This viewer contains data directly from the U.S. Census Bureau. Use this map viewer to identify 2020 Census tract, block group, or block at a location. Map is centered on the City of Long Beach and shows the City boundary as recorded in the Census incorporated places layer. Data source: https://www.census.gov/data/developers/data-sets/TIGERweb-map-service.htmlAbout Census Tracts: https://www.census.gov/programs-surveys/geography/about/glossary.html#par_textimage_13About Census Block Groups: https://www.census.gov/programs-surveys/geography/about/glossary.html#par_textimage_4About Census Blocks: https://www.census.gov/programs-surveys/geography/about/glossary.html#par_textimage_5

Census geographic areas are used by the Census Bureau to collect, tabulate, and aggregate decennial census data, and are also used in more frequent demographics reports like the annual American Community Survey (ACS). Three levels of areal geography are available from MassGIS (with layer name in parentheses): Blocks, Block Groups, and TractsSee the datalayer metadata for full details.Map service also available.

The United States Census Bureau publishes geographic units used for tabulation of the 2020 Census population data in the 2020 TIGER/Line Shapefile. The geographic units, which remain constant throughout the decade, include counties, census tracts, block groups, and blocks. Fields have been added so data formatted or published by the council can be joined to the shapefile for analysis. Each Shapefile (.shp) is in a compressed file (.zip) format. Blocks.zip - Census Blocks BlockGroups.zip - Block Groups Tracts.zip - Census Tracts Counties.zip - Counties Cities.zip - Census Places (Cities) CDPs.zip - Census Designated Places Each 'Pop' file contains the 2020 Census population for the corresponding geographic level. BlocksPop.zip - Census Blocks 2020 Census Population BlockGroupPop.zip - Census Block Groups 2020 Census Population TractsPop.zip - Census Tracts 2020 Census Population CountiesPop.zip - Counties 2020 Census Population

2019 US Census All Counties and County Equivalents geospatial data

U.S. Census Bureau; TIGER/Line Shapefiles 2019 Data accessed from: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2019.html

TIGER/Line Shapefiles do not include demographic data, but they do contain geographic entity codes (GEOIDs) that can be linked to the Census Bureau’s demographic data.

The Geographic Areas Reference Manual (GARM) describes in great detail the basic geographic entities the Census Bureau uses (https://www.census.gov/programs-surveys/acs/geography-acs.html).

TIGER Data Products Guide (https://www.census.gov/programs-surveys/geography/guidance/tiger-data-products-guide.html)

The Census Bureau (https://www.census.gov/) maintains census tract geographic boundaries for the analysis and mapping of demographic information across the United States. Every 10 years the Census Bureau provides opportunity to local government to review and update statistical areas boundary including census tract geography through Participants Statistical Areas Program (PSAP). Los Angeles County actively participated in PSAP program of 2010 and 2020 census and submit the update of census tract boundaries. There are little more Census Tracts within Los Angeles County in 2020 Census TIGER/Line Shapefiles, compared to 2010. The Census Bureau releases the results of census counts at different census geography including census tracts. This web map is crated to visualize the similarities and differences between Los Angeles County's 2010 and 2020 census tracts.

This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This API returns the geographies specified by a geography name (e.g., Washington) of a specific geography type (e.g., congressional district) within the entire United States.

The 2020 TIGER/Line Shapefiles contain current geographic extent and boundaries of both legal and statistical entities (which have no governmental standing) for the United States, the District of Columbia, Puerto Rico, and the Island areas. This vintage includes boundaries of governmental units that match the data from the surveys that use 2020 geography (e.g., 2020 Population Estimates and the 2020 American Community Survey). In addition to geographic boundaries, the 2020 TIGER/Line Shapefiles also include geographic feature shapefiles and relationship files. Feature shapefiles represent the point, line and polygon features in the MTDB (e.g., roads and rivers). Relationship files contain additional attribute information users can join to the shapefiles. Both the feature shapefiles and relationship files reflect updates made in the database through September 2020. To see how the geographic entities, relate to one another, please see our geographic hierarchy diagrams here.Census Urbanized Areashttps://www2.census.gov/geo/tiger/TIGER2020/UACCensus Urban/Rural Census Block Shapefileshttps://www.census.gov/cgi-bin/geo/shapefiles/index.php2020 TIGER/Line and Redistricting shapefiles:https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2020.htmlTechnical documentation:https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc.pdfTIGERweb REST Services:https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_restmapservice.htmlTIGERweb WMS Services:https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_wms.htmlThe legal entities included in these shapefiles are:American Indian Off-Reservation Trust LandsAmerican Indian Reservations – FederalAmerican Indian Reservations – StateAmerican Indian Tribal Subdivisions (within legal American Indian areas)Alaska Native Regional CorporationsCongressional Districts – 116th CongressConsolidated CitiesCounties and Equivalent Entities (except census areas in Alaska)Estates (US Virgin Islands only)Hawaiian Home LandsIncorporated PlacesMinor Civil DivisionsSchool Districts – ElementarySchool Districts – SecondarySchool Districts – UnifiedStates and Equivalent EntitiesState Legislative Districts – UpperState Legislative Districts – LowerSubminor Civil Divisions (Subbarrios in Puerto Rico)The statistical entities included in these shapefiles are:Alaska Native Village Statistical AreasAmerican Indian/Alaska Native Statistical AreasAmerican Indian Tribal Subdivisions (within Oklahoma Tribal Statistical Areas)Block Groups3-5Census AreasCensus BlocksCensus County Divisions (Census Subareas in Alaska)Unorganized Territories (statistical county subdivisions)Census Designated Places (CDPs)Census TractsCombined New England City and Town AreasCombined Statistical AreasMetropolitan and Micropolitan Statistical Areas and related statistical areasMetropolitan DivisionsNew England City and Town AreasNew England City and Town Area DivisionsOklahoma Tribal Statistical AreasPublic Use Microdata Areas (PUMAs)State Designated Tribal Statistical AreasTribal Designated Statistical AreasUrban AreasZIP Code Tabulation Areas (ZCTAs)Shapefiles - Features:Address Range-FeatureAll Lines (called Edges)All RoadsArea HydrographyArea LandmarkCoastlineLinear HydrographyMilitary InstallationPoint LandmarkPrimary RoadsPrimary and Secondary RoadsTopological Faces (polygons with all geocodes)Relationship Files:Address Range-Feature NameAddress RangesFeature NamesTopological Faces – Area LandmarkTopological Faces – Area HydrographyTopological Faces – Military Installations

This resource is a member of a series. 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. 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 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.

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. 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 2010 Census and beyond, 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.

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 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 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.

A. SUMMARY Census blocks, the smallest geographic area for which the Bureau of the Census collects and tabulates decennial census data, are formed by streets, roads, railroads, streams and other bodies of water, other visible physical and cultural features, and the legal boundaries shown on Census Bureau maps. More information on the census tracts can be found here.

B. HOW THE DATASET IS CREATED The boundaries are uploaded from TIGER/Line shapefiles provided by the U.S. Census Bureau.

C. UPDATE PROCESS This dataset is static. Changes to the census blocks are tracked in multiple datasets. See here for 2000 and 2010 census tract boundaries.

D. HOW TO USE THIS DATASET This boundary file can be joined to other census datasets on GEOID. Column descriptions can be found on in the technical documentation included on the census.gov website

E. RELATED DATASETS Census 2020: Census Tracts for San Francisco Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods Census 2020: Blocks for San Francisco Clipped to SF Shoreline Census 2020: Blocks Groups for San Francisco Census 2020: Blocks Groups for San Francisco Clipped to SF Shoreline

This feature class is a compilation of the US Census Geographies (Polygons) for 1990, 2000, 2010 and 2020 at the Tract, Block Group, and Block scale for the Tahoe Basin. Each feature has been assigned a TRPAID as a unique ID, which is a combination of the Census derived GEOID and the census year. It is intended to be used in combination with the Census_Demographics table which contains downloaded census data that can be joined using TRPAID

A Block Group usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within the census tract. Within the standard census geography hierarchy, BGs never cross state, county, or census tract boundaries but may cross the boundaries of any other geographic entity. There are little more number of Census Block Groups within Los Angeles County in 2020 Census TIGER/Line Shapefiles, compared in 2010.BGs are generally define to contain between 600 to 3,000 people and 240 and 1,200 housing units. BGs are the smallest geographic unit for which the Census Bureau tabulates sample data. Created/Updated: Updated on September 2023, to merged Long Beach Breakwater land-based block group silver polygons into bigger block group 9903000 as per 2022 TIGER Line Shapefiles, and to update Santa Catalina Islands and San Clemente Islands block group boundary based on DPW City boundaries (except 5990002 tract in Avalon). Updated on Sep 2022 and Dec 2022, to align tract boundary along city boundaries.Created on March 2021.How This Data is Created? This 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. Data Fields:1. BG20 (BLKGRPCE20): 7 digit census tracts and block group number, 2. CT20 (TRACTCE20): 6-digit census tract number, 3. Label (NAMELSAD20): Block group number label

The Census data utilized for developing the Community Layer used 2010 TIGER/Line shapefile datasets (TIGER = Topologically Integrated Geographic Encoding and Referencing). TIGER/Line shapefiles are available for free download from the US Census Bureau and include various legal and statistical geographic areas for which the Census tabulates data. The shapefiles are designed to be used in a GIS environment, with the ability to directly link the geographic areas to Census data via a unique GEOID number.The following TIGER/Line datasets should be used: - Counties and Equivalent Entities –primary legal divisions within each state (counties, parishes, etc)- County Subdivisions –includes both legal areas (Minor Civil Divisions or MCDs) and various statistical areas- Places –includes both legal areas (Incorporated Places) and statistical areas (Census Designated Places or CDPs)- Blocks –the smallest geographical area for which Census population counts are recorded; blocks never cross boundaries of any entity for which the Census Bureau tabulates data, including counties, county subdivisions, places, and American Indian, Alaska Native, and Native Hawaiian (AIANNH) areas- American Indian, Alaska Native, and Native Hawaiian (AIANNH) AreasExtracting and Formatting CIS DataA key component of the community layer is the ability to link CIS information spatially. Data from CIS cannot directly be joined with Census data. The two datasets have community name discrepancies which impede an exact match. Therefore, CIS data needs to be formatted to match Census community names. A custom report can be obtained from CIS to include a CID number, Community Name, County, State, Community Status, and Tribal status for all CIS records. Make sure all CID numbers are six digits and you follow the CIS community naming convention outlined in Table 4.2.1.1 in the Community Layer Update Technical Guide 20131206. Converting the CIS name“ADDISON, VILLAGE OF” to “ADDISON TOWN”involves removing unneeded spaces, comma, and preposition to make the join successful to the Census data. Using a comprehensive report at a national level gains efficiencies as bulk edits can be made. Data for each state should be extracted as needed by separating the CIS data into each type of community corresponding to the Census geography layers used, and a new JoinID column (e.g. ADDISON TOWN) can be created for each dataset allowing the CIS data to be joined to the Census data.

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.

The Lawrence Group, under contract with Metropolitan Council, created a 2000 Census Bureau block polygon dataset for the Twin Cities Metropolitan Area (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington Counties). This dataset is coincident with and developed using the TLG Street Centerline and Landmarks databases where 2000 block boundaries fall on those features. For those block boundaries that are defined by features not included in TLG databases, TLG used other digital resources to generate these boundaries, such as orthophotography or additional features from city and county GIS databases. TLG used it's best judgement to digitize block boundaries when the block boundaries followed nonvisible features or street extensions.

A. SUMMARY Census Block groups are the next level above census blocks in the geographic hierarchy. Block groups are a combination of census blocks that is a subdivision of a census tract.A block group consists of all census blocks whose numbers begin with the same digit in a given census tract; for example, block group 3 includes all census blocks numbered in the 300s. More information on the census tracts can be found here.

B. HOW THE DATASET IS CREATED The boundaries are uploaded from TIGER/Line shapefiles provided by the U.S. Census Bureau.

C. UPDATE PROCESS This dataset is static. Changes to the census blocks are tracked in multiple datasets. See here for 2000 census tract boundaries.

D. HOW TO USE THIS DATASET This boundary file can be joined to other census datasets on GEOID. Column descriptions can be found on in the technical documentation included on the census.gov website

E. RELATED DATASETS Census 2020: Census Tracts for San Francisco Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods Census 2020: Blocks for San Francisco Census 2020: Blocks for San Francisco Clipped to SF Shoreline Census 2020: Blocks Groups for San Francisco Clipped to SF Shoreline

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.