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Quiet Corners

Scores rural US counties on stability, remoteness and sprawl risk, using census data

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Quiet Corners

Methodology & Data (readable without JS)

The quiet corners of America

Quiet Corners scores rural U.S. counties on stability, remoteness, sprawl risk and affordability, and surfaces the ones that are staying quiet and are likely to keep staying quiet. The methodology below sets out how stability, remoteness and sprawl risk are computed and how they roll up into the overall score, and the data trust model names the source behind each input. The dashboard below is public and free to use in your browser — no account, no signup.

Every data point comes from the U.S. Census Bureau or USDA, with one disclosed exception: interstate proximity (30% of the sprawl-risk composite, below) is measured against a hand-maintained waypoint list, not a government dataset. No commercial APIs, no scraped listicles, no vibes.

Explore the map below, or filter counties directly by stability, remoteness, sprawl risk or overall score.

Methodology

Independent scores, each 0-100:

Stability — Coefficient of variation (Bessel-corrected) plus linear regression slope across 5 years of population estimates. Low CV + flat slope = high stability. Weighted 60/40 CV-to-slope.

Remoteness — Great-circle distance from county centroid to nearest city with population over 25,000. Uses the full Census place gazetteer — capturing regional hubs, college towns, and county seats that rural residents actually drive to. The pipeline exports this as raw miles (distance_to_metro_mi), not a normalized 0-100 score; the dashboard’s Remoteness filter slides across that raw distance, up to 250 miles.

Sprawl Risk — A five-factor composite, all five live on this run: interstate proximity (30%), building permit trend (25%), state migration acceleration (20%), fast-growing metro proximity (15%), and recreation/retirement county typing (10%). Lower is better. Permits and metro proximity used to be dead — the Census API retired both endpoints — and are now read from the keyless bulk files on www2.census.gov instead (Building Permits Survey county annual files; PEP subcounty estimates).

A county missing an input is scored over the factors it does have, with the remaining weights renormalized, so a gap cannot quietly deflate a score toward “no sprawl risk”. A factor that scores 0 from real data still counts at full weight.

The trust panel on the dashboard lists, per factor, how many counties it scored above zero on the run that produced this page — read from the data, so it stays true across regenerations. Those counts are not coverage rates. A factor reads 0 both when its input is missing and when the county genuinely has no pressure from it: most rural counties carry no USDA recreation or retirement type at all, migration scores 0 for every state whose inward flow is flat or falling, and a county more than 100 miles from an interstate scores 0 there by construction. Permits are the one factor where a low count is partly a real gap — many rural counties have no usable multi-year permit series in the survey’s county files.

Overall — Quietness 55% and Affordability 45%. Quietness is itself stability 40%, remoteness 30%, and inverted sprawl risk 30%. Both levels renormalize over the inputs a county actually has, and a county with nothing scoreable gets no score rather than a zero. Livability was removed: it returned the affordability score verbatim, which double-weighted affordability while advertising a dimension that did not exist.

Counties must have a USDA Rural-Urban Continuum Code of 6 or higher (nonmetro with urban population under 20,000) to appear in results. Within qualifying counties, candidate towns (incorporated places with population 1,000-3,000) are surfaced with scores inherited from their parent county.

Data trust model

Every figure on this page is regenerated from source by a pipeline that refuses to invent a number it does not have — but it discloses gaps two different ways depending on the dimension. Stability, remoteness and affordability report a missing county’s field as absent (null) rather than defaulted; the coverage panel states the real scored percentage for each. The sprawl sub-factors instead report a per-factor non-zero count in the sprawl-factors panel, and a factor with no input for a county is dropped from that county’s composite with the remaining weights renormalized — never defaulted to a convenient number. The generation timestamp is stamped into the exported data rather than typed by hand.

Sources the pipeline draws on:

  • County populations: Census PEP Vintage 2024 (2020-2024)
  • County coordinates: Census Gazetteer 2024
  • Nearest cities: Census Place Gazetteer 2024 (all places >25K)
  • Rural classification: USDA Rural-Urban Continuum Codes 2023
  • County typing: USDA County Typology Codes 2015 (recreation/retirement flags)
  • Interstate proximity: Static, hand-maintained waypoint list along major US interstates (422 points across 30 route chains, no duplicates), with distance measured to the nearest route segment rather than the nearest point — not a government dataset
  • County geometry: us-atlas counties-10m.json (ISC License, © the us-atlas project) — a TopoJSON build derived from Census TIGER/Line cartographic boundaries, served from this domain rather than a third-party CDN
  • Building permits: Census Building Permits Survey, county annual bulk files (www2.census.gov/econ/bps/County/) — the API timeseries endpoint is retired; these keyless files replace it
  • Fast-growing metro proximity: Census Subcounty Population Estimates bulk file (SUB-EST2024) — the PEP place API endpoint is retired; this keyless file replaces it
  • State migration: Census ACS 1-Year B07001 (Geographical Mobility)
  • Affordability: Census ACS 5-Year (median home value, gross rent, household income)
  • Candidate towns: Census Subcounty Population Estimates 2024 (SUB-EST2024)

No data is sampled, simulated, or interpolated beyond filling the 2001-2009 intercensal gap with Census-published CSV data. What you see is what the Census Bureau reported.

The map, the geometry and every byte of data on this page are served from this domain. There are no third-party scripts, no tile servers, and no analytics on it.

Methodology & Data Trust Model

The quiet corners of America

Quiet Corners scores rural U.S. counties on stability, remoteness, sprawl risk and affordability, and surfaces the ones that are staying quiet and are likely to keep staying quiet. The methodology below sets out how stability, remoteness and sprawl risk are computed and how they roll up into the overall score, and the data trust model names the source behind each input. The dashboard below is public and free to use in your browser — no account, no signup.

Every data point comes from the U.S. Census Bureau or USDA, with one disclosed exception: interstate proximity (30% of the sprawl-risk composite, below) is measured against a hand-maintained waypoint list, not a government dataset. No commercial APIs, no scraped listicles, no vibes.

Explore the map below, or filter counties directly by stability, remoteness, sprawl risk or overall score.

Methodology

Independent scores, each 0-100:

Stability — Coefficient of variation (Bessel-corrected) plus linear regression slope across 5 years of population estimates. Low CV + flat slope = high stability. Weighted 60/40 CV-to-slope.

Remoteness — Great-circle distance from county centroid to nearest city with population over 25,000. Uses the full Census place gazetteer — capturing regional hubs, college towns, and county seats that rural residents actually drive to. The pipeline exports this as raw miles (distance_to_metro_mi), not a normalized 0-100 score; the dashboard’s Remoteness filter slides across that raw distance, up to 250 miles.

Sprawl Risk — A five-factor composite, all five live on this run: interstate proximity (30%), building permit trend (25%), state migration acceleration (20%), fast-growing metro proximity (15%), and recreation/retirement county typing (10%). Lower is better. Permits and metro proximity used to be dead — the Census API retired both endpoints — and are now read from the keyless bulk files on www2.census.gov instead (Building Permits Survey county annual files; PEP subcounty estimates).

A county missing an input is scored over the factors it does have, with the remaining weights renormalized, so a gap cannot quietly deflate a score toward “no sprawl risk”. A factor that scores 0 from real data still counts at full weight.

The trust panel on the dashboard lists, per factor, how many counties it scored above zero on the run that produced this page — read from the data, so it stays true across regenerations. Those counts are not coverage rates. A factor reads 0 both when its input is missing and when the county genuinely has no pressure from it: most rural counties carry no USDA recreation or retirement type at all, migration scores 0 for every state whose inward flow is flat or falling, and a county more than 100 miles from an interstate scores 0 there by construction. Permits are the one factor where a low count is partly a real gap — many rural counties have no usable multi-year permit series in the survey’s county files.

Overall — Quietness 55% and Affordability 45%. Quietness is itself stability 40%, remoteness 30%, and inverted sprawl risk 30%. Both levels renormalize over the inputs a county actually has, and a county with nothing scoreable gets no score rather than a zero. Livability was removed: it returned the affordability score verbatim, which double-weighted affordability while advertising a dimension that did not exist.

Counties must have a USDA Rural-Urban Continuum Code of 6 or higher (nonmetro with urban population under 20,000) to appear in results. Within qualifying counties, candidate towns (incorporated places with population 1,000-3,000) are surfaced with scores inherited from their parent county.

Data trust model

Every figure on this page is regenerated from source by a pipeline that refuses to invent a number it does not have — but it discloses gaps two different ways depending on the dimension. Stability, remoteness and affordability report a missing county’s field as absent (null) rather than defaulted; the coverage panel states the real scored percentage for each. The sprawl sub-factors instead report a per-factor non-zero count in the sprawl-factors panel, and a factor with no input for a county is dropped from that county’s composite with the remaining weights renormalized — never defaulted to a convenient number. The generation timestamp is stamped into the exported data rather than typed by hand.

Sources the pipeline draws on:

  • County populations: Census PEP Vintage 2024 (2020-2024)
  • County coordinates: Census Gazetteer 2024
  • Nearest cities: Census Place Gazetteer 2024 (all places >25K)
  • Rural classification: USDA Rural-Urban Continuum Codes 2023
  • County typing: USDA County Typology Codes 2015 (recreation/retirement flags)
  • Interstate proximity: Static, hand-maintained waypoint list along major US interstates (422 points across 30 route chains, no duplicates), with distance measured to the nearest route segment rather than the nearest point — not a government dataset
  • County geometry: us-atlas counties-10m.json (ISC License, © the us-atlas project) — a TopoJSON build derived from Census TIGER/Line cartographic boundaries, served from this domain rather than a third-party CDN
  • Building permits: Census Building Permits Survey, county annual bulk files (www2.census.gov/econ/bps/County/) — the API timeseries endpoint is retired; these keyless files replace it
  • Fast-growing metro proximity: Census Subcounty Population Estimates bulk file (SUB-EST2024) — the PEP place API endpoint is retired; this keyless file replaces it
  • State migration: Census ACS 1-Year B07001 (Geographical Mobility)
  • Affordability: Census ACS 5-Year (median home value, gross rent, household income)
  • Candidate towns: Census Subcounty Population Estimates 2024 (SUB-EST2024)

No data is sampled, simulated, or interpolated beyond filling the 2001-2009 intercensal gap with Census-published CSV data. What you see is what the Census Bureau reported.

The map, the geometry and every byte of data on this page are served from this domain. There are no third-party scripts, no tile servers, and no analytics on it.

Data Provenance

Filters
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Population [i] Total resident population. [Source: US Census PEP V2024]
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County County Name St US State Abbreviation [Source: US Census] Pop Total resident population [Source: US Census PEP V2024] Overall Weighted composite score of all metrics Stability Stability score (higher is better) [Source: US Census PEP] Affordability Affordability score (higher is better) [Source: US Census ACS] Remote Remoteness in miles (higher is better) [Source: US Census Gazetteer]

Documentation

Quiet Corners documents itself on this page: the Methodology & Data panel above holds the scoring method, every data source, and the trust model for the run that produced these numbers. There is no repository or installer — the dashboard in your browser is the product.