Wildfire Boundary Polygons from USGS and CalFire in cloud native formats

Cloud Native serializations of publicly available fire data from USGS and Calfire. Calfire data includes controlled burn treatments. Data through 2022

pmtiles

fire

parquet

united states

Contents

root

10.98 KB

73.66 KB

Details

Visibility: Public
Owner: Carl Boettiger
Created: 19 Mar 2024
Last Updated: 15 Aug 2025

Analytics

28 days

Downloads

1,513

Data served

53.4 GB

Countries

28-day downloads

12 Jul 2026

8 Aug 2026

Analytics

README

Fire Datasets

This bucket contains CAL FIRE and USGS fire perimeter datasets:

CAL FIRE Wildfire Perimeters — California wildfire perimeters (2025 release calfire-2025/firep, prior calfire-2024/firep)
CAL FIRE Prescribed Burns — California prescribed burn treatments (2025 release calfire-2025/rxburn, prior calfire-2024/rxburn)
USGS Wildland Fire Combined Dataset — National wildfire perimeters 1878–2021 (usgs-fires-2021/combined)

All datasets are polygon geometries processed into GeoParquet, PMTiles, and H3 hex Parquet (resolution 10).

The 2025 CAL FIRE release (FRAP fire251gdb) is the current dataset for California fires and prescribed burns; the 2024 release is retained as a prior version.

CAL FIRE Wildfire Perimeters 2025 (`calfire-2025/firep`) — current

Source: CAL FIRE FRAP GIS (fire251gdb, layer firep25_1) Features: 23,334 fire perimeter polygons Coverage: California, 1878–2025 License: CC-BY-4.0 Source layer: firep (PMTiles source-layer name)

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.parquet')
4WHERE YEAR_ >= 2024
5ORDER BY GIS_ACRES DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.parquet')
4WHERE YEAR_ >= 2024
5ORDER BY GIS_ACRES DESC
6LIMIT 10;

Hex aggregation note: in calfire-2025/firep/hex/h0=*/data_0.parquet, every source attribute (including GIS_ACRES) is repeated on each H3 cell the fire covers. Never SUM(GIS_ACRES) on hex data. To total burned acreage, deduplicate by feature first: SELECT SUM(GIS_ACRES) FROM (SELECT DISTINCT _cng_fid, GIS_ACRES FROM read_parquet('…/firep/hex/h0=*/data_0.parquet')).

MapLibre GL JS Example

1map.addSource('calfire-firep-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-2025-fill',
7  type: 'fill',
8  source: 'calfire-firep-2025',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-firep-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-2025-fill',
7  type: 'fill',
8  source: 'calfire-firep-2025',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});

CAL FIRE Prescribed Burns 2025 (`calfire-2025/rxburn`) — current

Source: CAL FIRE FRAP GIS (fire251gdb, layer rxburn25_1) Features: 11,975 prescribed burn polygons Coverage: California, 1900–2025 License: CC-BY-4.0 Source layer: rxburn (PMTiles source-layer name)

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY TREATED_AC DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY TREATED_AC DESC
6LIMIT 10;

MapLibre GL JS Example

1map.addSource('calfire-rxburn-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-2025-fill',
7  type: 'fill',
8  source: 'calfire-rxburn-2025',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-rxburn-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-2025-fill',
7  type: 'fill',
8  source: 'calfire-rxburn-2025',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});

1. CAL FIRE Wildfire Perimeters (`calfire-2024/firep`) — prior release

Source: CAL FIRE FRAP GIS Features: 22,810 fire perimeter polygons Coverage: California, 1878–2024 Source layer: firep (PMTiles source-layer name)

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY GIS_ACRES DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY GIS_ACRES DESC
6LIMIT 10;

MapLibre GL JS Example

1map.addSource('calfire-firep', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-fill',
7  type: 'fill',
8  source: 'calfire-firep',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-firep', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-fill',
7  type: 'fill',
8  source: 'calfire-firep',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});

Schema

Column	Type	Description
YEAR_	int16	Calendar year the fire was recorded
STATE	string	State abbreviation (always 'CA')
AGENCY	string	Responding agency code
UNIT_ID	string	CAL FIRE unit identifier
FIRE_NAME	string	Name of the fire
INC_NUM	string	Local incident number
IRWINID	string	IRWIN system incident ID
ALARM_DATE	datetime	Date the fire was reported
CONT_DATE	datetime	Date the fire was contained
C_METHOD	int16	Collection method code
CAUSE	int16	Fire cause code
COMPLEX_NAME	string	Complex fire name (if applicable)
COMPLEX_ID	string	Complex fire ID
OBJECTIVE	int16	Management objective code
GIS_ACRES	float32	GIS-calculated area in acres
COMMENTS	string	Additional comments
FIRE_NUM	string	Historical fire number
Shape_Length	float64	Perimeter length in meters
Shape_Area	float64	Area in square meters

2. CAL FIRE Prescribed Burns (`calfire-2024/rxburn`)

Source: CAL FIRE FRAP GIS Features: 10,675 prescribed burn polygons Coverage: California, 1980s–2024 Source layer: rxburn (PMTiles source-layer name)

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.parquet')
4WHERE YEAR_ >= 2015
5ORDER BY TREATED_AC DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.parquet')
4WHERE YEAR_ >= 2015
5ORDER BY TREATED_AC DESC
6LIMIT 10;

MapLibre GL JS Example

1map.addSource('calfire-rxburn', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-fill',
7  type: 'fill',
8  source: 'calfire-rxburn',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-rxburn', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-fill',
7  type: 'fill',
8  source: 'calfire-rxburn',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});

Schema

Column	Type	Description
YEAR_	int16	Calendar year of treatment
STATE	string	State abbreviation (always 'CA')
AGENCY	string	Responding agency code
UNIT_ID	string	CAL FIRE unit identifier
TREATMENT_ID	string	Unique treatment identifier
TREATMENT_NAME	string	Name of the treatment
TREATMENT_TYPE	int16	Treatment type code
START_DATE	datetime	Treatment start date
END_DATE	datetime	Treatment end date
TREATED_AC	float64	Reported treated area in acres
GIS_ACRES	float32	GIS-calculated area in acres
RX_CONSUM	int16	Fuel consumption class code
PRE_CON_CLASS	int16	Pre-treatment condition class code
POST_CON_CLASS	int16	Post-treatment condition class code
Shape_Length	float64	Perimeter length in meters
Shape_Area	float64	Area in square meters

3. USGS Wildland Fire Combined Dataset (`usgs-fires-2021/combined`)

Source: USGS ScienceBase Features: 135,061 fire perimeter polygons Coverage: Continental US, Alaska, Hawaii, US territories, 1878–2021 Source layer: combined (PMTiles source-layer name)

This dataset combines records from dozens of federal, state, and local data sources into a single de-duplicated national inventory. Where multiple sources cover the same fire, the highest-quality polygon is selected and source attributes are preserved in list fields.

DuckDB Example

1LOAD spatial;
2SELECT Fire_Year, Assigned_Fire_Type, GIS_Acres, Listed_Fire_Names
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.parquet')
4WHERE Fire_Year >= 2000 AND GIS_Acres > 100000
5ORDER BY GIS_Acres DESC
6LIMIT 20;
1LOAD spatial;
2SELECT Fire_Year, Assigned_Fire_Type, GIS_Acres, Listed_Fire_Names
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.parquet')
4WHERE Fire_Year >= 2000 AND GIS_Acres > 100000
5ORDER BY GIS_Acres DESC
6LIMIT 20;

H3 Hex Example (burn area by hex cell)

1import duckdb
2
3conn = duckdb.connect()
4conn.execute("INSTALL httpfs; LOAD httpfs;")
5conn.execute("""
6CREATE SECRET (
7  TYPE S3,
8  KEY_ID '',
9  SECRET '',
10  ENDPOINT 's3-west.nrp-nautilus.io',
11  USE_SSL 'TRUE',
12  URL_STYLE 'path'
13)
14""")
15
16result = conn.execute("""
17SELECT h3_index, SUM(GIS_Acres) AS total_acres
18FROM read_parquet(
19  'https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined/hex/h0=*/data_0.parquet',
20  hive_partitioning=true
21)
22GROUP BY h3_index
23ORDER BY total_acres DESC
24LIMIT 20
25""").df()
1import duckdb
2
3conn = duckdb.connect()
4conn.execute("INSTALL httpfs; LOAD httpfs;")
5conn.execute("""
6CREATE SECRET (
7  TYPE S3,
8  KEY_ID '',
9  SECRET '',
10  ENDPOINT 's3-west.nrp-nautilus.io',
11  USE_SSL 'TRUE',
12  URL_STYLE 'path'
13)
14""")
15
16result = conn.execute("""
17SELECT h3_index, SUM(GIS_Acres) AS total_acres
18FROM read_parquet(
19  'https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined/hex/h0=*/data_0.parquet',
20  hive_partitioning=true
21)
22GROUP BY h3_index
23ORDER BY total_acres DESC
24LIMIT 20
25""").df()

MapLibre GL JS Example

1map.addSource('usgs-fires', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.pmtiles'
4});
5map.addLayer({
6  id: 'usgs-fires-fill',
7  type: 'fill',
8  source: 'usgs-fires',
9  'source-layer': 'combined',
10  paint: {
11    'fill-color': '#ff7f0e',
12    'fill-opacity': 0.4
13  }
14});
1map.addSource('usgs-fires', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.pmtiles'
4});
5map.addLayer({
6  id: 'usgs-fires-fill',
7  type: 'fill',
8  source: 'usgs-fires',
9  'source-layer': 'combined',
10  paint: {
11    'fill-color': '#ff7f0e',
12    'fill-opacity': 0.4
13  }
14});

Schema

Column	Type	Description
USGS_Assigned_ID	int32	Unique USGS identifier
Assigned_Fire_Type	string	Fire type (Wildfire, Prescribed Fire, etc.)
Fire_Year	int16	Year the fire occurred
Fire_Polygon_Tier	int16	Source quality tier (1 = highest quality)
Fire_Attribute_Tiers	string	Quality tier per attribute
GIS_Acres	float64	GIS-calculated area in acres
GIS_Hectares	float64	GIS-calculated area in hectares
Source_Datasets	string	Contributing source dataset names
Listed_Fire_Types	string	All fire types from contributing sources
Listed_Fire_Names	string	All fire names from contributing sources
Listed_Fire_Codes	string	All fire codes from contributing sources
Listed_Fire_IDs	string	All fire IDs from contributing sources
Listed_Fire_IRWIN_IDs	string	All IRWIN IDs from contributing sources
Listed_Fire_Dates	string	All fire dates from contributing sources
Listed_Fire_Causes	string	All fire causes from contributing sources
Listed_Fire_Cause_Class	string	Cause classification
Listed_Rx_Reported_Acres	string	Reported Rx acres
Listed_Map_Digitize_Methods	string	Digitization methods
Listed_Notes	string	Source dataset notes
Processing_Notes	string	USGS processing and QA notes
Wildfire_Notice	string	Data quality notice for wildfire attribution
Prescribed_Burn_Notice	string	Data quality notice for prescribed burn attribution
Wildfire_and_Rx_Flag	string	Wildfire/Rx overlap flag
Overlap_Within_1_or_2_Flag	string	Temporal overlap flag
Circleness_Scale	float64	Shape circularity (1.0 = circle); low values may be artifacts
Circle_Flag	int16	Suspiciously circular geometry flag
Exclude_From_Summary_Rasters	string	Whether to exclude from summary rasters
Shape_Length	float64	Perimeter length in meters

Citation

CAL FIRE datasets: California Department of Forestry and Fire Protection (CAL FIRE), Forest and Range Assessment Program (FRAP). Fire Perimeter and Prescribed Burn data, 2025 release (fire251gdb; 2024 release also retained). https://frap.fire.ca.gov/mapping/gis-data/

USGS dataset: Welty, J.L., and Jeffries, M.I., 2021, Combined wildfire datasets for the United States and certain territories, 1878-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZXGFY3

README

Fire Datasets

This bucket contains CAL FIRE and USGS fire perimeter datasets:

CAL FIRE Wildfire Perimeters — California wildfire perimeters (2025 release calfire-2025/firep, prior calfire-2024/firep)
CAL FIRE Prescribed Burns — California prescribed burn treatments (2025 release calfire-2025/rxburn, prior calfire-2024/rxburn)
USGS Wildland Fire Combined Dataset — National wildfire perimeters 1878–2021 (usgs-fires-2021/combined)

All datasets are polygon geometries processed into GeoParquet, PMTiles, and H3 hex Parquet (resolution 10).

The 2025 CAL FIRE release (FRAP fire251gdb) is the current dataset for California fires and prescribed burns; the 2024 release is retained as a prior version.

CAL FIRE Wildfire Perimeters 2025 (`calfire-2025/firep`) — current

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.parquet')
4WHERE YEAR_ >= 2024
5ORDER BY GIS_ACRES DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.parquet')
4WHERE YEAR_ >= 2024
5ORDER BY GIS_ACRES DESC
6LIMIT 10;

Hex aggregation note: in calfire-2025/firep/hex/h0=*/data_0.parquet, every source attribute (including GIS_ACRES) is repeated on each H3 cell the fire covers. Never SUM(GIS_ACRES) on hex data. To total burned acreage, deduplicate by feature first: SELECT SUM(GIS_ACRES) FROM (SELECT DISTINCT _cng_fid, GIS_ACRES FROM read_parquet('…/firep/hex/h0=*/data_0.parquet')).

MapLibre GL JS Example

1map.addSource('calfire-firep-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-2025-fill',
7  type: 'fill',
8  source: 'calfire-firep-2025',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-firep-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-2025-fill',
7  type: 'fill',
8  source: 'calfire-firep-2025',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});

CAL FIRE Prescribed Burns 2025 (`calfire-2025/rxburn`) — current

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY TREATED_AC DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY TREATED_AC DESC
6LIMIT 10;

MapLibre GL JS Example

1map.addSource('calfire-rxburn-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-2025-fill',
7  type: 'fill',
8  source: 'calfire-rxburn-2025',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-rxburn-2025', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2025/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-2025-fill',
7  type: 'fill',
8  source: 'calfire-rxburn-2025',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});

1. CAL FIRE Wildfire Perimeters (`calfire-2024/firep`) — prior release

Source: CAL FIRE FRAP GIS Features: 22,810 fire perimeter polygons Coverage: California, 1878–2024 Source layer: firep (PMTiles source-layer name)

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY GIS_ACRES DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, FIRE_NAME, AGENCY, GIS_ACRES
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.parquet')
4WHERE YEAR_ >= 2020
5ORDER BY GIS_ACRES DESC
6LIMIT 10;

MapLibre GL JS Example

1map.addSource('calfire-firep', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-fill',
7  type: 'fill',
8  source: 'calfire-firep',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-firep', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/firep.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-firep-fill',
7  type: 'fill',
8  source: 'calfire-firep',
9  'source-layer': 'firep',
10  paint: {
11    'fill-color': '#d62728',
12    'fill-opacity': 0.5
13  }
14});

Schema

Column	Type	Description
YEAR_	int16	Calendar year the fire was recorded
STATE	string	State abbreviation (always 'CA')
AGENCY	string	Responding agency code
UNIT_ID	string	CAL FIRE unit identifier
FIRE_NAME	string	Name of the fire
INC_NUM	string	Local incident number
IRWINID	string	IRWIN system incident ID
ALARM_DATE	datetime	Date the fire was reported
CONT_DATE	datetime	Date the fire was contained
C_METHOD	int16	Collection method code
CAUSE	int16	Fire cause code
COMPLEX_NAME	string	Complex fire name (if applicable)
COMPLEX_ID	string	Complex fire ID
OBJECTIVE	int16	Management objective code
GIS_ACRES	float32	GIS-calculated area in acres
COMMENTS	string	Additional comments
FIRE_NUM	string	Historical fire number
Shape_Length	float64	Perimeter length in meters
Shape_Area	float64	Area in square meters

2. CAL FIRE Prescribed Burns (`calfire-2024/rxburn`)

Source: CAL FIRE FRAP GIS Features: 10,675 prescribed burn polygons Coverage: California, 1980s–2024 Source layer: rxburn (PMTiles source-layer name)

DuckDB Example

1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.parquet')
4WHERE YEAR_ >= 2015
5ORDER BY TREATED_AC DESC
6LIMIT 10;
1LOAD spatial;
2SELECT YEAR_, TREATMENT_NAME, AGENCY, TREATED_AC
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.parquet')
4WHERE YEAR_ >= 2015
5ORDER BY TREATED_AC DESC
6LIMIT 10;

MapLibre GL JS Example

1map.addSource('calfire-rxburn', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-fill',
7  type: 'fill',
8  source: 'calfire-rxburn',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});
1map.addSource('calfire-rxburn', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/calfire-2024/rxburn.pmtiles'
4});
5map.addLayer({
6  id: 'calfire-rxburn-fill',
7  type: 'fill',
8  source: 'calfire-rxburn',
9  'source-layer': 'rxburn',
10  paint: {
11    'fill-color': '#2ca02c',
12    'fill-opacity': 0.5
13  }
14});

Schema

Column	Type	Description
YEAR_	int16	Calendar year of treatment
STATE	string	State abbreviation (always 'CA')
AGENCY	string	Responding agency code
UNIT_ID	string	CAL FIRE unit identifier
TREATMENT_ID	string	Unique treatment identifier
TREATMENT_NAME	string	Name of the treatment
TREATMENT_TYPE	int16	Treatment type code
START_DATE	datetime	Treatment start date
END_DATE	datetime	Treatment end date
TREATED_AC	float64	Reported treated area in acres
GIS_ACRES	float32	GIS-calculated area in acres
RX_CONSUM	int16	Fuel consumption class code
PRE_CON_CLASS	int16	Pre-treatment condition class code
POST_CON_CLASS	int16	Post-treatment condition class code
Shape_Length	float64	Perimeter length in meters
Shape_Area	float64	Area in square meters

3. USGS Wildland Fire Combined Dataset (`usgs-fires-2021/combined`)

DuckDB Example

1LOAD spatial;
2SELECT Fire_Year, Assigned_Fire_Type, GIS_Acres, Listed_Fire_Names
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.parquet')
4WHERE Fire_Year >= 2000 AND GIS_Acres > 100000
5ORDER BY GIS_Acres DESC
6LIMIT 20;
1LOAD spatial;
2SELECT Fire_Year, Assigned_Fire_Type, GIS_Acres, Listed_Fire_Names
3FROM read_parquet('https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.parquet')
4WHERE Fire_Year >= 2000 AND GIS_Acres > 100000
5ORDER BY GIS_Acres DESC
6LIMIT 20;

H3 Hex Example (burn area by hex cell)

1import duckdb
2
3conn = duckdb.connect()
4conn.execute("INSTALL httpfs; LOAD httpfs;")
5conn.execute("""
6CREATE SECRET (
7  TYPE S3,
8  KEY_ID '',
9  SECRET '',
10  ENDPOINT 's3-west.nrp-nautilus.io',
11  USE_SSL 'TRUE',
12  URL_STYLE 'path'
13)
14""")
15
16result = conn.execute("""
17SELECT h3_index, SUM(GIS_Acres) AS total_acres
18FROM read_parquet(
19  'https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined/hex/h0=*/data_0.parquet',
20  hive_partitioning=true
21)
22GROUP BY h3_index
23ORDER BY total_acres DESC
24LIMIT 20
25""").df()
1import duckdb
2
3conn = duckdb.connect()
4conn.execute("INSTALL httpfs; LOAD httpfs;")
5conn.execute("""
6CREATE SECRET (
7  TYPE S3,
8  KEY_ID '',
9  SECRET '',
10  ENDPOINT 's3-west.nrp-nautilus.io',
11  USE_SSL 'TRUE',
12  URL_STYLE 'path'
13)
14""")
15
16result = conn.execute("""
17SELECT h3_index, SUM(GIS_Acres) AS total_acres
18FROM read_parquet(
19  'https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined/hex/h0=*/data_0.parquet',
20  hive_partitioning=true
21)
22GROUP BY h3_index
23ORDER BY total_acres DESC
24LIMIT 20
25""").df()

MapLibre GL JS Example

1map.addSource('usgs-fires', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.pmtiles'
4});
5map.addLayer({
6  id: 'usgs-fires-fill',
7  type: 'fill',
8  source: 'usgs-fires',
9  'source-layer': 'combined',
10  paint: {
11    'fill-color': '#ff7f0e',
12    'fill-opacity': 0.4
13  }
14});
1map.addSource('usgs-fires', {
2  type: 'vector',
3  url: 'pmtiles://https://s3-west.nrp-nautilus.io/public-fire/usgs-fires-2021/combined.pmtiles'
4});
5map.addLayer({
6  id: 'usgs-fires-fill',
7  type: 'fill',
8  source: 'usgs-fires',
9  'source-layer': 'combined',
10  paint: {
11    'fill-color': '#ff7f0e',
12    'fill-opacity': 0.4
13  }
14});

Schema

Column	Type	Description
USGS_Assigned_ID	int32	Unique USGS identifier
Assigned_Fire_Type	string	Fire type (Wildfire, Prescribed Fire, etc.)
Fire_Year	int16	Year the fire occurred
Fire_Polygon_Tier	int16	Source quality tier (1 = highest quality)
Fire_Attribute_Tiers	string	Quality tier per attribute
GIS_Acres	float64	GIS-calculated area in acres
GIS_Hectares	float64	GIS-calculated area in hectares
Source_Datasets	string	Contributing source dataset names
Listed_Fire_Types	string	All fire types from contributing sources
Listed_Fire_Names	string	All fire names from contributing sources
Listed_Fire_Codes	string	All fire codes from contributing sources
Listed_Fire_IDs	string	All fire IDs from contributing sources
Listed_Fire_IRWIN_IDs	string	All IRWIN IDs from contributing sources
Listed_Fire_Dates	string	All fire dates from contributing sources
Listed_Fire_Causes	string	All fire causes from contributing sources
Listed_Fire_Cause_Class	string	Cause classification
Listed_Rx_Reported_Acres	string	Reported Rx acres
Listed_Map_Digitize_Methods	string	Digitization methods
Listed_Notes	string	Source dataset notes
Processing_Notes	string	USGS processing and QA notes
Wildfire_Notice	string	Data quality notice for wildfire attribution
Prescribed_Burn_Notice	string	Data quality notice for prescribed burn attribution
Wildfire_and_Rx_Flag	string	Wildfire/Rx overlap flag
Overlap_Within_1_or_2_Flag	string	Temporal overlap flag
Circleness_Scale	float64	Shape circularity (1.0 = circle); low values may be artifacts
Circle_Flag	int16	Suspiciously circular geometry flag
Exclude_From_Summary_Rasters	string	Whether to exclude from summary rasters
Shape_Length	float64	Perimeter length in meters

Wildfire Boundary Polygons from USGS and CalFire in cloud native formats

Wildfire Boundary Polygons from USGS and CalFire in cloud native formats

Fire Datasets

CAL FIRE Wildfire Perimeters 2025 (calfire-2025/firep) — current

DuckDB Example

MapLibre GL JS Example

CAL FIRE Prescribed Burns 2025 (calfire-2025/rxburn) — current

DuckDB Example

MapLibre GL JS Example

1. CAL FIRE Wildfire Perimeters (calfire-2024/firep) — prior release

DuckDB Example

MapLibre GL JS Example

Schema

2. CAL FIRE Prescribed Burns (calfire-2024/rxburn)

DuckDB Example

MapLibre GL JS Example

Schema

3. USGS Wildland Fire Combined Dataset (usgs-fires-2021/combined)

DuckDB Example

H3 Hex Example (burn area by hex cell)

MapLibre GL JS Example

Schema

Citation

Fire Datasets

CAL FIRE Wildfire Perimeters 2025 (calfire-2025/firep) — current

DuckDB Example

MapLibre GL JS Example

CAL FIRE Prescribed Burns 2025 (calfire-2025/rxburn) — current

DuckDB Example

MapLibre GL JS Example

1. CAL FIRE Wildfire Perimeters (calfire-2024/firep) — prior release

DuckDB Example

MapLibre GL JS Example

Schema

2. CAL FIRE Prescribed Burns (calfire-2024/rxburn)

DuckDB Example

MapLibre GL JS Example

Schema

3. USGS Wildland Fire Combined Dataset (usgs-fires-2021/combined)

DuckDB Example

H3 Hex Example (burn area by hex cell)

MapLibre GL JS Example

Schema

Citation

CAL FIRE Wildfire Perimeters 2025 (`calfire-2025/firep`) — current

CAL FIRE Prescribed Burns 2025 (`calfire-2025/rxburn`) — current

1. CAL FIRE Wildfire Perimeters (`calfire-2024/firep`) — prior release

2. CAL FIRE Prescribed Burns (`calfire-2024/rxburn`)

3. USGS Wildland Fire Combined Dataset (`usgs-fires-2021/combined`)

CAL FIRE Wildfire Perimeters 2025 (`calfire-2025/firep`) — current

CAL FIRE Prescribed Burns 2025 (`calfire-2025/rxburn`) — current

1. CAL FIRE Wildfire Perimeters (`calfire-2024/firep`) — prior release

2. CAL FIRE Prescribed Burns (`calfire-2024/rxburn`)

3. USGS Wildland Fire Combined Dataset (`usgs-fires-2021/combined`)