4 datasets found
  1. l

    2020 Census Blocks

    • geohub.lacity.org
    • data.lacounty.gov
    • +2more
    Updated Mar 22, 2021
    + more versions
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    County of Los Angeles (2021). 2020 Census Blocks [Dataset]. https://geohub.lacity.org/items/8a29319474fe44bb96152d0be8e778af
    Explore at:
    Dataset updated
    Mar 22, 2021
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    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:1. June 2023: This update includes 2022 November Santa Clarita City annexation and the addition of "Kinneloa Mesa" community (was a part of unincorporated East Pasadena). Added new data fields FIP_CURRENT to CITYCOMM_CURRENT to reflect new/updated city and communities. Updated city/community names and FIP codes of census blocks that are in 2022 November Santa Clarita City annexation and new Kinneloa Mesa community (look for FIP_Current, City_Current, Comm_Current field values)2. February 2023: Updated few Census Block CSA values based on Demographic Consultant inquiry/suggestions3. April 2022: Updated Census Block data attribute values based on Supervisorial District 2021, Service Planning Area 2022, Health District 2022 and ZIP Code Tabulation Area 2020Created: 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, LA County FIPS, 2021 Supervisorial Districts, 2020 Census Zip Code Tabulation Area (ZCTA) and some administrative boundary information such as 2022 Health Districts and 2022 Service Planning Areas (SPS) are also added. "Housing20" field value and "Pop20" field value is populated with PL 94-171 Redistricting Data Summary File: Decennial Census P.L. 94-171 Redistricting Data Summary Files. Similarly, "Feat_Type" field is added and populated with water, ocean and land values. Five new data fields (FIP_CURRENT to CITYCOMM_CURRENT) are added in June 2023 updates to accommodate 2022 Santa Clarita city annexation. City/community names and FIP codes of census blocks affected by 2022 November Santa Clarita City annexation are assigned based on the location of block centroids. In June 2023 update, total of 36 blocks assigned to the City of Santa Clarita that were in Unincorporated Valencia and Castaic. Note: This data includes 3 NM ocean (FEAT_TYPE field). However, user can use a definition query to remove those. Data Fields: 1. STATE (STATEFP20): State FIP, "06" for California, 2. COUNTY (COUNTYFP20): County FIP "037" for Los Angeles County, 3. CT20: (TRACTCE20): 6-digit census tract number, 4. BG20: 7-digit block group number, 5. CB20 (BLOCKCE20): 4-digit census block number, 6. CTCB20: Combination of CT20 and CB20, 7. FEAT_TYPE: Land use types such as water bodies, ocean (3 NM ocean) or land, 8. FIP20: Los Angeles County FIP code, 9. BGFIP20: Combination of BG20 and FIP20, 10. CITY: Incorporated city name, 11. COMM: Unincorporated area community name and LA City neighborhood, also known as "CSA", 12. CITYCOMM: City/Community name label, 13. ZCTA20: Parcel specific zip codes, 14. HD12: 2012 Health District number, 15. HD_NAME: Health District name, 16. SPA22: 2022 Service Planning Area number, 17. SPA_NAME: Service Planning Area name, 18. SUP21: 2021 Supervisorial District number, 19. SUP_LABEL: Supervisorial District label, 20. POP20: 2020 Population (PL 94-171 Redistricting Data Summary File - Total Population), 21. HOUSING20: 2020 housing (PL 94-171 Redistricting Data Summary File - Total Housing),22. FIP_CURRENT: Los Angeles County 2023 FIP code, as of June 2023,23. BG20FIP_CURRENT: Combination of BG20 and 2023 FIP, as of June 2023,24. CITY_CURRENT: 2023 Incorporated city name, as of June 2023,25. COMM_CURRENT: 2023 Unincorporated area community name and LA City neighborhood, also known as "CSA", as of June 2023,26. CITYCOMM_CURRENT: 2023 City/Community name label, as of June 2023.

  2. D

    2022 Tract-level Indicators of Potential Disadvantage

    • catalog.dvrpc.org
    • dvrpc-dvrpcgis.opendata.arcgis.com
    esri feature class +4
    Updated Feb 15, 2025
    + more versions
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    DVRPC (2025). 2022 Tract-level Indicators of Potential Disadvantage [Dataset]. https://catalog.dvrpc.org/dataset/2022-tract-level-indicators-of-potential-disadvantage
    Explore at:
    geojson, html, esri feature class, json, xmlAvailable download formats
    Dataset updated
    Feb 15, 2025
    Dataset authored and provided by
    DVRPC
    Description

    Title VI of the Civil Rights Act and the Executive Order on Environmental Justice (#12898) do not provide specific guidance to evaluate EJ issues within a region's transportation planning process. Therefore, MPOs must devise their own methods for ensuring that EJ issues are investigated and evaluated in transportation decision-making. In 2001, DVRPC developed an EJ technical assessment to identify direct and disparate impacts of its plans, programs, and planning process on defined population groups in the Delaware Valley region. This assessment, called the Indicators of Potential Disadvantage Methodology, is utilized in a variety of DVRPC plans and programs. DVRPC currently assesses the following population groups, defined by the U.S. Census Bureau:

    • Youth

    • Older Adults

    • Female

    • Racial Minority

    • Ethnic Minority

    • Foreign-Born

    • Disabled

    • Limited English Proficiency

    • Low-Income

    Census tables used to gather data from the 2018-2022 American Community Survey 5-Year Estimates

    Using U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group.

    Census tables used to gather data from the 2018-2022 American Community Survey 5-Year Estimates.

    For more information and for methodology, visit DVRPC's website:http://www.dvrpc.org/GetInvolved/TitleVI/

    For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipd

    Source of tract boundaries: 2020 US Census Bureau, TIGER/Line Shapefiles

    Note: Tracts with null values should be symbolized as "Insufficient or No Data".

    Data Dictionary for Attributes:

    (Source = DVRPC indicates a calculated field)

    Field

    Alias

    Description

    Source

    year

    IPD analysis year

    DVRPC

    geoid20

    11-digit tract GEOID

    Census tract identifier

    ACS 5-year

    statefp

    2-digit state GEOID

    FIPS Code for State

    ACS 5-year

    countyfp

    3-digit county GEOID

    FIPS Code for County

    ACS 5-year

    tractce

    Tract number

    Tract Number

    ACS 5-year

    name

    Tract number

    Census tract identifier with decimal places

    ACS 5-year

    namelsad

    Tract name

    Census tract name with decimal places

    ACS 5-year

    d_class

    Disabled percentile class

    Classification of tract's disabled percentage as: well below average, below average, average, above average, or well above average

    calculated

    d_est

    Disabled count estimate

    Estimated count of disabled population

    ACS 5-year

    d_est_moe

    Disabled count margin of error

    Margin of error for estimated count of disabled population

    ACS 5-year

    d_pct

    Disabled percent estimate

    Estimated percentage of disabled population

    ACS 5-year

    d_pct_moe

    Disabled percent margin of error

    Margin of error for percentage of disabled population

    ACS 5-year

    d_pctile

    Disabled percentile

    Tract's regional percentile for percentage disabled

    calculated

    d_score

    Disabled percentile score

    Corresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4

    calculated

    em_class

    Ethnic minority percentile class

    Classification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above average

    calculated

    em_est

    Ethnic minority count estimate

    Estimated count of Hispanic/Latino population

    ACS 5-year

    em_est_moe

    Ethnic minority count margin of error

    Margin of error for estimated count of Hispanic/Latino population

    ACS 5-year

    em_pct

    Ethnic minority percent estimate

    Estimated percentage of Hispanic/Latino population

    calculated

    <p style='margin:0 0 0

  3. w

    County, City and Township (CTU) Lookup Table

    • data.wu.ac.at
    • gisdata.mn.gov
    fgdb, html, jpeg, shp
    Updated Jul 12, 2018
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    Metropolitan Council (2018). County, City and Township (CTU) Lookup Table [Dataset]. https://data.wu.ac.at/schema/gisdata_mn_gov/Mzk2NmRkMzMtOTljYy00ODMxLWI3ZmYtZTI2MTkzZTMxZmJm
    Explore at:
    fgdb, html, shp, jpegAvailable download formats
    Dataset updated
    Jul 12, 2018
    Dataset provided by
    Metropolitan Council
    Area covered
    06972c7d643ebd01ef97b2d6d234b1bdeab504b1
    Description

    This is a lookup table containing various data related to cities, townships, unorganized territories (CTUs) and any divisions created by county boundaries splitting them. These are termed Minor Civil Division (MCDs) by the Census Bureau. The table encompases the Twin Cities 7-county metropolitan area. It is intended to be a Council wide master lookup table for these entites. It contains official federal and state unique identifiers for CTUs and MCDs as well as identifiers created and used by other organizations. The table also contains historical MCDs dating back to the 1990s and a few other non-MCD records that are of importance to Met. Council use of this table.

    The County CTU Lookup Table relates to the Counties and Cities & Townships, Twin Cities Metropolitan Area dataset here: https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-metro-counties-and-ctus

    NOTES:

    - On 5/28/2014 a new field was added to reflect the new community designations defined in the Council's Thrive MSP 2040 regional plan - COMDES2040

    - On 3/17/2011 it was discovered that the CTU ID used for the City of Lake St. Croix Beach was incorrect. It was changed from 2394379 to 2395599 to match GNIS.

    - On 3/17/2011 it was discovered that the CTU ID used for the City of Lilydale was incorrect. It was changed from 2394457 to 2395708 to match GNIS.

    - On 11/9/2010 it was discovered that the CTU ID used for the City of Crystal was incorrect. It was changed from 2393541 to 2393683 to match GNIS.

    - Effective April 2008, a change was made in GNIS to match the FIPS place codes to the "civil" feature for each city instead of the "populated place" feature. Both cities and townships are now "civil" features within GNIS. This means that the official GNIS unique ID for every city in Minnesota has changed.

    - As of January 1, 2006, the five digit FIPS 55-3 Place codes that were used as unique identifiers in this dataset (CTU_CODE and COCTU_CODE fields) were officially retired by the Federal governement. They are replaced by a set of integer codes from the Geographic Names Information System (GNIS_CODE field). Both codes will be kept in this database, but the GNIS_CODE is considered the official unique identifier from this point forward. The GNIS codes are also slated to become official ANSI codes for these geographic features. While GNIS treats these codes as 6 to 8 digit integer data types, the Census Bureau formats them as 8 digit text fields, right justified with leading zeros included.

    - The Census Bureau will continue to create FIPS 55 Place codes for new cities and townships through the 2010 Census. After that, no new FIPS 55 codes will be created. Note that for townships that wholly incorporate into cities, the same FIPS 55 code will be used for the new city. (GNIS creates a new ID for the new city.)

    - Cities and townships have also been referred to as ''MCDs'' (a Census term), however this term technically refers to the part of each city or township within a single county. Thus, a few cities in the metro area that are split by county boundaries are actually comprised of two different MCDs. This was part of the impetus for a proposed MN state data standard that uses the ''CTU'' terminology for clarity.

    - A variety of civil divisions of the land exist within the United States. In Minnesota, only three types exist - cities, townships and unorganized territories. All three of these exist within the Twin Cities seven county area. The only unorganized territory is Fort Snelling (a large portion of which is occupied by the MSP International Airport).

    - Some cities are split between two counties. Only those parts of cities within the 7-county area are included.

    - Prior to the 2000 census, the FIPS Place code for the City of Greenwood in Hennepin County was changed from 25928 to 25918. This dataset reflects that change.

  4. U.S. Heart Disease Mortality Rates 2017-2019

    • hub.arcgis.com
    Updated Jul 28, 2021
    + more versions
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    Centers for Disease Control and Prevention (2021). U.S. Heart Disease Mortality Rates 2017-2019 [Dataset]. https://hub.arcgis.com/maps/ad21224485f049ee85808504c406c9ed_0/about
    Explore at:
    Dataset updated
    Jul 28, 2021
    Dataset authored and provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    North Pacific Ocean, Pacific Ocean
    Description

    Create maps of U.S. heart disease death rates by county. Data can be stratified by age, race/ethnicity, and sex. Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceMortality data were obtained from the National Vital Statistics System. Bridged-Race Postcensal Population Estimates were obtained from the National Center for Health Statistics. International Classification of Diseases, 10th Revision (ICD-10) codes: I00-I09, I11, I13, I20-I51; underlying cause of death.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.' Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)   RRR: 3 digits represent race/ethnicity     All - Overall     AIA - American Indian and Alaska Native, non-Hispanic     API - Asian and Pacific Islander, non-Hispanic     BLK - Black, non-Hispanic     HIS - Hispanic     WHT - White, non-Hispanic   S: 1 digit represents sex     A - All    F - Female     M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound.  Example: The column 'BLK_M_65UP' displays rates per 100,000 black men aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 100,000 population. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria: At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

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County of Los Angeles (2021). 2020 Census Blocks [Dataset]. https://geohub.lacity.org/items/8a29319474fe44bb96152d0be8e778af

2020 Census Blocks

Explore at:
39 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 22, 2021
Dataset authored and provided by
County of Los Angeles
Area covered
Description

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:1. June 2023: This update includes 2022 November Santa Clarita City annexation and the addition of "Kinneloa Mesa" community (was a part of unincorporated East Pasadena). Added new data fields FIP_CURRENT to CITYCOMM_CURRENT to reflect new/updated city and communities. Updated city/community names and FIP codes of census blocks that are in 2022 November Santa Clarita City annexation and new Kinneloa Mesa community (look for FIP_Current, City_Current, Comm_Current field values)2. February 2023: Updated few Census Block CSA values based on Demographic Consultant inquiry/suggestions3. April 2022: Updated Census Block data attribute values based on Supervisorial District 2021, Service Planning Area 2022, Health District 2022 and ZIP Code Tabulation Area 2020Created: 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, LA County FIPS, 2021 Supervisorial Districts, 2020 Census Zip Code Tabulation Area (ZCTA) and some administrative boundary information such as 2022 Health Districts and 2022 Service Planning Areas (SPS) are also added. "Housing20" field value and "Pop20" field value is populated with PL 94-171 Redistricting Data Summary File: Decennial Census P.L. 94-171 Redistricting Data Summary Files. Similarly, "Feat_Type" field is added and populated with water, ocean and land values. Five new data fields (FIP_CURRENT to CITYCOMM_CURRENT) are added in June 2023 updates to accommodate 2022 Santa Clarita city annexation. City/community names and FIP codes of census blocks affected by 2022 November Santa Clarita City annexation are assigned based on the location of block centroids. In June 2023 update, total of 36 blocks assigned to the City of Santa Clarita that were in Unincorporated Valencia and Castaic. Note: This data includes 3 NM ocean (FEAT_TYPE field). However, user can use a definition query to remove those. Data Fields: 1. STATE (STATEFP20): State FIP, "06" for California, 2. COUNTY (COUNTYFP20): County FIP "037" for Los Angeles County, 3. CT20: (TRACTCE20): 6-digit census tract number, 4. BG20: 7-digit block group number, 5. CB20 (BLOCKCE20): 4-digit census block number, 6. CTCB20: Combination of CT20 and CB20, 7. FEAT_TYPE: Land use types such as water bodies, ocean (3 NM ocean) or land, 8. FIP20: Los Angeles County FIP code, 9. BGFIP20: Combination of BG20 and FIP20, 10. CITY: Incorporated city name, 11. COMM: Unincorporated area community name and LA City neighborhood, also known as "CSA", 12. CITYCOMM: City/Community name label, 13. ZCTA20: Parcel specific zip codes, 14. HD12: 2012 Health District number, 15. HD_NAME: Health District name, 16. SPA22: 2022 Service Planning Area number, 17. SPA_NAME: Service Planning Area name, 18. SUP21: 2021 Supervisorial District number, 19. SUP_LABEL: Supervisorial District label, 20. POP20: 2020 Population (PL 94-171 Redistricting Data Summary File - Total Population), 21. HOUSING20: 2020 housing (PL 94-171 Redistricting Data Summary File - Total Housing),22. FIP_CURRENT: Los Angeles County 2023 FIP code, as of June 2023,23. BG20FIP_CURRENT: Combination of BG20 and 2023 FIP, as of June 2023,24. CITY_CURRENT: 2023 Incorporated city name, as of June 2023,25. COMM_CURRENT: 2023 Unincorporated area community name and LA City neighborhood, also known as "CSA", as of June 2023,26. CITYCOMM_CURRENT: 2023 City/Community name label, as of June 2023.

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