Within a 10-minute walk explained simply: reading a metric across the neighbourhood

An ATM two streets away is still your ATM

Every MapBees area is small - about 350 metres across, a few minutes on foot. Count ATMs inside just that area and most of London reads as “none”, which is true and useless: nobody minds walking two streets for cash.

Within a 10-minute walk reads every metric over an area and its neighbours: the area itself, the six areas touching it, and the twelve beyond those - nineteen areas, about 800 metres across. Nearer areas count more than farther ones. The field calls this a neighbourhood, or focal, statistic; the shape it is computed on is a k-ring of hexagons. What it does is simple: it draws the map the way people actually experience a place.

Within a 10-minute walkthe field's term: Neighbourhood (k-ring) statistic

London map of ATMs counted in each area on its own, mostly dark with scattered bright dots — Just this spot: ATMs counted inside each area alone. A scatter of dots, and most of the city reads as none.

London map of ATMs counted within a 10-minute walk, showing connected bright patches at town centres — Within a 10-minute walk: the same ATMs, read over each area and its neighbours. Town centres appear as patches, and the map now shows what you can reach.

How the neighbourhood is counted

The area itself counts in full. Each of the six touching areas counts at 0.7. Each of the twelve areas one step further out counts at 0.4. That is a distance decay- a plain way of saying that an ATM next door matters more than one at the edge of the walk.

The Look at control with its explainer open: two hexagon flowers, Just this spot with one highlighted centre and Within a walk with all nineteen highlighted, and text explaining the 100%, 70% and 40% weights — Hover the little hexagon flower next to 'Look at' and the app draws the idea: one area, or the area plus its two rings, with the weights spelled out.

ATMs within a 10-minute walk of one area

In the area itself: 1 × 1.0 = 1.0
In the six touching areastwo ATMs among them: 2 × 0.7 = 1.4
In the twelve areas beyondthree ATMs among them: 3 × 0.4 = 1.2
Within a 10-minute walk: 1.0 + 1.4 + 1.2 = 3.6

The weights add up to 10 across all nineteen areas (1 + 6 × 0.7 + 12 × 0.4), which is why a neighbourhood total is about ten times a typical single-area count.

Switching it on

Every count of places has a Look at row - on the Amount, Variety, Fair share and Missing maps, and on each factor of a score. The default is “Just this spot”. Change it to “Within a 10-minute walk” and the map redraws.

Where to click

Map type
Amount
Atm
Look at: Within a 10-minute walk

The Look at dropdown set to Within a 10-minute walk, with the hexagon flower beside it lit — The hexagon flower lights up when the walk is on, so you can tell at a glance whether a factor is being read across its neighbours.

The Amount panel with Atm selected and Look at set to Within a 10-minute walk — The sentence under the badge now reads 'Atm, within a 10-minute walk' - the setting is part of the measure's name, so a shared link says it too.

Why it is missing for some metrics

A walk adds counts up, and averages cannot be added: the average income of nineteen areas is not the sum of nineteen incomes. So the row exists only for counts of places - shops, services, transit stops.

Why the Clusters map has no such row

The cluster test already reads each area's neighbours. Adding a walk would count the neighbourhood twice, so on that map the row is not rendered at all.

Reading the map

Hover card over a London area reading Atm, 0 — Just this spot: this area has no ATM of its own.

Hover card over the same kind of London area reading Atm, 3 — Within a walk: the same neighbourhood has three ATMs' worth within reach, nearer ones counting more.

Legend reading Atm, a purple to yellow ramp from 0 to the highest neighbourhood count in London — The legend's top end is now a neighbourhood total, roughly ten times a single-area count, so the numbers are bigger and the map is smoother.

It changes the answer, not just the picture

Widening a question often fixes it. “ATMs per resident in this area” is zero almost everywhere, because most areas have no ATM; “ATMs within a walk per resident within a walk” is a real number nearly everywhere. The division still happens, just over the same walk on both sides - places within reach, divided by people within reach - so a rate stays honest.

Where it does its best work

Most posts in this series lean on the walk without making a fuss of it. The gap analysis reads grocery stores within a walk so shortfalls become whole stores rather than fractions; the variety indices need a neighbourhood's worth of restaurants before “how mixed” means anything. Any time a single area is too small to hold the thing you are counting, the walk is the honest unit.

Open ATMs within a walk in London

The whole idea, in four lines

Within a 10-minute walk reads a metric over an area and its two rings of neighbours: nineteen areas, about 800 m across.
Nearer counts more: the area at 1.0, the touching ring at 0.7, the outer ring at 0.4. That is a distance decay.
It is offered for counts of places only, because averages cannot be added - and the Clusters map drops the row entirely, because it already reads the neighbours.
The map gets smoother and the numbers roughly ten times bigger; lone spikes dilute and real districts show up as patches.
It is part of the measure's name, so a shared link carries it and the badge says it.

Quick questions

What does 'Within a 10-minute walk' do?

Instead of counting only what is inside one small area, it adds up the area and its two rings of neighbours - 19 areas, about 800 metres across - with nearer neighbours counting more than farther ones.

Why do nearer areas count more?

Because a café next door matters more than one 800 metres away. The area itself counts in full, the first ring at 0.7 and the second at 0.4, which is a simple distance decay.

Why does the map look smoother?

Because every value is now a neighbourhood total rather than a single-area count. Lone spikes are diluted and genuine districts show up as connected patches - which is usually the truer picture of what people can reach.

Why is it unavailable for some metrics?

A walk adds counts up, and averages cannot be added. So it is offered for counts of places - shops, services, transit stops - and not for an average income or a share.

Does 'Per 1 000 residents' still work within a walk?

Yes. The count and the residents are both totalled over the same walk, so the rate stays honest - places within reach, divided by the people within reach.

See it on a real map

The best way to understand the score is to play with it. The full app is on a free tier, with no sales call.

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About the author

Tinkal Gogoi(LinkedIn profile, opens in a new tab)Founder & Location Data Engineer

Builds MapBees's location-intelligence pipeline end to end — census and Overture Maps ingestion, H3 hex scoring, and the map interface — and writes the methodology behind every number on the site.

Within a 10-minute walk: the neighbourhood view, explained simply