In 2023, 36.8 percent of Hawaii residents were Asian. A further 28 percent of the population were of two or more races, and 21 percent of Hawaii residents were white in that same year.

About this dataset

Context

The dataset tabulates the population of Hawaii by race. It includes the population of Hawaii across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Hawaii across relevant racial categories.

Key observations

The percent distribution of Hawaii population by race (across all racial categories recognized by the U.S. Census Bureau): 22.51% are white, 1.92% are Black or African American, 0.27% are American Indian and Alaska Native, 37.27% are Asian, 10.31% are Native Hawaiian and other Pacific Islander, 1.68% are some other race and 26.05% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Hawaii
• Population: The population of the racial category (excluding ethnicity) in the Hawaii is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Hawaii total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hawaii Population by Race & Ethnicity. You can refer the same here

86,58 (persons per sq. km) in 2022.

in 2021, over four percent of the total population of Hawaii was uninsured, one of the lowest in the U.S. The largest part of Hawaii's population was insured through employers. This statistic depicts the health insurance status distribution of the total population in Hawaii in 2021.

86,58 (persons per sq. km) в 2022.

About this dataset

Context

The dataset tabulates the Hawaii County population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Hawaii County. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 114,064 (56% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Hawaii County population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Hawaii County is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Hawaii County is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hawaii County Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Hawaii County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Hawaii County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.18% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Hawaii County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Hawaii County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hawaii County Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Hawaii population pyramid, which represents the Hawaii population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Hawaii, is 28.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Hawaii, is 31.8.
• Total dependency ratio for Hawaii is 59.8.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Hawaii is 3.1.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Hawaii population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Hawaii for the selected age group is shown in the following column.
• Population (Female): The female population in the Hawaii for the selected age group is shown in the following column.
• Total Population: The total population of the Hawaii for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hawaii Population by Age. You can refer the same here

This dataset contains a collection of known point locations of melon-headed whales identified through direct human observation via shipborne and aerial surveys. This can be useful for assessing species abundance, population structure, habitat use, and behavior. This collection is aggregated from multiple data sources and survey periods listed below. Each data point contains attributes for further information about the time and source of the observation. This dataset was compiled by the Pacific Islands Ocean Observing System (PacIOOS) and may be updated in the future if additional data sources are acquired. Cascadia Research Collective (CRC) has been undertaking shipborne surveys for odontocetes in Hawaiian waters since 2000. Two populations of melon-headed whales have been identified in Hawaii: a smaller population resident to shallow waters off the northwest side of Hawaii Island and a larger population that moves among multiple Hawaiian islands and offshore. In addition, Dr. Joseph Mobley of the Marine Mammal Research Consultants (MMRC) led aerial surveys for cetaceans in Hawaiian waters from 1993-2003. For further information, please see: http://www.cascadiaresearch.org/hawaiian-cetacean-studies/melon-headed-whales-hawaii

About this dataset

Context

The dataset tabulates the Hawaii County population by age. The dataset can be utilized to understand the age distribution and demographics of Hawaii County.

Content

The dataset constitues the following three datasets

• Hawaii County, HI Age Group Population Dataset: A complete breakdown of Hawaii County age demographics from 0 to 85 years, distributed across 18 age groups
• Hawaii County, HI Age Cohorts Dataset: Children, Working Adults, and Seniors in Hawaii County - Population and Percentage Analysis
• Hawaii County, HI Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

This CSV file contains landscape factors representing anthropogenic disturbances to stream habitats summarized within local and network stream catchments as well as the downstream main channel catchments of perennial and intermittent stream reaches of the five main islands of Hawai'i. The source datasets compiled and attributed to spatial units were identified as being: (1) meaningful for assessing fluvial fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) broadly representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. Variables summarized at the catchment scale include measures of anthropogenic land uses, golf courses, population density, roads, ditches, pipelines, dams, mines, point-source pollution sites, and locations of former plantation lands. In this dataset variable summaries are linked to the Hawaii Fish Habi ...

Distance-power relationship data we used to create and evaluate a protocol to estimate population density, which can be used to compute abundance of terrestrial sound-producing animals from single automatic acoustic recorders and using an automatic detection algorithm. First posted - January 18, 2017 (available from author) Revised - August 22, 2018 (version 1.1)

The towed-diver method is used to conduct benthic surveys, assessing large-scale disturbances (e.g., bleaching) and quantifying benthic components such as habitat complexity/type and the general distribution and abundance patterns of live coral, CCA, macroalgae, and macroinvertebrates. Surveys are conducted in the Hawaiian and Mariana Archipelagos, American Samoa, and the Pacific Remote Island Areas as part of the NOAA National Coral Reef Monitoring Program (NCRMP). A suitable method for assessing relatively large areas of reef habitat, the method involves towing a pair of SCUBA divers—one benthic and one fish—behind a small boat for approximately 50 min following the ~15-m depth contour and covering about 2–3 km of habitat. Each diver is equipped with a towboard and attempts to maintain a constant elevation above the surface of the reef (~1 m) for the duration of the survey. A complete towed-diver survey is divided into 10, 5-min segments, with visual observations recorded by 5-min segment.

The visual estimate data provided in this dataset were collected during towed-diver surveys which includes percentage cover of total live hard corals, stressed hard corals, soft corals, sand, coralline algae, and macroalgae, and the number of individual macroinvertebrates (crown of thorns starfish (COTS), sea urchins, and giant clams). Benthic habitat complexity and type data are also collected as part of the survey with the following habitat type categories: continuous reef, spur and groove, patch reefs, rock boulders, pavement, rubble flat, sand flats, pinnacle, and wall.

The data were collected around the Hawaiian Archipelago as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led mission in 2016. These data can be accessed online via the NOAA National Centers for Environmental Information (NCEI) Ocean Archive.

This dataset contains a collection of known point locations of bottlenose dolphins identified either via automated satellite tracking of tagged organisms or through direct human observation via shipborne and aerial surveys. This can be useful for assessing species abundance, population structure, habitat use, and behavior. This collection is aggregated from multiple data sources and survey periods listed below. Each data point contains attributes for further information about the time and source of the observation. This dataset was compiled by the Pacific Islands Ocean Observing System (PacIOOS) and may be updated in the future if additional data sources are acquired. Cascadia Research Collective (CRC) has been undertaking surveys for odontocetes in Hawaiian waters since 2000. There are multiple island-associated populations of bottlenose dolphins recognized in Hawaiian waters, based on photo-identification, genetics, and satellite tagging, with individuals remaining associated with one or a couple of islands. Satellite tagging has been undertaken off Kauai to examine movements of individuals in relation to the U.S. Navy's Pacific Missile Range Facility. In addition, Dr. Joseph Mobley of the Marine Mammal Research Consultants (MMRC) led aerial surveys for cetaceans in Hawaiian waters from 1993-2003. For further information, please see: http://www.cascadiaresearch.org/hawaiian-cetacean-studies/bottlenose-dolphins-hawaii

To support a long-term NOAA Coral Reef Conservation Program (CRCP) for sustainable management and conservation of coral reef ecosystems, from 16 October - 14 November 2008, belt transect surveys of coral population and diseases quantitative assessments were conducted, as a part of Rapid Ecological Assessments (REA), during the Pacific Reef Assessment and Monitoring Program (RAMP) Cruise OES0810 in the Main Hawaiian Islands at biennial intervals by the Coral Reef Ecosystem Division (CRED) at the NOAA Pacific Islands Fisheries Science Center (PIFSC). During the cruise, there were 23 surveys in total conducted at REA sites around Hawaii Island in the Main Hawaiian Islands. At the specific REA sites, coral biologists along with fish biologists, algal biologists and marine invertebrate zoologist entered the water and conducted a fine-scale (~300 m2) and high degree of taxonomic resolution REA survey to assess and monitor species composition, abundance, percent cover, size distribution, diversity, and general health of fish, corals, macro-invertebrates, and algae in shallow-water (< 35 m) habitats. As a part of REA surveys, the coral belt surveys were focused on quantifying the diversity, abundance, density, and size-class distribution of the anthozoan and hydrozoan corals as well as the condition and health state of the coral reef populations. The surveys were conducted along two consecutively-placed, 25m transect lines. The belt width was dictated at the beginning of each dive by subjective perceived colony density: 1-m width was used in high density areas, while 2-m width was used in low density areas. Within each 25m transect, five 2.5-meter segments were surveyed (beginning at points: 0, 5, 10, 15, and 20 meters), whereby in each segment, all coral colonies whose center fell within 0.5m of either side of the transect line were identified to the lowest taxonomic level possible (genus or species) and two planar size metrics were collected: maximum diameter and diameter perpendicular to the maximum diameter. In addition, the extent of mortality, both recent and old, was estimated for each colony. Observers paid special attention to identifying as best as possible the extent of the former live colony. When a coral colony exhibited signs of disease or compromised health, additional information was recorded including type of affliction (bleaching, skeletal growth anomaly, white syndrome, tissue loss other than white syndrome, trematodiasis, necrosis, other, pigmentation responses, algal overgrowth, and predation), severity of the affliction (mild, moderate, marked, severe, acute), as well as photographic documentation and sometimes tissue samples. Tissue samples were catalogued and fixed in buffered zinc-formalin solution for further histopathological analyses. Raw survey data included species presence and relative abundance, colony counts per taxon, size (width and length), mortality, predation, and health status. A surveyed area was ranging from 10m2 to 25m2 per site.

About this dataset

Context

The dataset tabulates the population of Hawaii County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Hawaii County. The dataset can be utilized to understand the population distribution of Hawaii County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Hawaii County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Hawaii County.

Key observations

Largest age group (population): Male # 65-69 years (8,009) | Female # 65-69 years (8,666). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Hawaii County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Hawaii County is shown in the following column.
• Population (Female): The female population in the Hawaii County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Hawaii County for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hawaii County Population by Gender. You can refer the same here

Towed-diver surveys (aka. Towboard surveys) are conducted by the Coral Reef Ecosystem Division (CRED) of the NOAA Pacific Islands Fisheries Science Center (PIFSC) as part of biennial Pacific Reef Assessment and Monitoring Program (RAMP) Cruises. These cruises support NOAA Coral Reef Conservation Program (CRCP) long-term goals for sustainable management and conservation of coral reef ecosystems. 36 towboard surveys (81.8972 km in length), were conducted at Hawaii Island in the Main Hawaiian Islands from 24 February - 6 March 2005 as part of RAMP Cruise OES0502. Towboard surveys are a good method for obtaining a general description of large reef areas, assessing the status of low-density populations of large-bodied reef fish, large-scale disturbances (e.g., bleaching), general distribution and abundance patterns of macro-invertebrates (e.g., COT, giant clams), and for assessing trends in these populations and metrics. A pair of scuba divers (1 fish and 1 benthic diver) are towed 60 m behind a small survey launch at a speed of 1-2 knots and a depth of approximately 15m. Each survey is 50 min long, covers about 2 km of habitat, and is divided into ten 5-minute survey segments. The fish diver records, to the lowest possible taxon, all large-bodied reef fishes (>50cmTL) seen within 5m either side and 10m in front of the towboard. Length of each individual is estimated to the nearest cm. The fish towboard is also outfitted with a forward-facing digital video camera to record the survey swath. The benthic diver records percent cover of coral and macroalgae, estimates benthic habitat type and complexity, and censuses a suite of benthic macroinvertebrates including Crown of Thorns sea stars and sea urchins. The benthic towboard is equipped with a downward-facing digital still camera which images the benthos at 15 second intervals. These images are analyzed for percent cover of coral, algae, and other benthic components. Both towboards are equipped with SEABIRD SBE-39 temperature/depth sensors set to record at 5 second intervals. Latitude and longitude of each survey track is recorded at 15 second intervals using a Global Positioning System (GPS) receiver onboard the tow boat. A layback algorithm is applied to more accurately map the position of the divers with respect to the reef environment. This algorithm calculates the position of the divers based on the position of the tow boat taking into account the length of the tow rope, the depth of the divers, and the curvature of the survey track. This metadata applies to the fish biomass observations.

This dataset contains a collection of known point locations of short-finned pilot whales identified either via automated satellite tracking of tagged organisms or through direct human observation via shipborne and aerial surveys. This can be useful for assessing species abundance, population structure, habitat use, and behavior. This collection is aggregated from multiple data sources and survey periods listed below. Each data point contains attributes for further information about the time and source of the observation. This dataset was compiled by the Pacific Islands Ocean Observing System (PacIOOS) and may be updated in the future if additional data sources are acquired.

Cascadia Research Collective (CRC) has been undertaking shipborne surveys for odontocetes in Hawaiian waters since 2000. Short-finned pilot whales are among the most frequently encountered odontocetes in deep water around the main Hawaiian Islands. There appear to be island-resident populations in deep waters around all of the main Hawaiian Islands. From photo-identification and satellite tagging there is evidence of both an island-associated and a pelagic population of short-finned pilot whales in Hawaii, and several different communities of island-associated pilot whales around the islands, with individuals largely remaining associated with one or two islands. In adition, Dr. Joseph Mobley of the Marine Mammal Research Consultants (MMRC) led aerial surveys for cetaceans in Hawaiian waters from 1993-2003.

For further information, please see: http://www.cascadiaresearch.org/short-finned-pilot-whales-hawaii

This map illustrates where infrastructure and population could be potentially impacted by a one meter sea level rise by the year 2100. Examples of infrastructure: airports, education establishments, medical facilities, and buildings. The pattern is shown along coastal areas by both tracts and counties. The sea level rise model comes from the Climate Mapping Resilience and Adaptation (CMRA) portal. As you zoom into the map, you can see the pattern by where human settlement exists. This helps illustrate the pattern by where people live.Airport data: Airports (National) - National Geospatial Data Asset (NGDA) AirportsData can be accessed hereOpenStreetMap Data:BuildingsMedical FacilitiesEducation EstablishmentsPopulation data: ACS Table(s): B01001Data downloaded from: Census Bureau's API for American Community Survey Data can be accessed hereHuman Settlement data:WorldPop Population Density 2000-2020 100mData can be accessed hereAbout the CMRA data:The Climate Mapping Resilience and Adaptation (CMRA) portal provides a variety of information for state, local, and tribal community resilience planning. A key tool in the portal is the CMRA Assessment Tool, which summaries complex, multidimensional raster climate projections for thresholded temperature, precipitation, and sea level rise variables at multiple times and emissions scenarios. This layer provides the geographical summaries. What's included?Census 2019 counties and tracts; 2021 American Indian/Alaska Native/Native Hawaiian areas25 Localized Constructed Analogs (LOCA) data variables (only 16 of 25 are present for Hawaii and territories)Time periods / climate scenarios: historical; RCP 4.5 early-, mid-, and late-century; RCP 8.5 early-, mid-, and late-centuryStatistics: minimum, mean, maximumSeal level rise (CONUS only)Original Layers in Living Atlas:U.S. Climate Thresholds (LOCA)U.S. Sea Level Rise Source Data:Census TIGER/Line dataAmerican Indian, Alaska Native, and Native Hawaiian areasLOCA data (CONUS)LOCA data (Hawaii and territories)Sea level rise

The data included in this publication depict components of wildfire risk specifically for populated areas in the United States. These datasets represent where people live in the United States and the in situ risk from wildfire, i.e., the risk at the location where the adverse effects take place.

National wildfire hazard datasets of annual burn probability and fire intensity, generated by the USDA Forest Service, Rocky Mountain Research Station and Pyrologix LLC, form the foundation of the Wildfire Risk to Communities data. Vegetation and wildland fuels data from LANDFIRE 2020 (version 2.2.0) were used as input to two different but related geospatial fire simulation systems. Annual burn probability was produced with the USFS geospatial fire simulator (FSim) at a relatively coarse cell size of 270 meters (m). To bring the burn probability raster data down to a finer resolution more useful for assessing hazard and risk to communities, we upsampled them to the native 30 m resolution of the LANDFIRE fuel and vegetation data. In this upsampling process, we also spread values of modeled burn probability into developed areas represented in LANDFIRE fuels data as non-burnable. Burn probability rasters represent landscape conditions as of the end of 2020. Fire intensity characteristics were modeled at 30 m resolution using a process that performs a comprehensive set of FlamMap runs spanning the full range of weather-related characteristics that occur during a fire season and then integrates those runs into a variety of results based on the likelihood of those weather types occurring. Before the fire intensity modeling, the LANDFIRE 2020 data were updated to reflect fuels disturbances occurring in 2021 and 2022. As such, the fire intensity datasets represent landscape conditions as of the end of 2022. The data products in this publication that represent where people live, reflect 2020 estimates of housing units and 2021 estimates of population counts from the U.S. Census Bureau, combined with building footprint data from Onegeo and USA Structures, both reflecting 2022 conditions.

The specific raster datasets included in this publication include:

Building Count: Building Count is a 30-m raster representing the count of buildings in the building footprint dataset located within each 30-m pixel.

Building Density: Building Density is a 30-m raster representing the density of buildings in the building footprint dataset (buildings per square kilometer [km²]).

Building Coverage: Building Coverage is a 30-m raster depicting the percentage of habitable land area covered by building footprints.

Population Count (PopCount): PopCount is a 30-m raster with pixel values representing residential population count (persons) in each pixel.

Population Density (PopDen): PopDen is a 30-m raster of residential population density (people/km²).

Housing Unit Count (HUCount): HUCount is a 30-m raster representing the number of housing units in each pixel.

Housing Unit Density (HUDen): HUDen is a 30-m raster of housing-unit density (housing units/km²).

Housing Unit Exposure (HUExposure): HUExposure is a 30-m raster that represents the expected number of housing units within a pixel potentially exposed to wildfire in a year. This is a long-term annual average and not intended to represent the actual number of housing units exposed in any specific year.

Housing Unit Impact (HUImpact): HUImpact is a 30-m raster that represents the relative potential impact of fire to housing units at any pixel, if a fire were to occur. It is an index that incorporates the general consequences of fire on a home as a function of fire intensity and uses flame length probabilities from wildfire modeling to capture likely intensity of fire.

Housing Unit Risk (HURisk): HURisk is a 30-m raster that integrates all four primary elements of wildfire risk - likelihood, intensity, susceptibility, and exposure - on pixels where housing unit density is greater than zero.The geospatial data products described and distributed here are part of the Wildfire Risk to Communities project. This project was directed by Congress in the 2018 Consolidated Appropriations Act (i.e., 2018 Omnibus Act, H.R. 1625, Section 210: Wildfire Hazard Severity Mapping) to help U.S. communities understand components of their relative wildfire risk profile, the nature and effects of wildfire risk, and actions communities can take to mitigate risk. The first edition of these data represented the first time wildfire risk to communities had been mapped nationally with consistent methodology. They provided foundational information for comparing the relative wildfire risk among populated communities in the United States. In this version, the 2nd edition, we use improved modeling and mapping methodology and updated input data to generate the current suite of products.See the Wildfire Risk to Communities website at https://www.wildfirerisk.org for complete project information and an interactive web application for exploring some of the datasets published here. We deliver the data here as zip files by U.S. state (including AK and HI), and for the full extent of the continental U.S.

This data publication is a second edition and represents an update to any previous versions of Wildfire Risk to Communities risk datasets published by the USDA Forest Service. This second edition was originally published on 06/03/2024. On 09/10/2024, a minor correction was made to the abstract in this overall metadata document as well as the individual metadata documents associated with each raster dataset. The supplemental file containing data product descriptions was also updated. In addition, we separated the large CONUS download into a series of smaller zip files (one for each layer).

There are two companion data publications that are part of the WRC 2.0 data update: one that characterizes landscape-wide wildfire hazard and risk for the nation (Scott et al. 2024, https://doi.org/10.2737/RDS-2020-0016-2), and one that delineates wildfire risk reduction zones and provides tabular summaries of wildfire hazard and risk raster datasets (Dillon et al. 2024, https://doi.org/10.2737/RDS-2024-0030).