Census Tracts from 2020. The TIGER/Line shapefiles 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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2020 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2010 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area.

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)

Dataset Summary About this data: This layer presents the USA 2020 Census tracts within the City of Rochester boundary. The geography is sourced from US Census Bureau 2020 TIGER FGDB (National Sub-State) and cut by the City of Rochester boundary. Data Dictionary: STATE_ABBR: The two-letter abbreviation for a state (such as NY). STATE_FIPS: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state. New York State is 36. COUNTY_FIP: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county. Monroe County is 055. STCO_FIPS: The five-digit Federal Information Processing Standards (FIPS) code assigned to iedntify a unique county, typically as a concatenation of the State FIPS code and the County FIPS code. TRACT_FIPS: The six-digit number assigned to each census tract in a US county. FIPS: A unique geographic identifier, typically as a concatenation of State FIPS code, County FIPS code, and Census tract code. POPULATION: The population of a census tract. POP_SQMI: The population per square mile of a census tract. SQMI: The size of a census tract in square miles. Division: The name of the City of Rochester data division that the census tract falls in to. Source: This data comes from the Census Bureau.

Dataset Summary About this data: This layer presents the USA 2020 Census tracts within the City of Rochester boundary. The geography is sourced from US Census Bureau 2020 TIGER FGDB (National Sub-State) and cut by the City of Rochester boundary. Data Dictionary: STATE_ABBR: The two-letter abbreviation for a state (such as NY). STATE_FIPS: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state. New York State is 36. COUNTY_FIP: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county. Monroe County is 055. STCO_FIPS: The five-digit Federal Information Processing Standards (FIPS) code assigned to iedntify a unique county, typically as a concatenation of the State FIPS code and the County FIPS code. TRACT_FIPS: The six-digit number assigned to each census tract in a US county. FIPS: A unique geographic identifier, typically as a concatenation of State FIPS code, County FIPS code, and Census tract code. POPULATION: The population of a census tract. POP_SQMI: The population per square mile of a census tract. SQMI: The size of a census tract in square miles. Division: The name of the City of Rochester data division that the census tract falls in to. Source: This data comes from the Census Bureau.

The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2010 Census blocks nest within every other 2010 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.Field Definiiton:STATEFP10 - 2010 Census State FIPS codesCOUNTYFP10 - 2010 Census County FIPS CodesTRACTCE10 - 2010 Census Census Tract codeBLOCKCE10 - 2010 Census Census block codeGEOID10 - "Census block group identifier; a concatenation of 2010 Census state FIPS code, county FIPS code, and census tract code, and the block group number"NAME10 - 2010 Census translated legal/statistical area description and the block group numberMTFCC10 - 2010 Census MAF/TIGER featture class codeUR10 - 2010 Census Urban/RuralUACE10 - 2010 Census Urban AreaFUNCSTAT10 - 2010 Census Functional Statitical CodeALAND10 - 2010 Census Area LandAWATER10 - 2010 Census Area waterINTPTLAT10 - 2010 Census Internal Point (Latitude)INTPTLON10 - 2010 Census Internal Point (Longtitude)POPULATION - Total PopulationHOUSING_UNITS - Total Housing units

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.

blockgroupvulnerability OPPORTUNITY The US Centers for Disease Control (CDC) publishes a set of percentiles that compare US geographies by vulnerability across household, socioeconomic, racial/ethnic and housing themes. These Social Vulnerability Indexes (SVI) were originally intended to to help public health officials and emergency response planners identify communities that will need support around an event. They are generally valuable for any public interest that wants to relate themselves to needy communities by geography. The SVI publication and its basis variables are provided at the Census tract level of geographic detail. The Census' American Community Survey is available down the to the block group level, however. Recasting the SVI methods at this lower level of geography allows it to be tied to thousands of other demographic variables available. Because the SVI relies on ACS variables only available at the tract level, a projection model needs to applied to approximate its results using blockgroup level ACS variables. The blockgroupvulnerability dataset casts a prediction for the CDCs logic for a new contribution to the Open Environments blockgroup series available on Harvard's dataverse platform. DATA The CDC's annual SVI publication starts with 23 simple derivations using 50 ACS Census variables. Next the SVI process ranks census geographies to calculate a rank for each, where Percentile Rank = (Rank-1) / (N-1). The SVI themes are then calculated at the tract level as a percentile rank of a sum of the percentile ranks of the first level ACS derived variables. Finally, the overall ranking is taken as the sum of the theme percentile rankings. The SVI data publication is keyed by geography (7 cols) where ultimately the Census Tract FIPS code is 2 State + 3 County + 4 Tract + 2 Tract Decimals eg, 56043000301 is 56 Wyoming, 043 Washakie County, Tract 3.01 republishes Census demographics called 'adjunct variables' including area, population, households and housing units from the ACS daytime population taken from LandScan 2020 estimates derives 23 SVI variables from 50 ACS 5 Year variables with each having an estimate (E_), estimate precentage (EP_), margin of error (M_), margin percentage (MP_) and flag variable (F_) for those greater than 90% or less than 10% provides the final 4 themes and a composite SVI percentile annually vars = ['ST', 'STATE', 'ST_ABBR', 'STCNTY', 'COUNTY', 'FIPS', 'LOCATION'] +\ ['SNGPNT','LIMENG','DISABL','AGE65','AGE17','NOVEH','MUNIT','MOBILE','GROUPQ','CROWD','UNINSUR','UNEMP','POV150','NOHSDP','HBURD','TWOMORE','OTHERRACE','NHPI','MINRTY','HISP','ASIAN','AIAN','AFAM','NOINT'] +\ ['TOTAL','THEME1','THEME2','THEME3','THEME4'] + \ ['AREA_SQMI', 'TOTPOP', 'DAYPOP', 'HU', 'HH'] knowns = vars + \ # Estimates, the result of calc against ACS vars [('E_'+v) for v in vars] + \ # Flag 0,1 whether this geog is in 90 percentile rank (its vulnerable) [('F_'+v) for v in vars] +\ # Margine of error for ACS calcs [('M_'+v) for v in vars] + \ # Margine of error for ACS calcs, as percentage [('MP_'+v) for v in vars] +\ # Estimates of ACS calcs, as percentage [('EP_'+v) for v in vars] + \ # Estimated percentile ranks [('EPL_'+v) for v in vars] + \ # Sum across var percentile ranks [('SPL_'+v) for v in vars]+ \ # Percentile rank of the sum of percentile ranks [('RPL_'+v) for v in vars] [c for c in svitract.columns if c not in knowns] The SVI themes range over [0,1] but the CDC uses -999 as an NA value; this is set for ~800 or 1% of tracts which have no total poulation. The themes are numbered: Socioeconomic Status – RPL_THEME1 Household Characteristics – RPL_THEME2 Racial & Ethnic Minority Status – RPL_THEME3 Housing Type & Transportation – RPL_THEME4 The themes with their variables and ACS sources are as follows: Unlike Census data, the CDC ranks Puerto Rico and Tribal tracts separately from the US otherwise. Theme SVI Variable ACS Table ACS Variables Socioeconomic E_UNINSUR S2701 S2701_C04_001E Socioeconomic E_UNEMP DP03 DP03_0005E Socioeconomic E_POV150 S1701 S1701_C01_040E Socioeconomic E_NOHSDP B06009 B06009_002E Socioeconomic E_HBURD S2503 S2503_C01_028E + S2503_C01_032E + S2503_C01_036E + S2503_C01_040E Household E_SNGPNT B11012 B11012_010E + B11012_015E Household E_LIMENG B16005 B16005_007E + B16005_008E + B16005_012E + B16005_013E + B16005_017E + B16005_018E + B16005_022E + B16005_023E + B16005_029E + B16005_030E + B16005_034E + B16005_035E + B16005_039E + B16005_040E + B16005_044E + B16005_045E Household E_DISABL DP02 DP02_0072E Household E_AGE65 S0101 S0101_C01_030E Household E_AGE17 B09001 B09001_001E Racial & Ethnic E_TWOMORE DP05 DP05_0083E Racial & Ethnic E_OTHERRACE DP05 DP05_0082E Racial & Ethnic E_NHPI DP05 DP05_0081E Racial & Ethnic E_MINRTY DP05 DP05_0071E + DP05_0078E + DP05_0079E + DP05_0080E + DP05_0081E + DP05_0082E + ... Visit https://dataone.org/datasets/sha256%3A3edd5defce2f25c7501953ca3e77c4f15a8c71251352373a328794f961755c1c for complete metadata about this dataset.

Blocks are typically bounded by streets, roads or creeks. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be limited by other features.The Census Bureau established blocks covering the entire nation for the first time in 1990.There are less number of Census Blocks within Los Angeles County in 2020 Census TIGER/Line Shapefiles, compared in 2010.UPDATED: March 2021How This Data is Created?This census geographic file was downloaded from Census Bureau website: https://www2.census.gov/geo/tiger/TIGER2020PL/STATE/06_CALIFORNIA/06037/ on February 2021 and customized for LA County. New data fields are added in the census blocks 2020 data and populated with city/community names, Census FIPs, LA County FIPS, 2011 Supervirorial Districts, zipcodes and some administrative boundary information such as 2012 Health Districts and 2012 Service Planning Areas are also added. Similarly, "Feat_Type" field is added and populated with water, ocean and land values. Remaining two fields "SUP21" and "Pop20" will be populated later. Note: This data includes 3 NM ocean. However, user can use a definition query to remove those. Data Fields:1. STATE (STATEFP20): State FIP, "06" for California2. COUNTY (COUNTYFP20): County FIP "037" for Los Angeles County3. CT20: (TRACTCE20): 6-digit census tract number 4. BG20: 7-digit block group number5. CB20 (BLOCKCE20): 4-digit census block number6. CTCB20: Combination of CT20 and CB207. FEAT_TYPE: Land use types such as water bodies, ocean (3 NM ocean) or land 8. FIP20: Los Angeles County FIP code9. BGFIP20: Combination of BG20 and FIP2010. CITY: Incorporated city name11. COMM: Unincorporated area community name and LA City neighborhood, also known as "CSA".12. CITYCOMM: City/Community name label13. ZCTA20: Parcel specific zipcodes14. HD12: 2012 Health District number15. HD_NAME: Health District name16. SPA12: 2012 Service Planning Area number17. SPA_NAME: Service Planning Area name18. SUP11: 2011 Supervisorial District number19. SUP_LABEL: Supervisorial District label20. SUP21: Supervisorial District 2021 (wil be populated later)21. POP20: 2020 Population (to be populated later)

Abstract (en): This data collection contains FIPS codes for state, county, county subdivision, and place, along with the 1990 Census tract number for each side of the street for the urban cores of 550 counties in the United States. Street names, including prefix and/or suffix direction (north, southeast, etc.) and street type (avenue, lane, etc.) are provided, as well as the address range for that portion of the street located within a particular Census tract and the corresponding Census tract number. The FIPS county subdivision and place codes can be used to determine the correct Census tract number when streets with identical names and ranges exist in different parts of the same county. Contiguous block segments that have consecutive address ranges along a street and that have the same geographic codes (state, county, Census tract, county subdivision, and place) have been collapsed together and are represented by a single record with a single address range. 2006-01-12 All files were removed from dataset 551 and flagged as study-level files, so that they will accompany all downloads. (1) Due to the number of files in this collection, parts have been eliminated here. For a complete list of individual part names designated by state and county, consult the ICPSR Website. (2) There are two types of records in this collection, distinguished by the first character of each record. A "0" indicates a street name/address range record that can be used to find the Census tract number and other geographic codes from a street name and address number. A "2" indicates a geographic code/name record that can be used to find the name of the state, county, county subdivision, and/or place from the FIPS code. The "0" records contain 18 variables and the "2" records contain 10 variables.

The property level flood risk statistics generated by the First Street Foundation Flood Model Version 2.0 come in CSV format.

The data that is included in the CSV includes:

An FSID; a First Street ID (FSID) is a unique identifier assigned to each location.

The latitude and longitude of a parcel as well as the zip code, census block group, census tract, county, congressional district, and state of a given parcel.

The property’s Flood Factor as well as data on economic loss.

The flood depth in centimeters at the low, medium, and high CMIP 4.5 climate scenarios for the 2, 5, 20, 100, and 500 year storms this year and in 30 years.

Data on the cumulative probability of a flood event exceeding the 0cm, 15cm, and 30cm threshold depth is provided at the low, medium, and high climate scenarios for this year and in 30 years.

Information on historical events and flood adaptation, such as ID and name.

This dataset includes First Street's aggregated flood risk summary statistics. The data is available in CSV format and is aggregated at the congressional district, county, and zip code level. The data allows you to compare FSF data with FEMA data. You can also view aggregated flood risk statistics for various modeled return periods (5-, 100-, and 500-year) and see how risk changes due to climate change (compare FSF 2020 and 2050 data). There are various Flood Factor risk score aggregations available including the average risk score for all properties (flood factor risk scores 1-10) and the average risk score for properties with risk (i.e. flood factor risk scores of 2 or greater). This is version 2.0 of the data and it covers the 50 United States and Puerto Rico. There will be updated versions to follow.

If you are interested in acquiring First Street flood data, you can request to access the data here. More information on First Street's flood risk statistics can be found here and information on First Street's hazards can be found here.

The data dictionary for the parcel-level data is below.

Field Name

Type

Description

fsid

int

First Street ID (FSID) is a unique identifier assigned to each location

long

float

Longitude

lat

float

Latitude

zcta

int

ZIP code tabulation area as provided by the US Census Bureau

blkgrp_fips

int

US Census Block Group FIPS Code

tract_fips

int

US Census Tract FIPS Code

county_fips

int

County FIPS Code

cd_fips

int

Congressional District FIPS Code for the 116th Congress

state_fips

int

State FIPS Code

floodfactor

int

The property's Flood Factor, a numeric integer from 1-10 (where 1 = minimal and 10 = extreme) based on flooding risk to the building footprint. Flood risk is defined as a combination of cumulative risk over 30 years and flood depth. Flood depth is calculated at the lowest elevation of the building footprint (largest if more than 1 exists, or property centroid where footprint does not exist)

CS_depth_RP_YY

int

Climate Scenario (low, medium or high) by Flood depth (in cm) for the Return Period (2, 5, 20, 100 or 500) and Year (today or 30 years in the future). Today as year00 and 30 years as year30. ex: low_depth_002_year00

CS_chance_flood_YY

float

Climate Scenario (low, medium or high) by Cumulative probability (percent) of at least one flooding event that exceeds the threshold at a threshold flooding depth in cm (0, 15, 30) for the year (today or 30 years in the future). Today as year00 and 30 years as year30. ex: low_chance_00_year00

aal_YY_CS

int

The annualized economic damage estimate to the building structure from flooding by Year (today or 30 years in the future) by Climate Scenario (low, medium, high). Today as year00 and 30 years as year30. ex: aal_year00_low

hist1_id

int

A unique First Street identifier assigned to a historic storm event modeled by First Street

hist1_event

string

Short name of the modeled historic event

hist1_year

int

Year the modeled historic event occurred

hist1_depth

int

Depth (in cm) of flooding to the building from this historic event

hist2_id

int

A unique First Street identifier assigned to a historic storm event modeled by First Street

hist2_event

string

Short name of the modeled historic event

hist2_year

int

Year the modeled historic event occurred

hist2_depth

int

Depth (in cm) of flooding to the building from this historic event

adapt_id

int

A unique First Street identifier assigned to each adaptation project

adapt_name

string

Name of adaptation project

adapt_rp

int

Return period of flood event structure provides protection for when applicable

adapt_type

string

Specific flood adaptation structure type (can be one of many structures associated with a project)

fema_zone

string

Specific FEMA zone categorization of the property ex: A, AE, V. Zones beginning with "A" or "V" are inside the Special Flood Hazard Area which indicates high risk and flood insurance is required for structures with mortgages from federally regulated or insured lenders

footprint_flag

int

Statistics for the property are calculated at the centroid of the building footprint (1) or at the centroid of the parcel (0)

Abstract

A crosswalk dataset matching US ZIP codes to corresponding county codes

Documentation

The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.

**Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.

So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.

https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)

County definition

In the United States, a county is an administrative or political subdivision of a state that consists of a geographic region with specific boundaries and usually some level of governmental authority. The term "county" is used in 48 U.S. states, while Louisiana and Alaska have functionally equivalent subdivisions called parishes and boroughs, respectively.

Further reading

The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.

Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf

Contact information

Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.

Acknowledgement

This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook

This data set contains estimates of the percentage smoke detector utilization at the Census Tract level for the United States. Development of this data set is described in NIST TN 2020 (see references below). The zip file contains the data in shapefile format. Each record is a single census tract (using the 2013 Tiger files for census tracts) with associated data. Fields contained in the data set are: geoid: Geographic ID of the census tract. Format is '14000USXXYYYZZZZZZ', where XX is the FIPS code for the state, YYY is the FIPS code for the county, and ZZZZZZ is the census tract number. This field serves as a unique ID for the dataset. state: FIPS code for the state. county: FIPS code for the county. tract: Tract number. smsa: Standard Metropolitan Statistical Area as used in the American Housing Survey. PUMA: Public Use Microdata Area ID. region: Census region. dtctrs: Estimated fraction of households in the census tract with smoke detectors installed.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2020 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20: 2020 Census tractFIP21: 2020 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2020) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP21CSA: 2020 census tract with 2020 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP20_AGE_0_4: 2020 population 0 to 4 years oldPOP20_AGE_5_9: 2020 population 5 to 9 years old POP20_AGE_10_14: 2020 population 10 to 14 years old POP20_AGE_15_17: 2020 population 15 to 17 years old POP20_AGE_18_19: 2020 population 18 to 19 years old POP20_AGE_20_44: 2020 population 20 to 24 years old POP20_AGE_25_29: 2020 population 25 to 29 years old POP20_AGE_30_34: 2020 population 30 to 34 years old POP20_AGE_35_44: 2020 population 35 to 44 years old POP20_AGE_45_54: 2020 population 45 to 54 years old POP20_AGE_55_64: 2020 population 55 to 64 years old POP20_AGE_65_74: 2020 population 65 to 74 years old POP20_AGE_75_84: 2020 population 75 to 84 years old POP20_AGE_85_100: 2020 population 85 years and older POP20_WHITE: 2020 Non-Hispanic White POP20_BLACK: 2020 Non-Hispanic African AmericanPOP20_AIAN: 2020 Non-Hispanic American Indian or Alaska NativePOP20_ASIAN: 2020 Non-Hispanic Asian POP20_HNPI: 2020 Non-Hispanic Hawaiian Native or Pacific IslanderPOP20_HISPANIC: 2020 HispanicPOP20_MALE: 2020 Male POP20_FEMALE: 2020 Female POV20_WHITE: 2020 Non-Hispanic White below 100% Federal Poverty Level POV20_BLACK: 2020 Non-Hispanic African American below 100% Federal Poverty Level POV20_AIAN: 2020 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV20_ASIAN: 2020 Non-Hispanic Asian below 100% Federal Poverty Level POV20_HNPI: 2020 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV20_HISPANIC: 2020 Hispanic below 100% Federal Poverty Level POV20_TOTAL: 2020 Total population below 100% Federal Poverty Level POP20_TOTAL: 2020 Total PopulationAREA_SQMIL: Area in square milePOP20_DENSITY: Population per square mile.POV20_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2019.2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.Field Definition:STATEFP10 - 2010 Census State FIPS codesCOUNTYFP10 - 2010 Census County FIPS CodesTRACTCE10 - 2010 Census Census TractGEOID10 - "Census tract identifier; a concatenation of 2010 Census state FIPS code, county FIPS code, and census tract code"NAME10 - "2010 Census census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"NAMELSAD10 - 2010 Census translated legal/statistical area description and the census tract nameMTFCC10 - 2010 Census MAF/TIGER featture class codeFUNCSTAT10 - 2010 Census Functional Statitical CodeALAND10 - 2010 Census Area LandAWATER10 - 2010 Census Area waterINTPTLAT10 - 2010 Census Internal Point (Latitude)INTPTLON10 - 2010 Census Internal Point (Longtitude)POPULATION - Total PopulationHOUSING_UNITS - Total Housing units

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2016 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP16: 2016 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2016) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP16CSA: 2010 census tract with 2016 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP16_AGE_0_4: 2016 population 0 to 4 years oldPOP16_AGE_5_9: 2016 population 5 to 9 years old POP16_AGE_10_14: 2016 population 10 to 14 years old POP16_AGE_15_17: 2016 population 15 to 17 years old POP16_AGE_18_19: 2016 population 18 to 19 years old POP16_AGE_20_44: 2016 population 20 to 24 years old POP16_AGE_25_29: 2016 population 25 to 29 years old POP16_AGE_30_34: 2016 population 30 to 34 years old POP16_AGE_35_44: 2016 population 35 to 44 years old POP16_AGE_45_54: 2016 population 45 to 54 years old POP16_AGE_55_64: 2016 population 55 to 64 years old POP16_AGE_65_74: 2016 population 65 to 74 years old POP16_AGE_75_84: 2016 population 75 to 84 years old POP16_AGE_85_100: 2016 population 85 years and older POP16_WHITE: 2016 Non-Hispanic White POP16_BLACK: 2016 Non-Hispanic African AmericanPOP16_AIAN: 2016 Non-Hispanic American Indian or Alaska NativePOP16_ASIAN: 2016 Non-Hispanic Asian POP16_HNPI: 2016 Non-Hispanic Hawaiian Native or Pacific IslanderPOP16_HISPANIC: 2016 HispanicPOP16_MALE: 2016 Male POP16_FEMALE: 2016 Female POV16_WHITE: 2016 Non-Hispanic White below 100% Federal Poverty Level POV16_BLACK: 2016 Non-Hispanic African American below 100% Federal Poverty Level POV16_AIAN: 2016 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV16_ASIAN: 2016 Non-Hispanic Asian below 100% Federal Poverty Level POV16_HNPI: 2016 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV16_HISPANIC: 2016 Hispanic below 100% Federal Poverty Level POV16_TOTAL: 2016 Total population below 100% Federal Poverty Level POP16_TOTAL: 2016 Total PopulationAREA_SQMIL: Area in square milePOP16_DENSITY: Population per square mile.POV16_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2016. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

Field Definition:GEOID - "Census tract identifier; a concatenation of 2020 Census state FIPS code, county FIPS code, and census tract code"NAMELSAD - Census translated legal/statistical area description and the census tract nameALAND - Census Area LandAWATER - Census Area waterINTPTLAT - Census Internal Point (Latitude)INTPTLON - Census Internal Point (Longitude)NAME20 - "2020 Census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"POPULATION - Total PopulationP18PLUS - Population 18 years and olderHHPOP - Household PopulationGQ - Group Quarters PopulationHOUSING - Total Housing unitsOCCUNITS - Occupied Housing Units (Households)VACUNITS - Vacant Housing UnitsVACRATE -Vacancy RateHISPANIC - Hispanic or Latino NH_WHT - Not Hispanic or Latino, White alone NH_BLK - Not Hispanic or Latino, Black or African American alone NH_IND - Not Hispanic or Latino, American Indian and Alaska Native aloneNH_ASN - Not Hispanic or Latino, Asian aloneNH_HWN - Not Hispanic or Latino, Native Hawaiian and Other Pacific Islander alone NH_OTH - Not Hispanic or Latino, Some Other Race alone NH_TWO - Not Hispanic or Latino, Population of two or more races

An ESRI Shapefile for use in GIS software that contains data from the 2010 US Census for Alaska at the census tract level. Each geographic unit is identified using Federal Information Processing Standards (FIPS) numbers. Coordinate System: North American Datum 1983 Alaska Albers. Data available from the Alaska Department of Labor and Workforce Development, Research and Analysis Section.

This layer contains a Vermont-only subset of block group level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, and BLOCK.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block group level, since this data has been protected using differential privacy.*VCGI exported a Vermont-only subset of the nation-wide layer to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract BLKGRP: Block Group AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLAT: Internal Point (Latitude) INTPTLON: Internal Point (Longitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual block groups will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

The RAND Center for Population Health and Health Disparities (CPHHD) Data Core Series is composed of a wide selection of analytical measures, encompassing a variety of domains, all derived from a number of disparate data sources. The CPHHD Data Core's central focus is on geographic measures for census tracts, counties, and Metropolitan Statistical Areas (MSAs) from two distinct geo-reference points, 1990 and 2000. The current study, Decennial Census Abridged, has two cross-sectional datasets, one longitudinal (interpolated) dataset, and one longitudinal (extrapolated) dataset containing a large number and variety of population and housing characteristics-related measures. These data are summarized at five different geographic levels: tract, county (FIPS), county (Geographic), MSA (Geographic), and state. The following types of measures constructed from the Census Bureau Population and Housing Characteristics data are included in the data for this collection: housing characteristics (stock, quality, ownership, costs, expenditures, occupancy, etc.), crowding (housing and population density), urbanicity, racial and ethnic composition, language, nationality, and citizenship. Further measures cover family/household structure, transportation, educational attainment, labor force, employment status, disabilities, income, poverty, and demographics (e.g., age, gender, and race).