How the Location Finder Works

Open methodology. No black boxes, no hidden formulas. Here is exactly how we score every county, what data we use, and how your weights shape the results.

The short version

The Location Finder scores every U.S. county across 10 dimensions that matter to homesteaders. Each dimension is normalized to a 0–100 scale so they can be compared fairly. You set weights for the dimensions you care about most, and we calculate a weighted average to produce your personal match score.

A county that scores 85 on water availability and 40 on growing season will rank differently for someone who prioritizes water than for someone focused on year-round gardening. Same data, different priorities, different results.

10 Scoring Dimensions

1. Water Availability & Rights

Data: NOAA precipitation records + state water rights classification

Measures annual precipitation in inches combined with whether the state uses riparian, prior appropriation, or hybrid water rights. Counties with higher rainfall and more permissive water rights score higher. A county receiving 50+ inches of annual precipitation in a riparian-rights state scores near the top; an arid county in a prior-appropriation state scores near the bottom.

Example: A county in western North Carolina with 52 inches of annual precipitation and riparian water rights scores 88/100.
Precipitation data updated from NOAA Climate Normals (30-year averages).

2. Property Taxes

Data: U.S. Census Bureau, American Community Survey (ACS)

Uses the county median property tax paid annually. Lower taxes score higher. Counties are ranked against the national range, so a county with a $600 median annual tax scores much higher than one with a $6,000 median. The normalization inverts the scale: the lowest-tax counties get the highest scores.

Example: A rural Alabama county with a $420 median property tax scores 94/100.
ACS 5-year estimates, updated annually.

3. Building Codes

Data: ICC state adoption records + Census county population

Evaluates state-level adoption of the International Residential Code (IRC) and factors in county population as a proxy for local enforcement intensity. States with no statewide building code score higher. Within states that have adopted the IRC, less-populated counties score higher because rural counties tend to enforce codes less strictly.

Example: A county in a state with no statewide code and a population under 10,000 scores 92/100.
Code adoption status reviewed annually; population from Census ACS.

4. Growing Season

Data: NOAA Climate Normals, frost-free days

Counts the average number of frost-free days per year for each county. More frost-free days means a longer growing season and a higher score. Counties in the Deep South with 240+ frost-free days score near the top. Northern counties with fewer than 100 frost-free days score near the bottom.

Example: A county in southern Mississippi with 260 frost-free days scores 91/100.
NOAA Climate Normals based on 30-year averages, updated each decade.

5. Land Cost

Data: U.S. Census Bureau, American Community Survey (ACS)

Uses the county median home value as a proxy for land cost. Lower values score higher. The normalization inverts the scale so that affordable counties rank above expensive ones. A county with a $75,000 median home value scores far higher than one at $500,000.

Example: A county in rural West Virginia with a $68,000 median home value scores 95/100.
ACS 5-year estimates, updated annually.

6. Gun Laws

Data: State statutory analysis (permit, carry, and purchase requirements)

Evaluates state-level firearms regulations including concealed carry permit requirements, open carry legality, and purchase restrictions. States with constitutional carry (no permit required) and unrestricted open carry score highest. States requiring permits for both purchase and carry score lowest.

Example: A county in a constitutional-carry state with no purchase permits scores 96/100.
State law data reviewed and updated as legislation changes.

7. Natural Disaster Risk

Data: FEMA National Risk Index + FEMA disaster declarations

Combines the FEMA National Risk Index composite rating with the county's historical disaster declaration count. Lower combined risk scores higher. A county with a "relatively low" NRI rating and few historical declarations scores near the top. Coastal and tornado-alley counties with "relatively high" or "very high" ratings score lower.

Example: An inland New England county with a "relatively low" NRI rating and 8 historical declarations scores 82/100.
NRI updated periodically by FEMA; declarations updated as events occur.

8. Off-Grid Legality

Data: State statutory analysis (rainwater, solar, composting toilet laws)

Evaluates state laws governing rainwater harvesting, off-grid solar installation, and composting toilet use. States where all three are explicitly legal with no permit requirements score highest. States that restrict or ban any of these practices score lower. Each legal category contributes equally to the score.

Example: A county in a state where rainwater collection, solar, and composting toilets are all unrestricted scores 95/100.
State law data reviewed and updated as legislation changes.

9. Crime

Data: FBI Uniform Crime Reporting (UCR) program

Uses violent crime rate and property crime rate per 100,000 residents. Both rates are combined and normalized so that lower crime counties score higher. Very rural counties with minimal reported crime score near the top. Urban counties with high per-capita crime rates score near the bottom.

Example: A rural county with a combined crime rate in the bottom 5% nationally scores 93/100.
FBI UCR data released annually, typically with a 1-2 year lag.

10. Nuclear & Military Target Distance

Data: Census population density as proxy for target proximity

Uses population density as a proxy for distance from potential nuclear or military targets, since major targets correlate strongly with population centers, military installations, and critical infrastructure. Less populated counties score higher. This is a rough proxy, not a precise measurement -- but it captures the general pattern that remote, low-population areas are farther from likely targets. Note: This proxy is unreliable for low-population rural counties near missile installations, particularly in the Great Plains (North Dakota, Wyoming, Nebraska). Verify independently if this dimension matters to your decision.

Example: A county with fewer than 10 people per square mile scores 90/100.
Population density from Census ACS, updated annually.

How Weights Work

Each of the 10 dimensions produces a score from 0 to 100. Your weights determine how much each dimension matters in the final calculation. The formula is a simple weighted average:

Match Score = (Weight1 × Score1 + Weight2 × Score2 + …) ÷ (Weight1 + Weight2 + …)

If you set all weights equally, every dimension contributes the same amount. If you max out "Growing Season" and set everything else to minimum, the results will heavily favor southern counties with long frost-free periods. If you max out "Water Availability" instead, the top results shift toward the Southeast and Pacific Northwest.

Different users get different rankings from the same data. A retiree prioritizing low taxes and low crime will see a completely different top-10 list than a young family prioritizing growing season and water. That is the point.

What We Don't Do

  • We don't combine dimensions into a single "freedom score" or political ranking.
  • We don't rank states as "best" or "worst." Every county is scored individually.
  • We don't use racial or ethnic demographic data in any dimension.
  • We don't log your searches, store your weight settings, or track which counties you view.

Client-Side Computation

When you open the Location Finder, a single JSON file containing all county data loads from our CDN into your browser. After that initial download, every calculation -- scoring, weighting, filtering, sorting -- runs entirely on your device. No server calls, no API requests, no round trips.

This means we literally cannot see what you search for. We do not know which weights you set, which counties appear in your results, or which ones you click on. Your search activity exists only in your browser's memory and disappears when you close the tab.

No Government Affiliation

We have no government affiliations. This tool was built by a private individual using publicly available federal data. We are not affiliated with FEMA, the Census Bureau, NOAA, the FBI, or any other government agency. All data is sourced from public datasets that any citizen can access.

Data Limitations

County-level averages may not reflect conditions at a specific property. A county with low average property taxes may still have expensive parcels. A county with a long growing season may have microclimates with shorter ones. Always verify conditions for the specific property you are considering.

Federal datasets are updated on different schedules. Census ACS data is released annually with a 1-2 year lag. NOAA Climate Normals are updated each decade. FEMA disaster declarations are updated as events occur. FBI crime data typically lags by 1-2 years. We pull the most recent available data for each source.

State laws change. Gun laws, off-grid regulations, and building codes can be updated by state legislatures at any time. We review and update our legal data periodically, but there may be a delay between a law changing and our data reflecting it.

Data Resolution

Not all dimensions have true county-level data. Here's what's county-specific and what's a state-level proxy:

County-Level Data

  • Natural disaster risk (FEMA NRI)
  • Disaster declaration history (FEMA)
  • Population, income, home value, property tax (Census ACS)
  • Nearest hospital distance (CMS)
  • Growing hardiness zone (derived from weather)

State-Level Proxies

  • Weather & growing season (latitude regression — no NOAA station matching yet)
  • Crime rates (FBI UCR state averages applied to all counties)
  • Broadband availability (FCC state averages)
  • Lyme disease risk (CDC state averages)
  • Feral hog presence (USDA state-level)

Two counties in the same state will show identical values for state-level proxy dimensions. We're improving county-level resolution with each data refresh.

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