The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2021, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

This dataset contains data from the P.L. 94-171 2020 Census Redistricting Program. The 2020 Census Redistricting Data Program provides states the opportunity to delineate voting districts and to suggest census block boundaries for use in the 2020 Census redistricting data tabulations (Public Law 94-171 Redistricting Data File). In addition, the Redistricting Data Program will periodically collect state legislative and congressional district boundaries if they are changed by the states. The program is also responsible for the effective delivery of the 2020 Census P.L. 94-171 Redistricting Data statutorily required by one year from Census Day. The program ensures continued dialogue with the states in regard to 2020 Census planning, thereby allowing states ample time for their planning, response, and participation. The U.S. Census Bureau will deliver the Public Law 94-171 redistricting data to all states by Sept. 30, 2021. COVID-19-related delays and prioritizing the delivery of the apportionment results delayed the Census Bureau’s original plan to deliver the redistricting data to the states by April 1, 2021.

Data in this dataset contains information on population, diversity, race, ethnicity, housing, household, vacancy rate for 2020 for various geographies (county, MCD, Philadelphia Planning Districts (referred to as county planning areas [CPAs] internally, Census designated places, tracts, block groups, and blocks)

For more information on the 2020 Census, visit https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html

PLEASE NOTE: 2020 Decennial Census data has had noise injected into it because of the Census's new Disclosure Avoidance System (DAS). This can mean that population counts and characteristics, especially when they are particularly small, may not exactly correspond to the data as collected. As such, caution should be exercised when examining areas with small counts. Ron Jarmin, acting director of the Census Bureau posted a discussion of the redistricting data, which outlines what to expect with the new DAS. For more details on accuracy you can read it here: https://www.census.gov/newsroom/blogs/director/2021/07/redistricting-data.html

Census tracts are designated as urban, rural center, or rural through SB 1000 analysis. These designations are being used for the REV 2.0 and Community Charging in Urban Areas GFOs. Rural centers are contiguous urban census tracts with a population of less than 50,0000. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Rural communities are census tracts where less than 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Urban communities are contiguous urban census tracts with a population of 50,000 or greater. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.Data Dictionary:OBJECTID: Unique IDSTATEFP: State FIPS CodeCOUNTYFP: County FIPS CodeTRACTCE: Census Tract IDGEOID: Geographic IdentifierName: Census Tract ID Name (short)NAMELSAD: Census Tract ID Name (long)ALAND: Land Area (square meters)AWATER: Water Area (square meters)DAC: Whether or not a census tract is a disadvantaged community as defined by SB 535 and designated by CalEPA using CalEnviroScreen 4.0 (May 2022 update)Income_Group: Whether or not a census tract is low-, middle-, or high-income as defined by AB 1550 and designated by CARB and the CEC (June 2023 update)Urban_Rural_RuralCenter: Whether or not a census tract is urban, rural, or rural center as defined and designated by the CEC through the SB 1000 Assessment (2024 update)PerCap_100k_L2DCFC: Number of public Level 2 and DC fast chargers per 100,000 people in a census tractDAC_andor_LIC: Whether or not a census tract is a disadvantaged or low-income community as defined by SB 535 and AB 1550 and designated by CalEPA and CARBUCC_eligible: Whether or not the census tract is an eligible area for the Community Charging in Urban Areas GFO. For a site to be eligible, it must be in a census tract that is either a disadvantaged or low-income community, and urban, and has below the state average for per capita public Level 2 and DC fast chargers as defined by the CEC.REV2_eligible: Whether or not the census tract is an eligible area for the Rural Electric Vehicle Charging 2.0 GFO. For a site to be eligible, it must be in a rural or rural center census tract as defined by the CEC.Shape_Area: Census tract shape area (square meters)Shape_Length: Census tract shape length (square meters)

Tribal Designated Statistical AreasThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Tribal Designated Statistical Areas (TDSA). Per the USCB, “TDSAs are statistical geographic entities identified and delineated for the Census Bureau by federally recognized American Indian tribes that do not currently have an American Indian reservation and/or off-reservation trust land. A TDSA is intended to encompass a compact and contiguous area that contains a concentration of individuals who identify with the delineating federally recognized American Indian tribe. TDSAs are also intended to be comparable to American Indian reservations within the same state or region and provide a means for reporting statistical data for the area.”Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Tribal Designated Statistical Areas) and will support mapping, analysis, data exports and OGC API – Feature access.Data.gov: TIGER/Line Shapefile, 2019, nation, U.S., Current American Indian/Alaska Native/Native Hawaiian Areas National (AIANNH) NationalGeoplatform: TIGER/Line Shapefile, 2019, nation, U.S., Current American Indian/Alaska Native/Native Hawaiian Areas National (AIANNH) NationalFor more information, please visit: My Tribal Area; TIGERwebFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

Visit the Enterprise Zone Program website with any questionsThis web layer contains sub layers for the following Census geographies: counties, tracts, block groups, Census designated places, and county subdivisions. In addition, there is a layer displaying which Census blocks have 'graduated out' - meaning they do not qualify based on any of the above geographies but lie in a current Enterprise Zone.

Potential Environmental Justice Areas (PEJA) is defined in the PEJA field. PEJA's have been identified based on data from the 2014-2018 5-year American Community Survey (ACS), conducted by the US Census Bureau. Environmental justice efforts focus on improving the environment in communities, specifically minority and low-income communities, and addressing disproportionate adverse environmental impacts that may exist in those communities. The information balloon for each census block group area displays the census block group ID, population, percent minority, percent below poverty level, county, municipality, and a link to more information on the Department of Environmental Conservation's website https://www.dec.ny.gov/public/333.html The data was collected by the US Census Bureau as part of the American Community Survey. Reported income and race/ethnicity data were analyzed by OEJ to determine the presence of Potential Environmental Justice Areas. The designated areas are then considered for additional outreach within the permitting process, for grant eligibility, and for targeted enforcement of Environmental Conservation Law violations. Utilized established methods as originally detailed in the Interim Environmental Justice Policy, US EPA Region 2, December 2000, and recommended by the Environmental Justice Advisory Group, Recommendations for the New York State Department of Environmental Conservation Environmental Justice Program, January 2, 2002. Individual thresholds for low-income populations (statewide), minority populations (rural communities), and minority populations (urban communities) were determined by using ArcGIS 10.3 (used to indicate if census block groups overlapped Census designated urban areas) and IBM SPSS Statistics 26 (to conduct a K-means clustering algorithm on ACS data for the three categories).View Dataset on the Gateway

Locations of disadvantaged and/or low-income communities designated by both California and Justice40.Definitions:California-designated Disadvantaged Communities – The California Environmental Protection Agency (CalEPA) identifies four types of geographic areas as disadvantaged: (1) census tracts receiving the highest 25 percent of overall scores in CalEnviroScreen 4.0; (2) census tracts lacking overall scores in CalEnviroScreen 4.0 due to data gaps, but receiving the highest 5 percent of CalEnviroScreen 4.0 cumulative pollution burden scores; (3) census tracts identified in the 2017 DAC designation as disadvantaged, regardless of their scores in CalEnviroScreen 4.0; (4) and areas under the control of federally recognized Tribes. California-designated Low-income Communities – Census tracts with median household incomes at or below 80 percent of the statewide median income or with median household incomes at or below the threshold designated as low income by the California Department of Housing and Community Development’s list of state income limits adopted under Health and Safety Code Section 50093. Justice40-designated disadvantaged communities - Consistent with the Justice40 Interim Guidance, U.S. Department of Transportation (DOT) and U.S. Department of Energy (DOE) developed a joint interim definition of disadvantaged communities for the National Electric Vehicle Infrastructure (NEVI) Formula Program. The joint interim definition uses publicly available data sets that capture vulnerable populations, health, transportation access and burden, energy burden, fossil dependence, resilience, and environmental and climate hazards.

The Commercial Fisheries Entry Commision (CFEC) is an independent, autonomous agency of the State of Alaska which regulates entry into Alaska's commercial fisheries. The CFEC is responsible for leasing all commercial fishing permits including permits for limited-entry fisheries. Limited-entry fisheries include all state salmon fisheries, most herring fisheries, and various other fisheries. This dataset includes age demographics, broken out into decades, of all Alaska resident permanent salmon permit holders between 1975 and 2016. The source of this permit information is permit application and renewal forms collected by CFEC. This dataset tabulates individuals by community and unduplicated by person, meaning that if an individual holds more than one permit, they are only represented once. Also included in this dataset is a script which leverages census designated place data to assign latitude and longitude values to each community.

Dataset containing hazard risk and resistance data for all BCAT-tracked jurisdictions across all 50 states, DC, and 5 US territories (American Samoa, Commonwealth of the Northern Mariana Islands, Guam, Puerto Rico, USVI), but rolled up to the county level. Tracked hazards include: flood, seismic, damaging wind, hurricane wind, and tornado. These five hazards are also consolidated into a "combined hazard" category. If a jurisdiction has high risk for any one of the five tracked hazards, it has high "combined hazard" risk. A jurisdiction is "combined hazard" resistant if and only if it is resistant to all of the individual five hazards for which it has high risk. Risk and resistance methodology is described in detail in the BCAT Glossary, accessible at www.fema.gov/bcat. Dataset aims to track Authorities Having Jurisdiction (AHJs), those political subdivisions of a state which adopt and enforce building codes or, in the absence of any state restrictions, could adopt and enforce building codes if they wanted to. These types of jurisdictions primarily tend to be incorporated places and counties (i.e., not statistical entities like Census blocks or tracts or Census Designated Places). The jurisdictional data is rolled up to the county level such that counties fall into one of three categories: fully resistant (meaning all the tracked jurisdictions in that county are resistant to the given hazard(s)), partially resistant (meaning some but not all of the jurisdictions in that county are resistant to the given hazard(s)), and not resistant (meaning none of the tracked jurisdictions in that county are resistant to the given hazard(s)).

The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on the latest available governmental unit boundaries. The Census TIGER database represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The 2006 Second Edition TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. This shapefile represents the current State Senate Districts for New Mexico as posted on the Census Bureau website for 2006.

This service shows the median household after-tax income in 2015 for Canada, by 2016 census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001. After-tax income - refers to total income less income taxes of the statistical unit during a specified reference period (for additional information refer to Total Income – 2016 Census Dictionary and After-tax Income – 2016 Census Dictionary). The median income of a specified group is the amount that divides the income distribution of that group into two halves. Census subdivision (CSD) is the general term for municipalities (as determined by provincial/territorial legislation) or areas treated as municipal equivalents for statistical purposes (e.g., Indian reserves, Indian settlements and unorganized territories). Municipal status is defined by laws in effect in each province and territory in Canada. To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below. Besides the variable described here, the dataset contains the id, name, type, province, population, land area and the number of private households for each census subdivision. If a value is null, it could be because it is not available for a specific reference period, it is not applicable, it is too unreliable to be published or it is suppressed to meet confidentiality requirements of the Statistics Act. To find out the exact reason, refer to the source data from Census in the resources below.

The U.S. Department of Transportation's and U.S. Department of Energy's joint interim definition of disadvantaged communities for the National Electric Vehicle Infrastructure (NEVI) Formula Program includes combined census tracts from DOT's working disadvantaged community definition and DOE's working DAC definition.Data downloaded in May 2022 from https://www.anl.gov/esia/electric-vehicle-charging-equity-considerations.

Dataset containing hazard risk and resistance data for all BCAT-tracked jurisdictions across all 50 states, DC, and 5 US territories (American Samoa, Commonwealth of the Northern Mariana Islands, Guam, Puerto Rico, USVI), but rolled up to the county level. Tracked hazards include: flood, seismic, damaging wind, hurricane wind, and tornado. These five hazards are also consolidated into a "combined hazard" category. If a jurisdiction has high risk for any one of the five tracked hazards, it has high "combined hazard" risk. A jurisdiction is "combined hazard" resistant if and only if it is resistant to all of the individual five hazards for which it has high risk. Risk and resistance methodology is described in detail in the BCAT Glossary, accessible at www.fema.gov/bcat. Dataset aims to track Authorities Having Jurisdiction (AHJs), those political subdivisions of a state which adopt and enforce building codes or, in the absence of any state restrictions, could adopt and enforce building codes if they wanted to. These types of jurisdictions primarily tend to be incorporated places and counties (i.e., not statistical entities like Census blocks or tracts or Census Designated Places). The jurisdictional data is rolled up to the county level such that counties fall into one of three categories: fully resistant (meaning all the tracked jurisdictions in that county are resistant to the given hazard(s)), partially resistant (meaning some but not all of the jurisdictions in that county are resistant to the given hazard(s)), and not resistant (meaning none of the tracked jurisdictions in that county are resistant to the given hazard(s)).

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Source: U.S. Census Bureau, 2014-2018 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .ACS Technical Documentation..). The effect of nonsampling error is not represented in these tables..One person in each household is designated as the householder. In most cases, this is the person or one of the people in whose name the home is owned, being bought, or rented and who is listed on line one of the survey questionnaire. If there is no such person in the household, any adult household member 15 years old and over could be designated as the householder......Households are classified by type according to the presence of relatives. Two types of householders are distinguished: a family householder and a nonfamily householder. A family householder is a householder living with one or more individuals related to him or her by birth, marriage, or adoption. The householder and all people in the household related to him or her are family members. A nonfamily householder is a householder living alone or with non-relatives only......To determine poverty status of a householder in family households, one compares the total income in the past 12 months of all family members with the poverty threshold appropriate for that family size and composition. If the total family income is less than the threshold, then the householder together with every member of his or her family are considered as having income below the poverty level......In determining poverty status of a nonfamily householder, only the householder's own personal income is compared with the appropriate threshold for a single person. The poverty status of a nonfamily householder does not affect the poverty status of the other unrelated individuals living in the household and the incomes of people living in the household who are not related to the householder are not considered when determining the poverty status of a householder. The income of each unrelated individual is compared to the appropriate threshold for a single person..While the 2014-2018 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the medi...

The Metropolitan Planning Area (MPA) boundary is the line that includes the entire existing urbanized area defined by the United States Census, plus the areas expected to urbanize in the next 20 years. These areas are the basis for long-range and short-range transportation plans required by Federal law.After each Census, Federal rules require that ARC and local governments redraw the boundary. Being included in the MPA means those local governments can apply for federal funding through the TIP process and become eligible for funding under the Livable Centers Initiative, the comprehensive transportation plan, and other ARC projects. Following the 2020 Census, the Census Bureau designated a revised Atlanta Urbanized Area(UA) based on 2020 Census data. The Atlanta UA includes all or part of 20 counties, down from the 23 counties designated following the 2010 Census. These 20 include Barrow, Bartow, Cherokee, Clayton, Cobb, Coweta, Dawson, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Hall, Henry, Newton, Paulding, Rockdale, Spalding, and Walton counties.The Census applied new, stricter criteria in determining whether a census tract was urban or rural. In some places, this has meant that the Atlanta UA appears to have gotten smaller. For this reason, Pike County is no longer included in either the Atlanta Urbanized Area or the new MPA boundary. The Atlanta UA also no longer extends into Carroll County, though the new MPA boundary will include part of Carroll County as detailed below. The parts of Jackson County previously included in the Atlanta UA are now classified with the Gainesville UA. Adjacent to the Atlanta UA are the Cartersville and Gainesville UAs. These areas are represented by their own metropolitan planning organizations (MPOs). By previous formalagreement, ARC has assigned transportation planning responsibilities for the portion of the Atlanta UA in Bartow County to the Cartersville-Bartow Metropolitan Planning Organization (CBMPO).By similar previous formal agreement, ARC has assigned transportation planning responsibilities for the portions of the Atlanta UA in Hall and Jackson counties to the Gainesville-Hall Metropolitan Planning Organization (GHMPO), while GHMPO has assigned transportation planning responsibilities for the portions of the Gainesville UA in Forsyth and Gwinnett counties to ARC. These agreements will be updated to reflect new geographies andnecessary agreements following the 2020 Census.Data from the 2020 Census identified a new Winder Urban Area existing in Barrow,Gwinnett, and Walton counties. With a population of 50,189, the Winder UA exceeds the threshold of 50,000 established by Federal law to be designated as its own MPO. Conversations continue between ARC, the State, the City of Winder, and Barrow County about whether the City and County will form their own MPO; Federal law requires agreementbetween the two bodies. Until and unless Winder and Barrow County elect to form an MPO, they shall remain part of ARC. Should a Winder MPO be created, the new agreement between ARC and GHMPO will also need to include the new Winder MPO and divide transportation planning responsibilities in Barrow, Gwinnett, Hall, and Walton counties between the three agencies. ARC has developed the attached revised Metropolitan Planning Area through discussions with planning partners.• Like before, the new MPA boundary continues to contain the ARC’s 11-county region (Cherokee, Clayton, Cobb, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, and Rockdale) in its entirety, as well as the entirety of Coweta and Paulding counties.• Newton County is now included in the new MPA boundary in its entirety to account for significant growth along Interstate 20 in the Covington and Stanton Springs areas.• Barrow County is also now included in the new MPA boundary in its entirety until and unless the City of Winder and Barrow County form their own MPO.• While the Atlanta UA was reduced in Spalding County, and a separate Griffin UA identified that does not meet the minimum threshold to form its own MPO, the new MPA boundary expands to include all of Spalding County to account for expected growth along Interstate 75, US 19-41, and State Route 16.• In Dawson County, the new MPA boundary accounts for population growth along Lake Lanier.• In Walton County, the new MPA boundary includes areas that the Census has designated as urban, as well as the cities of Monroe and Social Circle.• Carroll County is no longer considered part of the Atlanta Urbanized Area. The county contains two separate Urbanized Areas, Carrollton and Villa Rica, neither of which is large enough to form its own MPO. Because the City of Villa Rica is geographically divided between Carroll and Douglas counties, the City has opted to remain entirely within ARC. Accordingly, the new MPA boundary includes the portion of Villa Rica in Carroll County.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..One person in each household is designated as the householder. In most cases, this is the person or one of the people in whose name the home is owned, being bought, or rented and who is listed on line one of the survey questionnaire. If there is no such person in the household, any adult household member 15 years old and over could be designated as the householder.Households are classified by type according to the presence of relatives. Two types of householders are distinguished: a family householder and a nonfamily householder. A family householder is a householder living with one or more individuals related to him or her by birth, marriage, or adoption. The householder and all people in the household related to him or her are family members. A nonfamily householder is a householder living alone or with non-relatives only.To determine poverty status of a householder in family households, one compares the total income in the past 12 months of all family members with the poverty threshold appropriate for that family size and composition. If the total family income is less than the threshold, then the householder together with every member of his or her family are considered as having income below the poverty level.In determining poverty status of a nonfamily householder, only the householder's own personal income is compared with the appropriate threshold for a single person. The poverty status of a nonfamily householder does not affect the poverty status of the other unrelated individuals living in the household and the incomes of people living in the household who are not related to the householder are not considered when determining the poverty status of a householder. The income of each unrelated individual is compared to the appropriate threshold for a single person..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an ...

Footnotes:1Age' refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well-defined reference date).2Low-income status refers to the income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income. For the 2021 Census, the reference period for low-income data is the calendar year 2020.3Low-income status refers to the income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income. For the 2021 Census, the reference period for low income data is the calendar year 2020.4Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.5Low-income status refers to the income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income. For the 2021 Census, the reference period for low income data is the calendar year 2020.6Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.7For more information, refer to the Census Dictionary: Census family.8This category includes men (and/or boys), as well as some non-binary persons.9Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses provided. In these cases, individuals in the category “non-binary persons” are distributed into the other two gender categories and are denoted by the “+” symbol.10This category includes women (and/or girls), as well as some non-binary persons.11Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses provided. In these cases, individuals in the category “non-binary persons” are distributed into the other two gender categories and are denoted by the “+” symbol.12For more information, refer to the Census Dictionary: Census family; Child presence.13For more information, refer to the Census Dictionary: Household living arrangements.14Includes foster children.15For more information, refer to the Census Dictionary: Household type; Census family.16Persons living in one-census-family households with additional persons and persons in multiple-census-family households.

description: A new component of fair housing studies is an analysis of the opportunities residents are afforded in racially or ethnically concentrated areas of poverty, also called RCAPs or ECAPs. An RCAP or ECAP is a neighborhood with significant concentrations of extreme poverty and minority populations. HUD s definition of an RCAP/ECAP is: A Census tract that has a non white population of 50 percent or more AND a poverty rate of 40 percent or more; OR A Census tract that has a non white population of 50 percent or more AND the poverty rate is three times the average tract poverty rate for the metro/micro area, whichever is lower. Why the 40 percent threshold? The RCAP/ECAP definition is not meant to suggest that a slightly lower than 40 percent poverty rate is ideal or acceptable. The threshold was borne out of research that concluded a 40 percent poverty rate was the point at which a neighborhood became significantly socially and economically challenged. Conversely, research has shown that areas with up to 14 percent of poverty have no noticeable effect on community opportunity. (See Section II in City of Austin s 2015 Analysis of Impediments to Fair Housing Choice: http://www.austintexas.gov/sites/default/files/files/NHCD/Reports_Publications/1Analysis_Impediments_for_web.pdf) This dataset provides socioeconomic data on protected classes from the 2008-2012 American Community Survey on census tracts in Austin s city limits and designates which of those tracts are considered RCAPs or ECAPs based on these socioeconomic characteristics. A map of the census tracts designated as RCAPs or ECAPs is attached to this dataset and downloadable as a pdf (see below).; abstract: A new component of fair housing studies is an analysis of the opportunities residents are afforded in racially or ethnically concentrated areas of poverty, also called RCAPs or ECAPs. An RCAP or ECAP is a neighborhood with significant concentrations of extreme poverty and minority populations. HUD s definition of an RCAP/ECAP is: A Census tract that has a non white population of 50 percent or more AND a poverty rate of 40 percent or more; OR A Census tract that has a non white population of 50 percent or more AND the poverty rate is three times the average tract poverty rate for the metro/micro area, whichever is lower. Why the 40 percent threshold? The RCAP/ECAP definition is not meant to suggest that a slightly lower than 40 percent poverty rate is ideal or acceptable. The threshold was borne out of research that concluded a 40 percent poverty rate was the point at which a neighborhood became significantly socially and economically challenged. Conversely, research has shown that areas with up to 14 percent of poverty have no noticeable effect on community opportunity. (See Section II in City of Austin s 2015 Analysis of Impediments to Fair Housing Choice: http://www.austintexas.gov/sites/default/files/files/NHCD/Reports_Publications/1Analysis_Impediments_for_web.pdf) This dataset provides socioeconomic data on protected classes from the 2008-2012 American Community Survey on census tracts in Austin s city limits and designates which of those tracts are considered RCAPs or ECAPs based on these socioeconomic characteristics. A map of the census tracts designated as RCAPs or ECAPs is attached to this dataset and downloadable as a pdf (see below).

Tabular Summaries - Communities at Risk As part of Montana DNRC’s Montana Wildfire Risk Assessment (MWRA), wildfire risk to homes, commercial buildings, and other structures was assessed across the state. The purpose of this assessment is to identify the counties and communities whose structures are most threatened by wildfire—both on average and in total. The risk-to-structures methods used for this assessment are identical to the methods used for structures within the overall MWRA project. See earlier section 3.4.1 of the report (page 20) for details. This portion of the report addresses only the tabular summaries. The summary methods used in this section were customized to the MWRA results from similar methods previously developed for the Pacific Northwest Risk Assessment (PNRA) and for the national Wildfire Risk to Communities (WRC) project.  Mean Risk to Structures We calculated the Mean Risk to Structures as the product of Mean Conditional Risk to Structures and Mean Burn Probability (multiplied by 1000 to remove decimal places). This is the primary variable by which the summary polygons are ranked. Like the components used to calculate it, Mean Risk to Structures is not a cumulative measure for a summary polygon, so it does not necessarily increase as the number or importance of structures increases. It represents the average of the structures in the polygon regardless of the total number or importance of structures. Total Structure Risk We calculated Total Structure Risk as the product of Mean Risk to Structures and Total Structure Importance. This is the secondary variable by which the summary polygons are ranked. Unlike the previous measures, the total importance of structures (their number and mean importance) strongly influences Total Structure Risk. The risk-to-structures results were summarized for two primary sets of summary polygons: MT Counties MT Communities Expanded Area Each set of summary polygons captures nearly all structures in Montana, without overlap. In the MT Counties set, a summary polygon is an individual county (e.g. Ravalli County). In the MT Communities (core plus zone combined) set called MT Communities Expanded Area, a summary polygon is the community core plus the zone surrounding the core (as defined below). Expanded Areas include populated areas outside of official community boundaries that are closer to the selected community than to any other community. Long definition: Populated areas not within the boundaries of a community were associated with the community to which they were closest, as measured by travel time. Travel time is influenced by road networks, associated travel speeds, and physical barriers such as water. Populated areas greater than 45 minutes travel time from any community are not included within the Expanded Area for any community. For this assessment, a community core was defined as a Populated Place Area (PPA) as identified by the U.S. Census Bureau. PPAs include incorporated cities and towns as well as Census Designated Places (CDPs). A CDP is an unincorporated concentration of population—a statistical counterpart to incorporated cities and towns. There are 364 PPAs across Montana. Of those, 127 (35 percent) are incorporated cities or towns, and 235 (65 percent) are CDPs. Two PPAs—Butte-Silver Bow and Anaconda-Deer Lodge—are unique in that they represent the balance of a county that is not otherwise incorporated; they are much larger in size than most PPAs. In the PPA dataset, the CDPs represent the location of highest concentration of population for a community; they do not include the less-densely populated areas surrounding the PPA. We refer to the U.S. Census PPA delineation as the community “core.” Approximately 66 percent of Montana’s total structure importance can be found within these PPA core areas (Figure A.1 of the Montana Wildfire Risk Assessment report). To include the populated area and structures surrounding the PPAs, Ager and others (2019) used a travel-time analysis to delineate the land areas closest by drive-time to each PPA core, up to a maximum of 45 minutes travel time. Approximately 33 percent of Montana’s total structure importance can be found within 45 minutes travel time of the cores. Only 1 percent of the total structure importance is not within 45-minutes travel time of any community core.