Housing Ready Methodology

The Housing Ready layer is a national, grid-based signal of where, among developable land, new housing adds the most value because people can reach the things daily life needs with short trip. It scores every location in the United States from 0 to 7 based on access to groceries, services, schools, health care, parks, and transit, plus regional access to jobs. The result reads like a smart-growth map whereby dense, mixed, transit-served places score high, and rural and auto-dependent land scores lower. The score deliberately excludes price because a housing premium is a symptom of constrained supply in a desirable place.

What it measures

Every location is scored on seven categories of access. The first six measure short, local access based on how much is reachable within a short trip. The seventh, employment access, measures regional opportunity based on how many jobs are reachable across the wider commute shed. Each category contributes a value from 0 to 1, and the seven sum to a total from 0 to 7, where 7 means propinquity to all factors.

Why access, and not other measures

We settled on direct access score after testing other indirect measures:

• Predicted driving and auto ownership. Measures of how much a household would need to drive capture travel efficiency. A low-driving score tells you a place is convenient on average but not whether a specific location has a grocery, a school, or a park within walking distance.
• Off-the-shelf walkability indices. These ready-made scores lean heavily on jobs, streets, and transit, and their "diversity" component measures the mix of where people work rather than what residents can reach. At the neighborhood scale that housing diversity signal is noisy and behaves more like a measure of how self-contained an area is than of genuine access.

So we measure access directly by counting the actual destinations a person can reach on foot from each location, across the seven categories below. This keeps the signal about the place's physical access to daily needs.

The seven categories of access

Points of interest for categories 1–4 come from an open, OpenStreetMap-derived business directory; parks combine open land-use polygons with named park locations, so small municipal parks that aren't mapped as polygons are still counted; transit comes from agencies' published GTFS schedules nationwide; and employment access is drawn from the same regional job-gravity model used elsewhere in CommunityScale's Housing + Transportation analysis.

How the score is computed

For each location and each category, the model sums up nearby destinations, weighting each by how far away it is whereby closer destinations count more. That weighted sum is then passed through a saturating curve: the first grocery store or transit stop within a short trip moves the score a lot, while the tenth adds very little.

The computation runs on a 150-meter national grid in an equal-area projection, so that distances measured in meters are consistent everywhere from Maine to California. The commercial, civic, and personal services category uses a higher saturation threshold so that it reads the intensity of a commercial district rather than simply whether one exists. Parks are handled differently from the other categories: the model measures the distance to the nearest park edge, so that the interior of a large park counts as fully served rather than penalized for being far from its center.

Distance decay: a short-range signal

The single most important calibration is how quickly access falls off with distance. A long, generous decay summed over a wide radius saturates everything, even sprawl has one of almost everything within a half-hour drive. To keep the signal meaningful, access is short-range by design, with only a soft tail beyond a comfortable trip:

Transit feeds are de-duplicated so that the same physical stop served by multiple agencies is not counted several times, and ferry landings are treated as their own mode rather than as rail.

Environmental constraints: land less suitable for building

Suitability answers where it makes sense; a separate constraint layer flags land that is less suitable for building. Any location that falls inside one of these constraints is set aside from the suitability surface rather than simply dimmed, so the layer never suggests strong value on land that is poorly suited to new housing.

These constraints are also available as optional show-on-demand overlays on the map, so users can see exactly what is being set aside at any location.

The constraint layers come from public datasets. Protected land is drawn from the USGS Protected Areas Database of the United States (PAD-US), keeping GAP status 1 and 2 — land managed for permanent biodiversity conservation — while GAP status 3 multiple-use public land is left in as developable. Flood hazard comes from FEMA's National Flood Hazard Layer, surface water from the USGS National Hydrography Dataset, and steep slopes from a national digital elevation model.

Reading the map

On the map, darker color means more suitable. The ramp runs from blank, through teal and blue, to a near-black indigo at the top of the scale. Low-access land fades toward transparent so the eye is drawn to the places where access is strongest. Hovering over any location shows the live breakdown of all seven category scores and lists any environmental constraints present there.

The layer is rendered at a single, uniform resolution everywhere in the country, so the same crisp detail holds whether you are looking at a major metro or a small town. The underlying score is identical everywhere; zooming only changes how much of it you can see at once.

Coverage and data gaps

The score is only as complete as the open datasets behind it. Points of interest, parks, and transit come from continuously-updated community and agency data — OpenStreetMap-derived business and land-use data, and agencies' published transit schedules — so coverage is uneven and never perfectly current. A destination can be missing, miscategorized, or out of date, and small or recently-added features such as a neighborhood park or a new grocery are the most likely to be under-counted. The boundaries between data sources, the constraint layers, and the 150-meter grid each introduce their own edge effects. Read the layer as a regional screening signal, not an authoritative inventory of any single location, and verify specifics on the ground.

Known limitations

• Straight-line distance. Access is measured as the crow flies rather than along the transportation network, which can overstate access where rivers, highways, or rail cuts break the street grid.
• Render-resolution masking. Constraints are applied at the resolution of the map tile rather than by fractional area, which is appropriate at the zoom levels shown but is not a parcel-level determination.
• Coverage. The current national run covers the continental United States; Alaska, Hawaii, and the territories are handled separately. Park coverage combines open land-use polygons with named park locations — which catches most municipal parks — but the smallest or most recently-added parks can still be missing.
• A planning signal, not a site-suitability study. The layer is a regional screening tool for comparing places. It is not a substitute for parcel-level due diligence, zoning analysis, or an environmental site assessment.