then Demographics, which returns the total, men and women, and nine age groups. For a quick first pass you can skip the walk and use a circle of 500 m or 1 km; the Demographics block describes 1 km as a walk of about twelve minutes.

This article is for anyone whose customers arrive on foot: convenience and grocery shops, pharmacies, bakeries, parcel pickup points, primary clinics, nurseries, and transport planners asking who lives within a walk of a stop. It covers the two ways to draw the area, which age groups matter for walk-in businesses, an example in Bangkok, what the count leaves out, and an AI employee that does it for a list of sites.

Two ways to draw the walk

Both are added up from the same population hexagons.

The choice between circles and travel areas in general, including drive times, is in a radius or a drive time. For walking specifically, the difference is usually largest where something blocks the way: a site beside a canal, a rail line or an expressway can reach only half of its circle on foot.

Which residents matter for a walk-in business

The total is the headline, but the age groups often decide the case. Demographics returns residents in nine age groups and three wider ones, children 0 to 19, adults 20 to 59 and seniors 60 and over, with the shares of children and seniors.

• Pharmacies and primary clinics: the seniors share. Older residents visit more often and are more likely to walk to the nearest one.
• Nurseries and after-school clubs: children under 10, and adults of parenting age.
• Convenience shops and bakeries: the total and the density, people per square kilometre; a dense walk area means more customers for each step of the walk.
• Pickup points: adults 20 to 59, who order most parcels and pass by on the way home.

An example in Bangkok

A made-up case. A pharmacy chain in Bangkok is offered two shophouses about a kilometre apart. One fronts a main road beside an expressway; the other is on a lane in a dense neighbourhood. It counts the residents within a 1 km circle and within a 10-minute walk of each. Suppose the figures read (invented for illustration):

Invented figures for illustration; not real figures for Bangkok.

By circle, the two look alike. By walk, the main-road shophouse loses more than half its residents, because the expressway cuts off the homes on the far side and its crossings are few. The lane shophouse keeps most of its circle, with a denser, older population. For a pharmacy that relies on neighbours walking in, the lane wins, even though the main road would be more visible to drivers.

The same two-step count would work in Cairo, Mumbai, Lyon or Montreal, all in countries with population data.

What the count leaves out

• Workers and visitors. Demographics counts residents, not the people who work in or pass through the area. For presence by day, add Mobility Footfall; the two are compared in footfall vs the people who live nearby.
• Whether people will walk. Heat, steep streets, poor pavements and busy crossings put people off. The walking area follows streets, not comfort.
• Rivals. Residents within a walk may already have a pharmacy at their door. Count rivals in the same area with Nearby places.
• Estimates. When the routing service cannot draw a walking area, the block uses a circle at a typical walking speed and says the area is an estimate.

Counting residents for a list of sites with an AI employee

1. Bring in the sites with My data.
2. Add Travel area: A travel time, Walking, 10 minutes, Each incoming place.
3. Add Demographics set to look in the Area of interest, with Totals for each area: one row per site's walk area.
4. Add Nearby places in the same areas to count the rivals within the walk.
5. Add Calculated field for residents per rival, then Sort and limit to put the best first.
6. Send it by Email. In the inbox: each site's residents within a 10-minute walk, the age shares, density, rivals in the same walk, and residents per rival.

Run it once for a shortlist. If you open sites often, keep the flow and add new candidates to the table; each run counts only what you give it.