How BuildingsScore works

The whole method, in the open: how nearby places become seven dimension scores and one overall 0–5★ rating. No hidden weights.

The big picture

For any point you pick, BuildingsScore runs four steps:

  1. Gather everything nearby — places, roads, rail, parks, water, industry, airports, air quality.
  2. Weigh each thing by how close it is (a park across the street counts more than one a kilometre away) and how much it matters.
  3. Score seven dimensions from those weighted signals.
  4. Blend the dimensions into a single rating from 0.0 to 5.0.

The seven dimensions

Each dimension is scored 0–5 on its own, then mixed into the overall rating with the weight below. The weights reflect how much each tends to shape day-to-day life.

DimensionWhat it measuresBlend weight
ConvenienceShops, groceries, pharmacies, services within walking distance20%
QuietFreedom from busy roads, rail, nightlife, stadiums, flight noise18%
TransitAccess to metro, train, tram, bus, ferry15%
EnvironmentDistance from industry, waste, farmland, plus flood risk13%
NatureParks, forests, water, playgrounds, sport & recreation12%
SafetyEmergency services nearby, minus a few negatives12%
Air qualityA live air-quality index (where available)10%

If a dimension has no data for a spot — most often air quality — it's dropped and the remaining weights are re-normalized, so the overall rating is always a fair average of what we actually know.

Distance matters most: the decay rule

Every nearby thing has a range (in metres) beyond which it no longer counts. Within that range its effect fades with distance — full strength right on top, zero at the edge:

When several of the same thing are nearby, the nearest one dominates and extra ones add progressively less (the score saturates) — three supermarkets aren't three times one. Continuous features like a road or railway are treated as a single thing at their nearest point, not counted once per mapped segment.

How each dimension is scored

Different kinds of dimension call for different math:

Amenities — Convenience & Nature

More good stuff nearby pushes the score up toward 5, with diminishing returns. Each place adds its importance × closeness; the total is mapped onto 0–5 along a saturating curve, so going from nothing to a few amenities matters far more than going from many to many-plus-one.

Transit — best available wins

Transport modes substitute for one another: an excellent metro stop already makes an area well-connected, and lacking a tram doesn't drag it down. So Transit rewards the best access you have rather than summing modes — a town without a subway isn't penalized for it.

Nuisances — Quiet & Environment

These start clean at 5 and each nearby bad thing multiplies the score down by its severity × closeness. One loud neighbour can dent it; several compound. Severity is per-factor — a motorway or landfill weighs much more than a single bar.

Safety — a neutral baseline, nudged

Safety starts from a neutral baseline and is lifted by nearby emergency services (police, fire, hospital) and dragged down by a few negatives (e.g. a prison), then clamped to 0–5.

Note: BuildingsScore does not currently use point-level crime data (there's no free, global source — see Data sources). Safety here is a proxy from emergency-service proximity, not a crime statistic.

Air quality

Where available, a live Universal Air Quality Index (0–100) is mapped directly onto 0–5 stars. Where it isn't, the dimension is simply omitted from the blend.

Two estimated signals — stated plainly

Some things can't be read off a map of places, so BuildingsScore uses honest approximations:

The overall rating

The final number is the weighted average of whatever dimensions are present, rounded to one decimal — a clean 0.0 to 5.0 in 0.1 steps. Open any dimension in the app to see the individual places driving it, each with its distance and a walking route.

What this is, and isn't

The weights and ranges are opinionated, transparent defaults — a sensible general view of livability, not an objective truth. Your priorities may differ (a student might love the nightlife that costs a Quiet point). Treat the score as a fast, comparable first read, and always visit in person before making a decision.