New Housing Units per 1,000 Residents, Tennessee Counties 2020-2025

What follows is the transcript of this chat as State Planner generated it. It is here to show how the answer above was arrived at: every query State Planner ran, what each one returned, and where the data came from.

transcript.md

↑ Contents

State Planner chat · https://stateplanner.com

State: Tennessee (TN)
Started: October 22, 2026, 12:27 AM UTC
Runtime: 42 sec
Status: completed

Prompt

Which Tennessee counties permitted the most new homes from 2020 through the latest year, how much of that was apartments of five units or more, and how does it compare with each county's population growth over the same years? Map new homes per 1,000 residents."

Model: Anthropic: Claude Haiku 5.5 (anthropic/claude-haiku-5.5, via openrouter)

Response

I'll start with the permit table's columns and the county population table's columns.

Next I'll check which years exist in each table and whether the county codes match.

The latest permit year is 2025, and 94 of 95 counties appear in permits. I'll pull the 2020–2025 totals per county, joined to population at 2020 and 2025.

The query failed because of a stray quote at the end of the SQL. Rerunning it corrected.

Pickett County has no permit rows, and several counties show zero. I'll check whether those zeros hold across all years or reflect counties whose permit offices don't report.

Zeros in Jackson, Morgan, Bledsoe, Hancock and Wayne are scattered, so those counties mostly show little or no permitting. Pickett has no rows at all. Next I'll map the per-1,000 rate in bands.

The map is drawn. Next I'll get the chart guide before a stacked bar of the top counties by new homes.

Where new homes were permitted, 2020–2025 (latest permit year is 2025)

Davidson, Knox, Rutherford, Montgomery and Hamilton permitted the most new homes in 2020–2025. Davidson alone accounts for about a quarter of the state's 295,540 units, and about half of the state's 89,921 units in buildings of five or more units.

Top 10 counties by new housing units, 2020–2025

County	New units	In 5+ unit buildings	5+ share	Units per 1,000 residents (2025)	Population change 2020–2025
Davidson	68,656	48,038	70%	92.0	+4.2%
Knox	22,126	8,570	39%	43.3	+6.4%
Rutherford	20,068	2,217	11%	51.9	+12.5%
Montgomery	19,737	7,208	37%	79.0	+12.9%
Hamilton	13,572	3,146	23%	34.7	+6.2%
Wilson	12,852	1,087	8%	73.4	+17.7%
Williamson	12,565	2,692	21%	46.2	+9.0%
Sumner	12,359	2,786	23%	57.3	+9.2%
Shelby	11,062	5,089	46%	12.2	−2.1%
Maury	10,793	1,216	11%	91.4	+16.0%

Population figures are Census July 1 estimates: 2020 (current release) and 2025.

Top 15 counties by new housing units, 2020-2025, split by building size

The chart shows the top 15 counties' new units, split into 5+ unit buildings and everything else. Apartments make up the largest share in Davidson, Shelby and Montgomery; Wilson, Maury and Rutherford are mostly single-family and smaller buildings.

Permits per 1,000 residents compared with population growth

The highest rates are Davidson (92.0), Maury (91.4), Montgomery (79.0), Sevier (72.2), Wilson (73.4) and Loudon (69.9). Several of these also grew fast, notably Maury (+16.0%), Wilson (+17.7%) and Montgomery (+12.9%).
Davidson has the most units, but its rate sits near the top because its population is large. Its population grew only +4.2%, slower than the state's +5.6%.
Shelby permitted 11,062 units, but at 12.2 per 1,000 its rate is among the lowest of the large counties, and its population fell (−2.1%).
Sevier and Loudon permitted high rates with modest growth (+2.5% and +15.6%), so rate and growth do not always move together.

New housing units per 1,000 residents, 2020-2025

Map legend: each county is shaded by its 2020–2025 new housing units per 1,000 residents in 2025. Darker red means more units per resident. Bands: under 10, 10–20, 20–35, 35–50, 50–70, 70 and over. Grey means no permit data (Pickett County has no rows in the permit table). Click a county for its totals and 2025 population.

Notes and caveats

Permits are authorizations to build, not starts or completions. Some permitted units are never built.
"Per 1,000 residents" uses each county's 2025 population as the denominator for all six years of permits. Counties that grew over the period would show a somewhat higher rate using average population.
Population figures are Census estimates, not counts.
Jackson, Morgan, Bledsoe, Hancock and Wayne show near-zero permits; the table has few or zero permits there in most years, so their low rates are what the data reports.
The 5+ unit column counts housing units in buildings of five or more units, the apartment category, not buildings.

Chart Queries

Top 15 counties by new housing units, 2020-2025, split by building size

     WITH perm AS (
             SELECT c.name,
                    sum(p.units_5plus) AS "Apartments 5+ units",
                    sum(p.units_total) - sum(p.units_5plus) AS "Other units"
               FROM tn_bps_county_permits p
               JOIN tn_census_counties c ON c.geoid = p.geoid
              WHERE p.year BETWEEN 2020 AND 2025
           GROUP BY c.name
           ORDER BY sum(p.units_total) DESC
              LIMIT 15
          )
   SELECT name AS "County",
          "Other units" AS "Other housing units",
          "Apartments 5+ units" AS "Units in 5+ unit buildings"
     FROM perm,
          LATERAL (
             VALUES (1)
          ) v(x)
 ORDER BY "Apartments 5+ units" + "Other units" DESC

charts/turn-1-top-counties-permits-5plus.csv

Picture: charts/turn-1-top-counties-permits-5plus.png

Exploratory Queries

Query 1 — Check which permit years exist from 2019 on and totals per year

   SELECT p.year,
          count(*) AS counties,
          sum(p.units_total) AS units,
          sum(p.units_5plus) AS units_5plus
     FROM tn_bps_county_permits p
    WHERE p.year >= 2019
 GROUP BY p.year
 ORDER BY p.year

year	counties	units	units_5plus
2019	94	41361	11262
2020	94	49719	15612
2021	94	57484	19690
2022	94	52637	17973
2023	94	47463	15036
2024	94	44863	11183
2025	94	43374	10427

data/turn-1-query-1.csv

Query 2 — Check population estimate years available from 2019 on

   SELECT YEAR,
          series,
          count(*) AS counties,
          sum(pop_estimate) AS pop
     FROM tn_census_county_pop_est
    WHERE YEAR >= 2019
 GROUP BY YEAR,
          series
 ORDER BY YEAR

year	series	counties	pop
2019	intercensal	95	6862615
2020	postcensal	95	6927736
2021	postcensal	95	6966687
2022	postcensal	95	7063325
2023	postcensal	95	7153029
2024	postcensal	95	7251291
2025	postcensal	95	7315076

data/turn-1-query-2.csv

Query 3 — Per-county permits 2020-2025, 5+ share, population change and permits per 1,000

     WITH perm AS (
             SELECT geoid,
                    sum(units_total) AS units,
                    sum(units_5plus) AS units_5plus
               FROM tn_bps_county_permits
              WHERE YEAR BETWEEN 2020 AND 2025
           GROUP BY geoid
          ),
          pop AS (
             SELECT geoid,
                    max(pop_estimate) FILTER (
                        WHERE YEAR = 2025
                    ) AS pop_2025,
                    max(pop_estimate) FILTER (
                        WHERE YEAR = 2020
                    ) AS pop_2020
               FROM tn_census_county_pop_est
              WHERE YEAR IN (2020, 2025)
           GROUP BY geoid
          )
   SELECT c.geoid,
          c.name AS county,
          p.units AS units,
          p.units_5plus AS units_5plus,
          round(100.0 * p.units_5plus / nullif(p.units, 0), 1) AS share_5plus,
          round(1000.0 * p.units / nullif(pp.pop_2025, 0), 1) AS per_1000,
          pp.pop_2020,
          pp.pop_2025,
          round(100.0 * (pp.pop_2025 - pp.pop_2020) / nullif(pp.pop_2020, 0), 1) AS pop_chg_pct
     FROM tn_census_counties c
LEFT JOIN perm p ON p.geoid = c.geoid
LEFT JOIN pop pp ON pp.geoid = c.geoid
 ORDER BY p.units DESC NULLS LAST

geoid	county	units	units_5plus	share_5plus	per_1000	pop_2020	pop_2025	pop_chg_pct
47037	Davidson County	68656	48038	70.0	92.0	716153	745904	4.2
47093	Knox County	22126	8570	38.7	43.3	480472	511453	6.4
47149	Rutherford County	20068	2217	11.0	51.9	343285	386352	12.5
47125	Montgomery County	19737	7208	36.5	79.0	221286	249935	12.9
47065	Hamilton County	13572	3146	23.2	34.7	367886	390833	6.2
47189	Wilson County	12852	1087	8.5	73.4	148654	175033	17.7
47187	Williamson County	12565	2692	21.4	46.2	249614	272061	9.0
47165	Sumner County	12359	2786	22.5	57.3	197416	215538	9.2
47157	Shelby County	11062	5089	46.0	12.2	929720	910226	-2.1
47119	Maury County	10793	1216	11.3	91.4	101812	118131	16.0
47155	Sevier County	7319	1436	19.6	72.2	98848	101342	2.5
47147	Robertson County	5239	244	4.7	65.3	72958	80175	9.9
47179	Washington County	5036	1251	24.8	35.7	133211	141199	6.0
47009	Blount County	5011	423	8.4	34.8	135666	143820	6.0
47105	Loudon County	4459	517	11.6	69.9	55144	63764	15.6
47011	Bradley County	3931	62	1.6	34.0	108832	115465	6.1
47141	Putnam County	3719	389	10.5	42.9	80101	86612	8.1
47163	Sullivan County	3200	490	15.3	19.5	158238	163759	3.5
47043	Dickson County	3054	430	14.1	52.1	54452	58662	7.7
47003	Bedford County	2574	6	0.2	46.6	50381	55273	9.7
47001	Anderson County	2513	904	36.0	30.6	77347	82066	6.1
47047	Fayette County	2374	0	0.0	52.7	41868	45071	7.7
47051	Franklin County	2243	20	0.9	49.2	42842	45579	6.4
47089	Jefferson County	2180	32	1.5	36.3	54897	60024	9.3
47063	Hamblen County	2018	188	9.3	29.3	64553	68843	6.6

25 out of 95 are listed here.

data/turn-1-query-3.csv

Query 4 — Check whether zero-permit counties have zero or missing rows in all years

   SELECT name,
          count(*) AS years_present,
          sum(units_total) AS units_all_years,
          min(units_total) AS min_yr,
          max(units_total) AS max_yr
     FROM tn_bps_county_permits
    WHERE name ILIKE ANY (
          ARRAY['Jackson%', 'Morgan%', 'Bledsoe%', 'Pickett%', 'Hancock%', 'Wayne%']
          )
 GROUP BY name
 ORDER BY name

name	years_present	units_all_years	max_yr
Bledsoe County	11	0	0
Hancock County	36	140	49
Jackson County	25	12	8
Morgan County	36	43	19
Wayne County	36	328	80

data/turn-1-query-4.csv

Map Layer Queries

Counties by new homes per 1,000 residents — colored by "Rate band": Under 10 (#fee5d9), 10 to 20 (#fcae91), 20 to 35 (#fb6a4a), 35 to 50 (#de2d26), 50 to 70 (#a50f15), 70 and over (#67000d), No permit data (#cccccc)

     WITH perm AS (
             SELECT geoid,
                    sum(units_total) AS units,
                    sum(units_5plus) AS units_5plus
               FROM tn_bps_county_permits
              WHERE YEAR BETWEEN 2020 AND 2025
           GROUP BY geoid
          ),
          pop AS (
             SELECT geoid,
                    max(pop_estimate) FILTER (
                        WHERE YEAR = 2025
                    ) AS pop_2025,
                    max(pop_estimate) FILTER (
                        WHERE YEAR = 2020
                    ) AS pop_2020
               FROM tn_census_county_pop_est
              WHERE YEAR IN (2020, 2025)
           GROUP BY geoid
          ),
          x AS (
             SELECT c.name,
                    c.geom,
                    p.units,
                    p.units_5plus,
                    pp.pop_2020,
                    pp.pop_2025,
                    1000.0 * p.units / nullif(pp.pop_2025, 0) AS per_1000
               FROM tn_census_counties c
          LEFT JOIN perm p ON p.geoid = c.geoid
          LEFT JOIN pop pp ON pp.geoid = c.geoid
          )
   SELECT geom,
          name AS "County",
          units AS "New housing units 2020-2025",
          units_5plus AS "Units in 5+ unit buildings",
          round(per_1000::numeric, 1) AS "Units per 1,000 residents",
          pop_2025 AS "Population 2025",
          CASE
                    WHEN per_1000 IS NULL THEN 'No permit data'
                    WHEN per_1000 < 10 THEN 'Under 10'
                    WHEN per_1000 < 20 THEN '10 to 20'
                    WHEN per_1000 < 35 THEN '20 to 35'
                    WHEN per_1000 < 50 THEN '35 to 50'
                    WHEN per_1000 < 70 THEN '50 to 70'
                    ELSE '70 and over'
          END AS "Rate band"
     FROM x

Picture: maps/turn-1-permits-per-thousand-counties.png

Used Data Sets

tn_bps_county_permits — last synced 2026-10-14 · 3,288 rows
tn_census_counties — last synced 2026-09-27 · 95 rows
tn_census_county_pop_est — last synced 2026-10-15 · 5,320 rows

data/turn-1-query-1.csv

↑ Contents

year	counties	units	units_5plus
2019	94	41361	11262
2020	94	49719	15612
2021	94	57484	19690
2022	94	52637	17973
2023	94	47463	15036
2024	94	44863	11183
2025	94	43374	10427

7 rows.

data/turn-1-query-2.csv

↑ Contents

year	series	counties	pop
2019	intercensal	95	6862615
2020	postcensal	95	6927736
2021	postcensal	95	6966687
2022	postcensal	95	7063325
2023	postcensal	95	7153029
2024	postcensal	95	7251291
2025	postcensal	95	7315076

7 rows.

data/turn-1-query-3.csv

↑ Contents

geoid	county	units	units_5plus	share_5plus	per_1000	pop_2020	pop_2025	pop_chg_pct
47037	Davidson County	68656	48038	70.0	92.0	716153	745904	4.2
47093	Knox County	22126	8570	38.7	43.3	480472	511453	6.4
47149	Rutherford County	20068	2217	11.0	51.9	343285	386352	12.5
47125	Montgomery County	19737	7208	36.5	79.0	221286	249935	12.9
47065	Hamilton County	13572	3146	23.2	34.7	367886	390833	6.2
47189	Wilson County	12852	1087	8.5	73.4	148654	175033	17.7
47187	Williamson County	12565	2692	21.4	46.2	249614	272061	9.0
47165	Sumner County	12359	2786	22.5	57.3	197416	215538	9.2
47157	Shelby County	11062	5089	46.0	12.2	929720	910226	-2.1
47119	Maury County	10793	1216	11.3	91.4	101812	118131	16.0
47155	Sevier County	7319	1436	19.6	72.2	98848	101342	2.5
47147	Robertson County	5239	244	4.7	65.3	72958	80175	9.9
47179	Washington County	5036	1251	24.8	35.7	133211	141199	6.0
47009	Blount County	5011	423	8.4	34.8	135666	143820	6.0
47105	Loudon County	4459	517	11.6	69.9	55144	63764	15.6
47011	Bradley County	3931	62	1.6	34.0	108832	115465	6.1
47141	Putnam County	3719	389	10.5	42.9	80101	86612	8.1
47163	Sullivan County	3200	490	15.3	19.5	158238	163759	3.5
47043	Dickson County	3054	430	14.1	52.1	54452	58662	7.7
47003	Bedford County	2574	6	0.2	46.6	50381	55273	9.7
47001	Anderson County	2513	904	36.0	30.6	77347	82066	6.1
47047	Fayette County	2374	0	0.0	52.7	41868	45071	7.7
47051	Franklin County	2243	20	0.9	49.2	42842	45579	6.4
47089	Jefferson County	2180	32	1.5	36.3	54897	60024	9.3
47063	Hamblen County	2018	188	9.3	29.3	64553	68843	6.6
47035	Cumberland County	2015	0	0.0	30.4	61381	66300	8.0
47031	Coffee County	1974	204	10.3	31.6	58132	62419	7.4
47021	Cheatham County	1810	217	12.0	42.3	41088	42778	4.1
47117	Marshall County	1770	180	10.2	46.5	34467	38071	10.5
47059	Greene County	1585	72	4.5	21.5	70339	73831	5.0
47177	Warren County	1572	242	15.4	36.0	41057	43717	6.5
47113	Madison County	1512	0	0.0	15.0	98832	100790	2.0
47115	Marion County	1294	0	0.0	43.4	28874	29804	3.2
47013	Campbell County	1257	14	1.1	31.2	39310	40290	2.5
47139	Polk County	1234	0	0.0	66.4	17558	18592	5.9
47167	Tipton County	1231	71	5.8	19.8	61050	62287	2.0
47145	Roane County	1198	0	0.0	20.9	53666	57395	6.9
47185	White County	1116	0	0.0	37.7	27441	29612	7.9
47123	Monroe County	1084	0	0.0	21.8	46399	49730	7.2
47019	Carter County	1057	0	0.0	18.4	56391	57361	1.7
47053	Gibson County	1024	0	0.0	19.8	50443	51779	2.6
47111	Macon County	972	160	16.5	35.1	25260	27663	9.5
47073	Hawkins County	952	0	0.0	16.0	56715	59559	5.0
47143	Rhea County	860	46	5.3	24.7	33302	34844	4.6
47041	DeKalb County	839	0	0.0	38.4	20186	21873	8.4
47159	Smith County	788	55	7.0	37.6	19963	20981	5.1
47055	Giles County	774	0	0.0	24.6	30346	31433	3.6
47173	Union County	729	0	0.0	34.0	19847	21450	8.1
47081	Hickman County	697	0	0.0	26.6	24972	26219	5.0
47169	Trousdale County	658	0	0.0	52.1	11646	12623	8.4
47121	Meigs County	590	0	0.0	41.6	12808	14186	10.8
47025	Claiborne County	529	6	1.1	15.9	32075	33229	3.6
47103	Lincoln County	504	0	0.0	13.7	35332	36853	4.3
47107	McMinn County	454	6	1.3	7.9	53347	57404	7.6
47057	Grainger County	418	0	0.0	16.2	23572	25739	9.2
47015	Cannon County	408	0	0.0	26.7	14564	15296	5.0
47045	Dyer County	399	6	1.5	11.0	36710	36320	-1.1
47183	Weakley County	395	0	0.0	11.9	32908	33261	1.1
47069	Hardeman County	245	0	0.0	9.7	25435	25274	-0.6
47085	Humphreys County	192	0	0.0	9.8	18998	19646	3.4
47075	Haywood County	188	72	38.3	11.0	17827	17042	-4.4
47033	Crockett County	176	0	0.0	12.6	13907	14006	0.7
47127	Moore County	176	0	0.0	25.4	6472	6920	6.9
47101	Lewis County	174	56	32.2	12.9	12609	13487	7.0
47131	Obion County	164	0	0.0	5.5	30779	30067	-2.3
47097	Lauderdale County	158	0	0.0	6.4	25115	24617	-2.0
47027	Clay County	151	0	0.0	19.3	7588	7821	3.1
47071	Hardin County	149	0	0.0	5.3	26948	27983	3.8
47099	Lawrence County	133	0	0.0	2.8	44185	46914	6.2
47077	Henderson County	133	0	0.0	4.7	27833	28518	2.5
47079	Henry County	119	0	0.0	3.6	32149	32896	2.3
47171	Unicoi County	118	0	0.0	6.6	17873	17856	-0.1
47109	McNairy County	117	66	56.4	4.5	25868	26236	1.4
47023	Chester County	105	0	0.0	5.8	17379	17994	3.5
47153	Sequatchie County	98	0	0.0	5.5	15848	17861	12.7
47133	Overton County	87	0	0.0	3.7	22590	23787	5.3
47135	Perry County	68	0	0.0	7.5	8383	9126	8.9
47061	Grundy County	66	0	0.0	4.7	13541	14116	4.2
47017	Carroll County	66	0	0.0	2.3	28427	29200	2.7
47161	Stewart County	57	7	12.3	3.9	13708	14439	5.3
47005	Benton County	45	0	0.0	2.8	15847	16183	2.1
47151	Scott County	35	0	0.0	1.5	21880	22671	3.6
47039	Decatur County	32	0	0.0	2.7	11429	11820	3.4
47029	Cocke County	31	0	0.0	0.8	36043	37889	5.1
47175	Van Buren County	30	0	0.0	4.4	6174	6874	11.3
47091	Johnson County	26	0	0.0	1.4	17985	18718	4.1
47095	Lake County	16	0	0.0	2.6	6988	6249	-10.6
47049	Fentress County	15	0	0.0	0.7	18533	20322	9.7
47083	Houston County	5	0	0.0	0.6	8295	8479	2.2
47067	Hancock County	4	0	0.0	0.6	6628	7075	6.7
47181	Wayne County	2	0	0.0	0.1	16220	16416	1.2
47087	Jackson County	0	0		0.0	11637	12466	7.1
47129	Morgan County	0	0		0.0	21051	22160	5.3
47007	Bledsoe County	0	0		0.0	14945	15920	6.5
47137	Pickett County					5002	5219	4.3

95 rows.

data/turn-1-query-4.csv

↑ Contents

name	years_present	units_all_years	max_yr
Bledsoe County	11	0	0
Hancock County	36	140	49
Jackson County	25	12	8
Morgan County	36	43	19
Wayne County	36	328	80

5 rows.

County	Other housing units	Units in 5+ unit buildings
Davidson County	20618	48038
Knox County	13556	8570
Rutherford County	17851	2217
Montgomery County	12529	7208
Hamilton County	10426	3146
Wilson County	11765	1087
Williamson County	9873	2692
Sumner County	9573	2786
Shelby County	5973	5089
Maury County	9577	1216
Sevier County	5883	1436
Robertson County	4995	244
Washington County	3785	1251
Blount County	4588	423
Loudon County	3942	517

15 rows.

maps/turn-1-permits-per-thousand-counties.png

↑ Contents

provenance/tn_bps_county_permits.md

↑ Contents

Provenance: `tn_bps_county_permits`

This file describes how the rows in PostgreSQL table tn_bps_county_permits were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_bps_county_permits
Family: BPS
Display name: Building Permits by County
Source URL: https://www2.census.gov/econ/bps/County/ (co<year>a.txt, 1990 on)
Geometry (source / stored): none / none
Update cycle: Yearly (each May)

Pipeline

The Building Permits Survey publishes one national county file per year, the annual summary (a), comma-delimited text with a two-row header. Every year from 1990 is loaded; the newest year is the one before the current, once the Bureau has published it. Each year's file is downloaded whole and kept; the sync keeps Tennessee's rows (FIPS State 47) and checks each file's survey date names its year (2024, or 9099 in the 1990s files).

A county listed twice in one year (the 2014 and 2015 files repeat four Alaska boroughs and one Maryland county under a second name with the same estimates) keeps the row with more reported units; two rows with different estimates fail the sync. The monthly and year-to-date files are not loaded.

Changed from the source: cut to Tennessee; reshaped to one row per county per year; the three totals added; the region, division and survey-date columns dropped (doc/BPS-SYNC.md).

No licence terms: a work of the U.S. Government, credited to the U.S. Census Bureau (doc/DATA-LICENSES.md).

Field → column mapping

Source field	Column	Type	Description
FIPS State, FIPS County	`geoid`	text	Two digits and three, joined
County Name	`name`	text	Trailing spaces trimmed
Survey Date	`year`	text → integer	Checked against the file's year
1-unit Bldgs, Units, Value	`bldgs_1`, `units_1`, `value_1`	integer	Estimates with imputation
2-units Bldgs, Units, Value	`bldgs_2`, `units_2`, `value_2`	integer
3-4 units Bldgs, Units, Value	`bldgs_3_4`, `units_3_4`, `value_3_4`	integer
5+ units Bldgs, Units, Value	`bldgs_5plus`, `units_5plus`, `value_5plus`	integer
1-unit rep … 5+ units rep	`rep_bldgs_1` … `rep_value_5plus`	integer	Reported only
(computed)	`bldgs_total`, `units_total`, `value_total`		The four estimate sizes added
Region Code, Division Code	(dropped)

provenance/tn_census_counties.md

↑ Contents

Provenance: `tn_census_counties`

This file describes how the rows in PostgreSQL table tn_census_counties were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_census_counties
Family: Census
Display name: Census Counties (Tennessee)
Source URL: https://tigerweb.geo.census.gov/arcgis/rest/services/TIGERweb/tigerWMS_Current/MapServer/82
Also from: https://www2.census.gov/programs-surveys/cfs/technical-documentation/geographies/list2022.xlsx
Geometry (source / stored): polygon / geometry(MultiPolygon, 4326)
Update cycle: Yearly

Pipeline

Two Census Bureau sources, joined on the county's 5-digit FIPS code:

Boundaries: TIGERweb tigerWMS_Current layer 82 ("Counties"), where=STATE='47', GeoJSON, outSR=4326, keyset-paged on GEOID.
CFS areas: sheet CFSAreas of the 2022 Commodity Flow Survey county list, the Tennessee rows (ST = 47). Only the 2022 columns are kept.

The two must name the same counties, or the sync fails. FAF's tn_faf_county_xwalk is built from this table: each county's cfs_geoid is the CFS22_ID of one FAF6 zone.

Field → column mapping

Source field	Column	Type	Description
TIGER `GEOID`	`geoid`	varchar(5)	state + county FIPS
TIGER `GEOID`, last 3	`county_fips`	varchar(3)	county FIPS
TIGER `NAME`	`name`	varchar(60)	e.g. `Shelby County`
CFS `CFS22_AREA`	`cfs_area`	varchar(5)	CSA/MSA code, or `99999`
CFS `CFS22_TYPE`	`cfs_area_type`	varchar(1)	C, M or R
CFS `CFS22_NAME`, whitespace collapsed	`cfs_area_name`	varchar(120)	the workbook pads some names with doubled and trailing spaces
CFS `CFS22_GEOID`	`cfs_geoid`	varchar(19)	e.g. `E330000US4736800000`
TIGER `AREALAND`	`aland_m2`	bigint	square meters
TIGER `AREAWATER`	`awater_m2`	bigint	square meters
TIGER `INTPTLAT`	`intptlat`	double precision	internal point
TIGER `INTPTLON`	`intptlon`	double precision	internal point
geometry	`geom`	geometry(MultiPolygon, 4326)	`ST_Multi(ST_GeomFromGeoJSON)`

Geometry

SRID 4326 (WGS84). GIST index on geom.

Change detection

The Census sync's check compares the layer's vintage ("January 1, 2026 vintage") and Tennessee's row count, and the county list's Last-Modified and length. A change to either marks Census stale, and the next Census sync rebuilds this table, then FAF's crosswalk.

Attribution

US Census Bureau. TIGER products are free to use with acknowledgement of the U.S. Census Bureau as the source; the CFS county list states no terms.

provenance/tn_census_county_pop_est.md

↑ Contents

Provenance: `tn_census_county_pop_est`

This file describes how the rows in PostgreSQL table tn_census_county_pop_est were obtained from an external source: where they were fetched and how fields were renamed and typed. Field meanings are in the mapping table below.

Identity

Table: tn_census_county_pop_est
Family: Census
Display name: Annual Population Estimates by County
Source URL: https://www2.census.gov/programs-surveys/popest/datasets/2020-2025/counties/totals/co-est2025-alldata.csv (vintage 2025; each vintage <V> is 2020-<V>/counties/totals/co-est<V>-alldata.csv), for 2020 on
History (2000–2019): under the same datasets/ directory, 2000-2010/intercensal/county/co-est00int-tot.csv and 2010-2020/intercensal/county/asrh/cc-est2020int-agesex-all.csv (the revised population), 2010/2010-eval-estimates/co-est2010-alldata.csv and 2010-2020/counties/totals/co-est2020-alldata.csv (the components of change of the releases they revised)
History (1970–1999): under https://www2.census.gov/programs-surveys/popest/tables/, 1900-1980/counties/asrh/co-asr-7079.csv, 1980-1990/counties/asrh/pe-02-<year>.csv and 1990-2000/intercensal/st-co/stch-icen<year>.txt (the county age, sex and race estimates), and 1900-1980/counties/totals/e7079co.txt and 1980-1990/counties/totals/e8089co.txt (the decades' county totals tables, for their census counts)
Geometry (source / stored): none / none
Update cycle: Yearly (each March)

Pipeline

The Population Estimates Program's national county file, CSV, one row per county with a column per year for each figure. The sync keeps Tennessee's county rows (SUMLEV 050, STATE 47), dropping the state's own total (040), and turns each into one row per year, the years read off the file's POPESTIMATE<year> columns. Every county the file names must be one the county layer of TIGERweb draws, or the sync fails. A file that is not valid UTF-8 is read as Latin-1. These rows are series postcensal.

The years before 2020 are series intercensal, from four further national files that never change:

Population, 2000–2009: co-est00int-tot.csv, one row per county, codes written without leading zeros (SUMLEV "50", STATE "1"), which the sync pads. ESTIMATESBASE2000 and POPESTIMATE2000–2009; its POPESTIMATE2010 and CENSUS2010POP are not loaded. vintage 2010.
Population, 2010–2019: the Bureau's table of revised county totals for the decade is a spreadsheet that names counties without codes, so the sync reads the same figures from cc-est2020int-agesex-all.csv, one row per county and YEAR code, its POPESTIMATE the whole population: YEAR 1 is the April 1, 2010 base, 2–11 July 1, 2010–2019, and 12 (the April 1, 2020 census) is not loaded. vintage 2020. 2010 is taken from this file, not the 2000s one, which has its own figure for it.
Components: the original releases' files, as published, matched by county code: co-est2010-alldata.csv for 2000–2010 (2000 is April to June) and co-est2020-alldata.csv for 2011–2019. Their natural change column is NATURALINC<year>. A county with no row in the 2000s release (one coded anew in the 2010s) has empty 2010 components; any other missing county fails the sync.
pop_change is computed, not read: pop_estimate less the row before's (2010's less the 2000s file's 2009, 2000's less 1999's, or ESTIMATESBASE2000 for a county with no 1999 row). The releases' NPOPCHG_<year> describes their own population, not the revised one, and is not loaded.
1970–1999: each county's July 1 population is the sum of its age, sex and race estimates, which tn_census_county_pop_char loads from the same files (its provenance has their layouts): vintage 1980, 1990 and 2000 for the three decades. The Bureau's county totals tables for the 1970s and 1980s, e7079co.txt and e8089co.txt, are fixed-width text in blocks of five years, a long name wrapping onto a line of its own; only their first column, the decade's April 1 census, is loaded, into estimates_base on the 1970 and 1980 rows. Their July figures are not loaded: the 1970s table rounds counties to hundreds, and both are on the geography of their day as the age files are, but not always the same day's. No component of change is loaded before 2000. pop_change is computed as for the later decades, 1970's from the April 1970 count, and the 2000 row's is from July 1999.
A history row's county need not be one TIGER draws today (Connecticut's eight old counties, the 1970s' Alaskan census divisions and Virginia's Nansemond, and a handful elsewhere); the sync logs them.

Field → column mapping

Source field	Column	Type	Description
`STATE` + `COUNTY`	`geoid`	varchar(5)	county FIPS
the `<year>` suffix	`year`	smallint
the newest `<year>`	`vintage`	smallint	1980, 1990, 2000, 2010 or 2020 on history rows
	`series`	varchar(12)	`postcensal`, or `intercensal` on history rows
`POPESTIMATE<year>`	`pop_estimate`	integer
`ESTIMATESBASE2020`	`estimates_base`	integer	2020 row only (`ESTIMATESBASE2000`, `YEAR` 1 on the 2000 and 2010 rows; the decade tables' census column on the 1970 and 1980 rows)
`NPOPCHG<year>`	`pop_change`	integer	computed on history rows
`BIRTHS<year>`	`births`	integer
`DEATHS<year>`	`deaths`	integer
`NATURALCHG<year>`	`natural_change`	integer	`NATURALINC<year>` on history rows
`INTERNATIONALMIG<year>`	`international_mig`	integer
`DOMESTICMIG<year>`	`domestic_mig`	integer
`NETMIG<year>`	`net_mig`	integer
`RESIDUAL<year>`	`residual`	integer
`GQESTIMATES<year>`	`gq_estimate`	integer

The file's per-1,000 rate columns (R…) and GQESTIMATESBASE2020 are not loaded.

Geometry

No geometry column.

Change detection

The Census sync's check asks for the next vintage's file each time and moves to it once it is published; otherwise it compares the current file's Last-Modified and length, and each history file's. Any of them marks this table stale, and the next Census sync rebuilds it whole, every year from 2020 replaced by the new release.

Attribution

US Census Bureau, Population Estimates Program.

New Housing Units per 1,000 Residents, Tennessee Counties 2020-2025

Layers

Data sets used

Ask your own question about Tennessee

Transcript

State Planner chat · https://stateplanner.com

Prompt

Response

Chart Queries

Top 15 counties by new housing units, 2020-2025, split by building size

Exploratory Queries

Query 1 — Check which permit years exist from 2019 on and totals per year

Query 2 — Check population estimate years available from 2019 on

Query 3 — Per-county permits 2020-2025, 5+ share, population change and permits per 1,000

Query 4 — Check whether zero-permit counties have zero or missing rows in all years

Map Layer Queries

Counties by new homes per 1,000 residents — colored by "Rate band": Under 10 (#fee5d9), 10 to 20 (#fcae91), 20 to 35 (#fb6a4a), 35 to 50 (#de2d26), 50 to 70 (#a50f15), 70 and over (#67000d), No permit data (#cccccc)

Used Data Sets

Provenance: tn_bps_county_permits

Identity

Pipeline

Field → column mapping

Provenance: tn_census_counties

Identity

Pipeline

Field → column mapping

Geometry

Change detection

Attribution

Provenance: tn_census_county_pop_est

Identity

Pipeline

Field → column mapping

Geometry

Change detection

Attribution

Provenance: `tn_bps_county_permits`

Provenance: `tn_census_counties`

Provenance: `tn_census_county_pop_est`