US Census Geographic Boundaries

Cloud-optimized formats for Draft CalEnviroScreen 5.0 (released January 2026) is a cumulative environmental pollution and health vulnerability screening tool developed by California's Office of Environmental Health Hazard Assessment (OEHHA).

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Visibility: Public
Owner: Carl Boettiger
Created: 16 Jun 2026
Last Updated: 16 Jun 2026

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census-2024

README-state.md

state-README.md

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US Census Geographic Boundaries

Product Details

Visibility: Public
Owner: Carl Boettiger
Created: 16 Jun 2026
Last Updated: 16 Jun 2026

Product Contents

root

census-2024

README-state.md

state-README.md

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Last Modified: 16 Jun 2026
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Name: state-README.md
Size: 4.54 KB
Content Type: text/markdown; charset=utf-8
Last Modified: 16 Jun 2026
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US Census 2024 State Boundaries

2024 state and territory boundaries from the US Census Bureau's TIGER/Line shapefiles, processed into cloud-native formats with H3 hexagonal spatial indexing.

Dataset Overview

Source: US Census Bureau TIGER/Line 2024
Geography Level: State/Territory
Features: 56 (50 states + DC + 5 territories)
H3 Resolution: 10 (~0.015 km² per hex)
Parent Resolutions: 9, 8, 0
Last Updated: February 2026

Available Formats

GeoParquet

s3://public-census/census-2024/state.parquet

Format: GeoParquet with ZSTD compression
CRS: EPSG:4326 (WGS84)
Row Groups: 100,000 features
Geometry Type: MultiPolygon
Use Case: Analytical queries with DuckDB, Polars, GeoPandas

PMTiles

s3://public-census/census-2024/state.pmtiles

Format: PMTiles v3
Use Case: Web map visualization with MapLibre GL JS, Leaflet

H3 Hex Index

s3://public-census/census-2024/state/hex/h0={cell}/

Format: Partitioned Parquet by H3 resolution 0 cells
Columns: h3_cell (resolution 10), feature_id, plus parent resolutions
Use Case: Fast spatial joins, area-weighted aggregation

Attributes

Key attributes from TIGER/Line shapefiles:

STATEFP: State FIPS code (2 digits)
STATENS: State GNIS identifier
GEOID: Complete geographic identifier (= STATEFP)
STUSPS: 2-letter state postal abbreviation
NAME: State/territory name
LSAD: Legal/Statistical Area Description
ALAND: Land area (square meters)
AWATER: Water area (square meters)

Usage Examples

DuckDB Query

Python (GeoPandas)

Web Mapping (MapLibre GL JS)

H3 Spatial Indexing

Each state boundary is indexed into H3 hexagons at resolution 10 (~0.015 km² per hex):

Alaska: ~113M hexes (largest)
Texas: ~70M hexes
Rhode Island: ~300K hexes (smallest state)

The hex index enables:

Fast point-in-polygon queries (join point data with hex, then hex with features)
Area-weighted aggregation (count events per state using hex coverage)
Multi-resolution analysis (parent resolutions 9, 8, 0 included)

Processing Details

Source URL: https://www2.census.gov/geo/tiger/TIGER2024/STATE/tl_2024_us_state.zip
Processing Date: February 2026
Pipeline: convert (17s) → hex (56 completions, 6m47s) → pmtiles (4m33s) → repartition (65s)
Total Features: 56 states/territories
Total Processing Time: ~12 minutes

Citation

U.S. Census Bureau (2024). TIGER/Line Shapefiles: State and Equivalent. Retrieved from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html

License

Public domain. No restrictions on use.

Census 2024 Counties - 3,235 county boundaries
Census 2024 Census Tracts - ~85,000 tract boundaries
Census 2024 Congressional Districts - 119th Congress districts

Access

Public HTTP Access:

S3 Access (requires credentials):

US Census 2024 State Boundaries

2024 state and territory boundaries from the US Census Bureau's TIGER/Line shapefiles, processed into cloud-native formats with H3 hexagonal spatial indexing.

Dataset Overview

Source: US Census Bureau TIGER/Line 2024
Geography Level: State/Territory
Features: 56 (50 states + DC + 5 territories)
H3 Resolution: 10 (~0.015 km² per hex)
Parent Resolutions: 9, 8, 0
Last Updated: February 2026

Available Formats

GeoParquet

s3://public-census/census-2024/state.parquet

Format: GeoParquet with ZSTD compression
CRS: EPSG:4326 (WGS84)
Row Groups: 100,000 features
Geometry Type: MultiPolygon
Use Case: Analytical queries with DuckDB, Polars, GeoPandas

PMTiles

s3://public-census/census-2024/state.pmtiles

Format: PMTiles v3
Use Case: Web map visualization with MapLibre GL JS, Leaflet

H3 Hex Index

s3://public-census/census-2024/state/hex/h0={cell}/

Format: Partitioned Parquet by H3 resolution 0 cells
Columns: h3_cell (resolution 10), feature_id, plus parent resolutions
Use Case: Fast spatial joins, area-weighted aggregation

Attributes

Key attributes from TIGER/Line shapefiles:

STATEFP: State FIPS code (2 digits)
STATENS: State GNIS identifier
GEOID: Complete geographic identifier (= STATEFP)
STUSPS: 2-letter state postal abbreviation
NAME: State/territory name
LSAD: Legal/Statistical Area Description
ALAND: Land area (square meters)
AWATER: Water area (square meters)

Usage Examples

DuckDB Query

Python (GeoPandas)

Web Mapping (MapLibre GL JS)

H3 Spatial Indexing

Each state boundary is indexed into H3 hexagons at resolution 10 (~0.015 km² per hex):

Alaska: ~113M hexes (largest)
Texas: ~70M hexes
Rhode Island: ~300K hexes (smallest state)

The hex index enables:

Fast point-in-polygon queries (join point data with hex, then hex with features)
Area-weighted aggregation (count events per state using hex coverage)
Multi-resolution analysis (parent resolutions 9, 8, 0 included)

Processing Details

Source URL: https://www2.census.gov/geo/tiger/TIGER2024/STATE/tl_2024_us_state.zip
Processing Date: February 2026
Pipeline: convert (17s) → hex (56 completions, 6m47s) → pmtiles (4m33s) → repartition (65s)
Total Features: 56 states/territories
Total Processing Time: ~12 minutes

Citation

U.S. Census Bureau (2024). TIGER/Line Shapefiles: State and Equivalent. Retrieved from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html

License

Public domain. No restrictions on use.

Census 2024 Counties - 3,235 county boundaries
Census 2024 Census Tracts - ~85,000 tract boundaries
Census 2024 Congressional Districts - 119th Congress districts

Access

Public HTTP Access:

S3 Access (requires credentials):

1https://s3-west.nrp-nautilus.io/public-census/census-2024/state.parquet
2https://s3-west.nrp-nautilus.io/public-census/census-2024/state.pmtiles

1s3://public-census/census-2024/state.parquet
2s3://public-census/census-2024/state.pmtiles
3s3://public-census/census-2024/state/hex/h0=*/

1https://s3-west.nrp-nautilus.io/public-census/census-2024/state.parquet
2https://s3-west.nrp-nautilus.io/public-census/census-2024/state.pmtiles

1s3://public-census/census-2024/state.parquet
2s3://public-census/census-2024/state.pmtiles
3s3://public-census/census-2024/state/hex/h0=*/

1-- Load state boundaries
2LOAD spatial;
3CREATE TABLE states AS 
4  SELECT * FROM read_parquet('s3://public-census/census-2024/state.parquet');
5
6-- Query by state name
7SELECT NAME, STUSPS, ALAND/1000000 as land_sq_km
8FROM states
9WHERE NAME = 'California';
10
11-- Join with H3 hex index for spatial aggregation
12CREATE TABLE state_hexes AS
13  SELECT * FROM read_parquet('s3://public-census/census-2024/state/hex/h0=*/');
14  
15-- Count H3 cells per state
16SELECT s.NAME, COUNT(h.h3_cell) as hex_count
17FROM state_hexes h
18JOIN states s ON h.feature_id = s._cng_fid
19GROUP BY s.NAME
20ORDER BY hex_count DESC;

1-- Load state boundaries
2LOAD spatial;
3CREATE TABLE states AS 
4  SELECT * FROM read_parquet('s3://public-census/census-2024/state.parquet');
5
6-- Query by state name
7SELECT NAME, STUSPS, ALAND/1000000 as land_sq_km
8FROM states
9WHERE NAME = 'California';
10
11-- Join with H3 hex index for spatial aggregation
12CREATE TABLE state_hexes AS
13  SELECT * FROM read_parquet('s3://public-census/census-2024/state/hex/h0=*/');
14  
15-- Count H3 cells per state
16SELECT s.NAME, COUNT(h.h3_cell) as hex_count
17FROM state_hexes h
18JOIN states s ON h.feature_id = s._cng_fid
19GROUP BY s.NAME
20ORDER BY hex_count DESC;

1import geopandas as gpd
2
3# Read state boundaries
4states = gpd.read_parquet('s3://public-census/census-2024/state.parquet')
5
6# Filter West Coast states
7west_coast = states[states['STUSPS'].isin(['CA', 'OR', 'WA'])]
8
9# Calculate total land area
10print(f"West Coast land area: {west_coast['ALAND'].sum() / 1e6:.0f} sq km")

1import geopandas as gpd
2
3# Read state boundaries
4states = gpd.read_parquet('s3://public-census/census-2024/state.parquet')
5
6# Filter West Coast states
7west_coast = states[states['STUSPS'].isin(['CA', 'OR', 'WA'])]
8
9# Calculate total land area
10print(f"West Coast land area: {west_coast['ALAND'].sum() / 1e6:.0f} sq km")

1map.addSource('states', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-census/census-2024/state.pmtiles'
4});
5
6map.addLayer({
7  id: 'states-fill',
8  type: 'fill',
9  source: 'states',
10  'source-layer': 'state',
11  paint: {
12    'fill-color': '#088',
13    'fill-opacity': 0.3,
14    'fill-outline-color': '#000'
15  }
16});

1map.addSource('states', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-census/census-2024/state.pmtiles'
4});
5
6map.addLayer({
7  id: 'states-fill',
8  type: 'fill',
9  source: 'states',
10  'source-layer': 'state',
11  paint: {
12    'fill-color': '#088',
13    'fill-opacity': 0.3,
14    'fill-outline-color': '#000'
15  }
16});

US Census Geographic Boundaries

US Census Geographic Boundaries

US Census 2024 State Boundaries

Dataset Overview

Available Formats

GeoParquet

PMTiles

H3 Hex Index

Attributes

Usage Examples

DuckDB Query

Python (GeoPandas)

Web Mapping (MapLibre GL JS)

H3 Spatial Indexing

Processing Details

Citation

License

Related Datasets

Access

US Census 2024 State Boundaries

Dataset Overview

Available Formats

GeoParquet

PMTiles

H3 Hex Index

Attributes

Usage Examples

DuckDB Query

Python (GeoPandas)

Web Mapping (MapLibre GL JS)

H3 Spatial Indexing

Processing Details

Citation

License

Related Datasets

Access