20221216103949001.0FALSEE2_CENACS_2021_CCIArcSDE Connection00252654.870800793966.09940062264.122900781564.7609001ProjectedGCS_North_American_1983_HARNLinear Unit: Meter (1.000000)NAD_1983_HARN_Florida_GDL_Albers<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.8'><WKT>PROJCS["NAD_1983_HARN_Florida_GDL_Albers",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",400000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-84.0],PARAMETER["Standard_Parallel_1",24.0],PARAMETER["Standard_Parallel_2",31.5],PARAMETER["Latitude_Of_Origin",24.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3087]]</WKT><XOrigin>-19550100</XOrigin><YOrigin>-7526400</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3087</WKID><LatestWKID>3087</LatestWKID></ProjectedCoordinateSystem>202301270937070020230127093707005000005000FGDCdatasetU.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch301-763-1128301-763-47104600 Silver Hill Road, Stop 7400WashingtonD.C.20233-7400USgeo.tiger@census.gov20230127ArcGIS Metadata1.0Florida Geographic Data Library (FGDL)431 Architecture PO Box 115706GainesvilleFlorida32611-5706USMailing list for FGDL: http://www.fgdl.org/fgdl-l.htmlFor FGDL Software: http://www.fgdl.org/software.htmlWeb site: http://www.fgdl.orgTechnical Support: http://www.fgdl.org/fgdlfeed.htmlFGDL Frequently Asked Questions: http://www.fgdl.org/fgdlfaq.htmlVector Digital Data Set (Polygon)DOWNLOADABLE DATAwithheldSDE Feature Class2020 Census Block Groups in Florida (With Selected Fields From the 2017-2021 American Community Survey) - Erase 22023-01-26T00:00:00U.S. Census BureauU.S. Census BureauWashington, DCVector Digital Data Set (Polygon)State of Florida<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This dataset contains the US Census Bureau 2020 Census Block Groups erased with Census Blocks with 2 or less people, for the State of Florida with selected fields from the 2017-2021 American Community Survey (ACS). Some of the fields included in this dataset are total population, education, and housing and economic characteristics. This data is at the block group level. The ACS was designed to replace the long-form of the decennial census. The ACS is a survey that releases data annually. ACS data are survey estimates distributed for 1-, 3-, and 5-year time periods. The 5-year estimates are the only time period estimates that provide data at the block group level. This data is designed for use within the Florida Department of Transportation Efficient Transportation Decision Making Process (ETDM). However, the subset of ACS fields included herein is useful for a variety of applications and uses.</SPAN></P></DIV></DIV></DIV>For the research and analysis of the 2017-2021 American Community Survey (ACS) at the Census Block Group geography level. The data contains selected fields from the 2017-2021 ACS. Census Block Groups are geographic entities made up of Census Blocks and that are contained within the same Census Tract. Block Groups generally contain between 600 and 3,000 people, with an optimum size of 1,500 people.U.S. Census Bureau(301) 763-4039(301) 763-43484600 Silver Hill Road, Stop 7400Washington, D.C.20233-7400UShttp://www.census.gov/Floridablock groupISO 19115 Topic CategorysocioeconomiceducationhousingpopulationeconomicISO 19115 Topic CategoryboundariessocietysocioeconomiceducationhousingboundariesFloridablock grouppopulationsocietyeconomicThe Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. The University of Florida GeoPlan Center makes no warranties, guaranties or representations as to the truth, accuracy or completeness of the data provided by the data sources. The University of Florida GeoPlan Center makes no representations or warranties about the quality or suitability of the materials, either expressly or implied, including but not limited to any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The University of Florida GeoPlan Center shall not be liable for any damages suffered as a result of using, modifying, contributing or distributing the materials. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. The University of Florida GeoPlan Center makes no warranties, guaranties or representations as to the truth, accuracy or completeness of the data provided by the data sources. The University of Florida GeoPlan Center makes no representations or warranties about the quality or suitability of the materials, either expressly or implied, including but not limited to any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The University of Florida GeoPlan Center shall not be liable for any damages suffered as a result of using, modifying, contributing or distributing the materials. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html</SPAN></P></DIV></DIV></DIV>Additional documentation can be found here: https://www.census.gov/programs-surveys/acs/technical-documentation/pums/documentation.htmlEsri ArcGIS 13.0.3.36057-87.639356-79.81221524.35469331.042641publication date2017-01-01T00:00:002021-12-31T00:00:001-87.639351-79.87251531.04247924.505905This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topologyThis data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topologyThis data is provided 'as is' by GeoPlan and is complete to our knowledge.GeoPlan relied on the integrity of the attribute information within the original data.This data is provided 'as is' and its horizontal positional accuracy has not been verified by GeoPlanThis data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlanSpatial and Attribute Information100000The 2020 TIGER line files were downloaded from the following site: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html. date downloaded 8/25/21. The data was projected to Albers HPGN. The American Community Survey data was downloaded from the Census Bureau in dat format from: https://www2.census.gov/programs-surveys/acs/summary_file/2020/prototype/5YRData/. date downloaded: 4/14/22. Changed name from tlgdb_2020_a_12_fl.gdb\Block_Group to CENACS_2020. A variety of GIS techniques including python scripting were used to download, parse, aggregate, and join the tabular demographic data to the spatial data. The result is a feature class with logically named fields that are made up of one or more census fields2023-01-26T00:00:00GeoPlanexternal786dcbb2ef2a12674391f92d21d5616b2e69f87eUniversity of Florida GeoPlan CenterTrueUniversity of Florida GeoPlan CenterErase 2020 Census blocks with 2 or less people from CENACS_2020.2023-01-26T00:00:00University of Florida GeoPlan CenterGainesvilleFL32611352-392-8686University of Florida GeoPlan Center13312EPSG6.13(9.2.0)E2_CENACS_2021_CCICENACS_2021U.S. Census BureauFeature Class13312GEOID20GEOID20String1200Block identifier; a concatenation of Census state Federal Information Processing Standards (FIPS) code, county FIPS code, census tract code, census block group codeNAMELSADNAMELSADString1300Census translated legal/statistical area description and the block group numberALANDALANDDouble8388Census land area (square meters)AWATERAWATERDouble8388Census water area (square meters)INTPTLATINTPTLATString1100Census latitude of the internal pointINTPTLONINTPTLONString1200Census longitude of the internal pointOBJECTIDOBJECTIDOID4100Internal feature number.EsriSequential unique whole numbers that are automatically generated.SHAPESHAPEGeometry400Feature geometry.EsriCoordinates defining the features.ACRESACRESDouble8388AcresFILEIDFILEIDString500Census File IDSTUSABSTUSABString2002 letter state codeSUMLEVELSUMLEVELDouble8388Census geographic summary levelSTATESTATEDouble8388StateCOUNTYCOUNTYDouble8388CountyTRACTTRACTDouble8388Census TractBLKGRPBLKGRPDouble8388Census Block GroupNAMENAMEString21100Block Group NameTOTALPOPTOTALPOPInteger4100Total Population - [B01003_E001]HOUSEHOLDSHOUSEHOLDSInteger4100Total: Households (Includes Living Alone) - [B11001_E001]MALEMALEInteger4100Population Male - [B01001_E002]FEMALEFEMALEInteger4100Population Female - [B01001_E026]WHITEWHITEInteger4100Population White alone - [B02001_E002]BLACKBLACKInteger4100Population Black or African American alone - [B02001_E003]AMERI_ESAMERI_ESInteger4100Population American Indian and Alaska Native alone - [B02001_E004]ASIANASIANInteger4100Population Asian alone - [B02001_E005]HAWN_PIHAWN_PIInteger4100Population Native Hawaiian and Other Pacific Islander alone - [B02001_E006]OTHEROTHERInteger4100Population Some other race alone - [B02001_E007]MULT_RACEMULT_RACEInteger4100Population Two or more races - [B02001_E008]HISPANICHISPANICInteger4100Population Hispanic or Latino by Race - [B03002_E012]WHITE_NHWHITE_NHInteger4100Not Hispanic or Latino: White alone - [B03002_E003]HISPNC_NOTHISPNC_NOTInteger4100Total Population minus Hispanic Population - [TOTALPOP] - [HISPANIC]MINORITYMINORITYInteger4100"Minority Population" is the population that lists their racial status as a race other than white alone and-or lists their ethnicity as Hispanic or Latino. That is, all people other than non-Hispanic white-alone individuals. The word "alone" in this case indicates that the person is of a single race, not multiracial - [TOTALPOP] - [WHITE_NH]AVE_HH_SZAVE_HH_SZDouble8388Average household size Total: Average Household Size of Occupied Housing Units by Tenure - [B25010_E001]PH_TOTALPH_TOTALInteger4100Total: Household Type by Relatives and Nonrelatives for Population in Households - [B11002_E001]PH_FAMPH_FAMInteger4100Population in family households - [B11002_E002]PH_NONFAMPH_NONFAMInteger4100Population in nonfamily households - [B11002_E012]FAM_HHFAM_HHInteger4100Family households - [B11001_E002]AVE_FAM_SZAVE_FAM_SZDouble8388Average family size (Total Population In family households/Family households) - [PH_FAM]/[FAM_HH]AGE_UNDER5AGE_UNDER5Integer4100Population Under 5 years - [B01001_E003] + [B01001_E027]AGE_5_17AGE_5_17Integer4100Population 5 to 17 years - [B01001_E004] + [B01001_E028] + [B01001_E005] + [B01001_E029] + [B01001_E006] + [B01001_E030]AGE_18_21AGE_18_21Integer4100Population 18 to 21 years - [B01001_E007] + [B01001_E031] + [B01001_E008] + [B01001_E032] + [B01001_E009] + [B01001_E033]AGE_22_29AGE_22_29Integer4100Population 22 to 29 years - [B01001_E010] + [B01001_E034] + [B01001_E011] + [B01001_E035]AGE_30_39AGE_30_39Integer4100Population 30 to 39 years - [B01001_E012] + [B01001_E036] + [B01001_E013] + [B01001_E037]AGE_40_49AGE_40_49Integer4100Population 40 to 49 years - [B01001_E014] + [B01001_E038] + [B01001_E015] + [B01001_E039]AGE_50_64AGE_50_64Integer4100Population 50 to 64 years - [B01001_E016] + [B01001_E040] + [B01001_E017] + [B01001_E041] + [B01001_E018] + [B01001_E042] + [B01001_E019] + [B01001_E043]AGE_65_UPAGE_65_UPInteger4100Population 65 and up - [B01001_E020] + [B01001_E044] + [B01001_E021] + [B01001_E045] + [B01001_E022] + [B01001_E046] + [B01001_E023] + [B01001_E047] + [B01001_E024] + [B01001_E048] + [B01001_E025] + [B01001_E049]AGE_65_74AGE_65_74Integer4100Population 65 to 74 years - [B01001_E020] + [B01001_E044] + [B01001_E021] + [B01001_E045] + [B01001_E022] + [B01001_E046]AGE_75_84AGE_75_84Integer4100Population 75 to 84 years - [B01001_E023] + [B01001_E047] + [B01001_E024] + [B01001_E048]AGE_85_UPAGE_85_UPInteger4100Population 85 years and over - [B01001_E025] + [B01001_E049]MED_AGEMED_AGEDouble8388Median age for population - [B01002_E001]HABVBELOWHABVBELOWInteger4100Households Total: households for poverty status in the past 12 months by household type by age of householder - [B17017_E001]HBELOW_POVHBELOW_POVInteger4100Households with income in the past 12 months below poverty level - [B17017_E002]HABOVE_POVHABOVE_POVInteger4100Households with income in the past 12 months at or above poverty level - [B17017_E031]ABVE_BELWABVE_BELWInteger4100Population Total: Poverty Status of Individuals in the Past 12 Months by Living Arrangement - [B17021_E001]ABOVE_POVABOVE_POVInteger4100Population with income in the past 12 months at or above poverty level - [B17021_E019]BELOW_POVBELOW_POVInteger4100Population with income in the past 12 months below poverty level - [B17021_E002]ED_TOTALED_TOTALInteger4100Population Total: Sex by Educational Attainment for the Population 25 Years and over - [B15002_E001]ED_LESS9THED_LESS9THInteger4100Educational Attainment for the Population 25 Years and over No schooling completed, Nursery to 4th grade, 5th and 6th grade, 7th and 8th grade - [B15002_E003] + [B15002_E020] + [B15002_E004] + [B15002_E021] + [B15002_E005] + [B15002_E022] + [B15002_E006] + [B15002_E023]ED_12NODIPED_12NODIPInteger4100Educational Attainment for the Population 25 Years and over 9th grade, 10th grade, 11th grade, 12th grade, no diploma - [B15002_E007] + [B15002_E024] + [B15002_E008] + [B15002_E025] + [B15002_E009] + [B15002_E026] + [B15002_E010] + [B15002_E027]HSGRADHSGRADInteger4100Educational Attainment for the Population 25 Years and over High school graduate, GED (includes equivalency) - [B15002_E011] + [B15002_E028] + [B15002_E012] + [B15002_E029] + [B15002_E013] + [B15002_E030] + [B15002_E014] + [B15002_E031] + [B15002_E015] + [B15002_E032] + [B15002_E016] + [B15002_E033] + [B15002_E017] + [B15002_E034] + [B15002_E018] + [B15002_E035]ED_SOMECOLED_SOMECOLInteger4100Educational Attainment for the Population 25 Years and over Some college - less than 1 year, Some college - 1 or more years no degree, Associate's degree - [B15002_E012] + [B15002_E029] + [B15002_E013] + [B15002_E030] + [B15002_E014] + [B15002_E031]ED_COLLEGEED_COLLEGEInteger4100Educational Attainment for the Population 25 Years and over Bachelor's degree, Master's degree, Professional school degree, Doctorate degree - [B15002_E015] + [B15002_E032] + [B15002_E016] + [B15002_E033] + [B15002_E017] + [B15002_E034] + [B15002_E018] + [B15002_E035]BACHELORSBACHELORSInteger4100Educational Attainment for the Population 25 Years and over Bachelor's degree only - [B15002_E015] + [B15002_E032]HSE_UNITSHSE_UNITSInteger4100Total Housing Units - [B25001_E001]COEFF_HSEVACANTInteger4100Total Housing Units. This is a duplicate of HSE_UNITS and used internally by GeoPlan - [B25001_E001]VACANTTRAN_TOTALInteger4100Total Vacant housing units - [B25004_E001]TRAN_TOTALTRAN_CARInteger4100Means of Transportation to Work Total, workers 16 years and over - [B08301_E001]TRAN_CARTRAN_MOTOInteger4100Means of Transportation to Work Car, truck, or van - [B08301_E002]TRAN_MOTOTRAN_BIKEInteger4100Means of Transportation to Work Motorcycle - [B08301_E017]TRAN_BIKETRAN_PUBInteger4100Means of Transportation to Work Bicycle - [B08301_E018]TRAN_PUBTRAN_WALKInteger4100Means of Transportation to Work Public transportation (excluding taxicab) - [B08301_E010]TRAN_WALKTRAN_OTHERInteger4100Means of Transportation to Work Walked - [B08301_E019]TRAN_OTHERTRAN_HOMEInteger4100Means of Transportation to Work Other means - [B08301_E020]TRAN_HOMEENROLLEDInteger4100Means of Transportation to Work Worked at home - [B08301_E021]ENROLLEDNOT_ENROLDInteger4100Population 3 Years And Over Enrolled In School - [B14002_E003] + [B14002_E027]NOT_ENROLDLESS_10KInteger4100Population 3 Years And Over Not enrolled in school - [B14002_E025] + [B14002_E049]LESS_10KI10K_14KInteger4100Number of Households with Household Income in The Past 12 Months Less than $10,000 (in 2021 Inflation-Adjusted Dollars) - [B19001_E002]I10K_14KI15K_19KInteger4100Number of Households with Household Income in The Past 12 Months $10,000 to $14,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E003]I15K_19KI20K_24KInteger4100Number of Households with Household Income in The Past 12 Months $15,000 to $19,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E004]I20K_24KI25K_29KInteger4100Number of Households with Household Income in The Past 12 Months $20,000 to $24,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E005]I25K_29KI30K_34KInteger4100Number of Households with Household Income in The Past 12 Months $25,000 to $29,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E006]I30K_34KI35K_39KInteger4100Number of Households with Household Income in The Past 12 Months $30,000 to $34,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E007]I35K_39KI40K_44KInteger4100Number of Households with Household Income in The Past 12 Months $35,000 to $39,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E008]I40K_44KI45K_49KInteger4100Number of Households with Household Income in The Past 12 Months $40,000 to $44,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E009]I45K_49KI50K_59KInteger4100Number of Households with Household Income in The Past 12 Months $45,000 to $49,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E010]I50K_59KI60K_74KInteger4100Number of Households with Household Income in The Past 12 Months $50,000 to $59,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E011]I60K_74KI75K_99KInteger4100Number of Households with Household Income in The Past 12 Months $60,000 to $74,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E012]I75K_99KI100K_124KInteger4100Number of Households with Household Income in The Past 12 Months $75,000 to $99,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E013]I100K_124KI125K_149KInteger4100Number of Households with Household Income in The Past 12 Months $100,000 to $124,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E014]I125K_149KI150K_199KInteger4100Number of Households with Household Income in The Past 12 Months $125,000 to $149,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E015]I150K_199KI200KMOREInteger4100Number of Households with Household Income in The Past 12 Months $150,000 to $199,999 (in 2021 Inflation-Adjusted Dollars) - [B19001_E016]I200KMOREMEDHHINCInteger4100Number of Households with Household Income in The Past 12 Months $200,000 or more (in 2021 Inflation-Adjusted Dollars) - [B19001_E017]MEDHHINCMEDFINCOMEInteger4100Median household income in the past 12 months (in 2021 inflation-adjusted dollars) - [B19013_E001]MEDFINCOMEHH_NOPUBAInteger4100Median family income in the past 12 months (in 2021 inflation-adjusted dollars) - [B19113_E001]HH_NOPUBAHH_PUBAInteger4100Households with No public assistance income - [B19057_E003]HH_PUBAMEDOOHVALInteger4100Households with public assistance income - [B19057_E002]MEDOOHVALH1ATTACHInteger4100Median value (dollars) Owner-occupied housing units - [B25077_E001]H1ATTACHH1DETACHInteger4100Housing Units in Structure 1, attached - [B25024_E003]H1DETACHH2UNITInteger4100Housing Units in Structure 1, detached - [B25024_E002]H2UNITH3_4UNITInteger4100Housing Units in Structure 2 - [B25024_E004]H3_4UNITH5_9UNITInteger4100Housing Units in Structure 3 or 4 - [B25024_E005]H5_9UNITH10_19UNITInteger4100Housing Units in Structure 5 to 9 - [B25024_E006]H10_19UNITH20_49UNITInteger4100Housing Units in Structure 10 to 19 - [B25024_E007]H20_49UNITH50MOREInteger4100Housing Units in Structure 20 to 49 - [B25024_E008]H50MOREMOBILEInteger4100Housing Units in Structure 50 or more - [B25024_E009]MOBILEOTHERHOUSEInteger4100Housing Units in Structure Mobile home - [B25024_E010]OTHERHOUSEH_SFInteger4100Housing Units in Structure Boat, RV, van, etc. - [B25024_E011]H_SFH_MFInteger4100Single Family - [H1ATTACH]+ [H1DETACH]H_MFOWNERInteger4100Mulit Family - [H2UNIT] + [H3_4UNIT] + [H5_9UNIT] + [H10_19UNIT] + [H20_49UNIT] + [H50MORE]OWNERRENTERInteger4100Owner occupied housing units - [B25038_E002]RENTEROWN_19Integer4100Renter occupied housing units - [B25038_E009]OWN_19RENT_19Integer4100Owner occupied housing units Moved in 2019 or later - [B25038_E003]RENT_19B20Integer4100Renter occupied housing units Moved in 2019 or later - [B25038_E010]B20B10_19Integer4100Housing Units Built 2020 or later - [B25034_E002]B10_19B00_09Integer4100Housing Units Built 2010 to 2019 - [B25034_E003]B00_09B90_99Integer4100Housing Units Built 2000 to 2009 - [B25034_E004]B90_99B80_89Integer4100Housing Units Built 1990 to 1999 - [B25034_E005]B80_89B70_79Integer4100Housing Units Built 1980 to 1989 - [B25034_E006]B70_79B60_69Integer4100Housing Units Built 1970 to 1979 - [B25034_E007]B60_69B50_59Integer4100Housing Units Built 1960 to 1969 - [B25034_E008]B50_59B40_49Integer4100Housing Units Built 1950 to 1959 - [B25034_E009]B40_49BEFORE39Integer4100Housing Units Built 1940 to 1949 - [B25034_E010]BEFORE39M19Integer4100Housing Units Built 1939 or earlier - [B25034_E011]M19M15_18Integer4100Occupied housing units moved in 2019 or later - [B25038_E003] + [B25038_E010]M15_18M10_14Integer4100Occupied housing units Moved in 2015 to 2018 - [B25038_E004] + [B25038_E011]M10_14M00_09Integer4100Occupied housing units Moved in 2010 to 2014 - [B25038_E005] + [B25038_E012]M00_09M90_99Integer4100Occupied housing units Moved in 2000 to 2009 - [B25038_E006] + [B25038_E013]M90_99M89BEFOREInteger4100Occupied housing units Moved in 1990 to 1999 - [B25038_E007] + [B25038_E014]M89BEFOREMO_19Integer4100Occupied housing units Moved in 1989 or earlier - [B25038_E008] + [B25038_E015]MO_19MO_15_18Integer4100Owner Occupied housing units moved in 2019 or later - [B25038_E003]MO_15_18MO_10_14Integer4100Owner Occupied housing units Moved in 2015 to 2018 - [B25038_E004]MO_10_14MO_00_09Integer4100Owner Occupied housing units Moved in 2010 to 2014 - [B25038_E005]MO_00_09MO_90_99Integer4100Owner Occupied housing units Moved in 2000 to 2009 - [B25038_E006]MO_90_99MO89BEFOREInteger4100Owner Occupied housing units Moved in 1990 to 1999 - [B25038_E007]MO89BEFOREMR_19Integer4100Owner Occupied housing units Moved in 1989 or earlier - [B25038_E008]MR_19MR_15_18Integer4100Renter Occupied housing units moved in 2019 or later - [B25038_E010]MR_15_18MR_10_14Integer4100Renter Occupied housing units Moved in 2015 to 2018 - [B25038_E011]MR_10_14MR_00_09Integer4100Renter Occupied housing units Moved in 2010 to 2014 - [B25038_E012]MR_00_09MR_90_99Integer4100Renter Occupied housing units Moved in 2000 to 2009 - [B25038_E013]MR_90_99MR89BEFOREInteger4100Renter Occupied housing units Moved in 1990 to 1999 - [B25038_E014]MR89BEFOREMYTOTALInteger4100Renter Occupied housing units Moved in 1989 or earlier - [B25038_E015]MYTOTALMYOWNERInteger4100Median year householder moved into unit - Occupied Housing Units Total - [B25039_E001]MYOWNERMYRENTERInteger4100Median year householder moved into unit - Occupied Housing Units Owner - [B25039_E002]MYRENTERVEHICLE_0Integer4100Median year householder moved into unit - Occupied Housing Units Renter - [B25039_E003]VEHICLE_0VEHICLE_1Integer4100Occupied Housing Units with No vehicle available - [B25044_E003] + [B25044_E010]VEHICLE_1VEHICLE_2Integer4100Occupied Housing Units with 1 vehicle available - [B25044_E004] + [B25044_E011]VEHICLE_2VEHICLE_3Integer4100Occupied Housing Units with 2 vehicles available - [B25044_E005] + [B25044_E012]VEHICLE_3VEHICLE_4Integer4100Occupied Housing Units with 3 vehicles available - [B25044_E006] + [B25044_E013]VEHICLE_4VEHICLE5GInteger4100Occupied Housing Units with 4 vehicles available - [B25044_E007] + [B25044_E014]VEHICLE5GS_TOTALInteger4100Occupied Housing Units with 5 or more vehicles available - [B25044_E008] + [B25044_E015]S_TOTALS_VERYWELLInteger4100Ability to Speak English for the Population 5+ Yrs Total - [B16004_E001]S_VERYWELLS_WELLInteger4100Ability to Speak English for the Population 5+ Yrs Speak English 'very well' - [B16004_E005] + [B16004_E010] + [B16004_E015] + [B16004_E020] + [B16004_E027] + [B16004_E032] + [B16004_E037] + [B16004_E042] + [B16004_E049] + [B16004_E054] + [B16004_E059] + [B16004_E064]S_WELLS_NOTWELLInteger4100Ability to Speak English for the Population 5+ Yrs Speak English 'well' - [B16004_E006] + [B16004_E011] + [B16004_E016] + [B16004_E021] + [B16004_E028] + [B16004_E033] + [B16004_E038] + [B16004_E043] + [B16004_E050] + [B16004_E055] + [B16004_E060] + [B16004_E065]S_NOTWELLS_NOTATALLInteger4100Ability to Speak English for the Population 5+ Yrs Speak English 'not well' - [B16004_E007] + [B16004_E012] + [B16004_E017] + [B16004_E022] + [B16004_E029] + [B16004_E034] + [B16004_E039] + [B16004_E044] + [B16004_E051] + [B16004_E056] + [B16004_E061] + [B16004_E066]S_NOTATALLS_ENGLISHInteger4100Ability to Speak English for the Population 5+ Yrs Speak English 'not at all' - [B16004_E008] + [B16004_E013] + [B16004_E018] + [B16004_E023] + [B16004_E030] + [B16004_E035] + [B16004_E040] + [B16004_E045] + [B16004_E052] + [B16004_E057] + [B16004_E062] + [B16004_E067]S_ENGLISHS_SPANISHInteger4100Ability to Speak English for the Population 5+ Yrs Speak only English - [B16004_E003] + [B16004_E025] + [B16004_E047]S_SPANISHS_EUROPEInteger4100Ability to Speak English for the Population 5+ Yrs Speak Spanish - [B16004_E004] + [B16004_E026] + [B16004_E048]S_EUROPES_ASIANInteger4100Ability to Speak English for the Population 5+ Yrs Speak other Indo-European languages - [B16004_E009] + [B16004_E031] + [B16004_E053]S_ASIANS_OTHERInteger4100Ability to Speak English for the Population 5+ Yrs Speak Asian and Pacific Island languages - [B16004_E014] + [B16004_E036] + [B16004_E058]S_OTHERS_NOTVERYWELLInteger4100Ability to Speak English for the Population 5+ Yrs Speak other languages - [B16004_E019] + [B16004_E041] + [B16004_E063]S_NOTVERYWELLS_NOTInteger4100Ability to Speak English for the Population 5+ Yrs, speak well, not well, or not at all - [s_well] + [s_notwell] + [s_notatall]S_NOTHL_TOTALInteger4100Ability to Speak English for the Population 5+ Yrs, not well, or not at all - [s_notwell] + [s_notatall]HL_TOTALHL_ENGLISHInteger4100Total Households by Household Language by Household Limited English Speaking Status - [C16002_E001]HL_ENGLISHHL_SPAN_LInteger4100Households that speak English. This includes households that are English only, or that speak other languages but are not a limited English speaking household. - [C16002_E002] + [C16002_E005]+ [C16002_E008]+ [C16002_E011]+ [C16002_E014]HL_SPAN_LHL_EURO_LInteger4100Households that speak Spanish: Limited English speaking household - [C16002_E004]HL_EURO_LHL_ASIAN_LInteger4100Households that speak Other Indo-European languages: Limited English speaking household - [C16002_E007]HL_ASIAN_LHL_OTHER_LInteger4100Households that speak Asian and Pacific Island languages: Limited English speaking household - [C16002_E010]HL_OTHER_LLABOR_CIVInteger4100Households that speak Other languages: Limited English speaking household - [C16002_E013]LABOR_CIVRTOTALInteger4100Civilian Employed Population 16 Years And Over Total - [C24010_E001]RTOTALRU50Integer4100Ratio of Income to Poverty Level in the Past 12 Months. Total population for whom Poverty Status is Determined - [C17002_E001]RU50R50_99Integer4100Ratio of Income to Poverty Level in the Past 12 Months Under .50 - [C17002_E002]R50_99R1_124Integer4100Ratio of Income to Poverty Level in the Past 12 Months .50 to .99 - [C17002_E003]R1_124R125ABVInteger4100Ratio of Income to Poverty Level in the Past 12 Months 1.00 to 1.24 - [C17002_E004]R125ABVRU1Integer4100Ratio of Income to Poverty Level in the Past 12 Months 1.25 and over - [C17002_E005] + [C17002_E006] + [C17002_E007] + [C17002_E008]RU1RU2ABVInteger4100Ratio of Income to Poverty Level in the Past 12 Months under 1 - [RU50] + [R50_99]RU2ABVDIS_TOTALInteger4100Ratio of Income to Poverty Level in the Past 12 Months 2.00 and over - [C17002_E008]DIS_TOTALDIS_2064Integer4100Population by Poverty Status in the Past 12 Months by Disability Status by Employment Status for the Population 20 to 64 Years Total - [B23024_E001]DIS_2064NO_DIS2064Integer4100Population 20 to 64 Years with Income in the past 12 months below and above poverty level with a disability - [B23024_E003] + [B23024_E018]NO_DIS2064GMTOTInteger4100Population 20 to 64 Years with Income in the past 12 months below and above poverty level with No disability - [B23024_E010] + [B23024_E025]GMTOTGMSAMEInteger4100Geographical Mobility in the Past Year for Current Residence Population 1 Year And Over Living in and out of Metropolitan Statistical Areas or Micropolitan Statistical Areas In The United States: Total - [B07201_E001] + [B07202_E001] + [B07203_E001]GMSAMEGMDIFFInteger4100Geographical Mobility in the Past Year for Current Residence Population 1 Year And Over Living in and out of Metropolitan Statistical Areas or Micropolitan Statistical Areas In The United States: Same house 1 year ago - [B07201_E002] + [B07202_E002] + [B07203_E002]GMDIFFGMABROADInteger4100Geographical Mobility in the Past Year for Current Residence Population 1 Year And Over Living in and out of Metropolitan Statistical Areas or Micropolitan Statistical Areas In The United States: Different house in United States 1 year ago - [B07201_E003] + [B07202_E003] + [B07203_E003]GMABROADC_TOTALInteger4100Geographical Mobility in the Past Year for Current Residence Population 1 Year And Over Living in and out of Metropolitan Statistical Areas or Micropolitan Statistical Areas In The United States: Abroad 1 year ago - [B07201_E014] + [B07202_E014] + [B07203_E011]C_TOTALC_COMPUTERInteger4100Types of Computers in Household. Total Households - [B28001_E001]C_COMPUTERC_NO_COMPInteger4100Households that have one or more types of computing devices. Includes: Desktop or laptop, Smartphone, Tablet or other portable wireless computer, Other computer - [B28001_E002]C_NO_COMPI_TOTALInteger4100Households that have No Computer - [B28001_E011]I_TOTALI_INTERNETInteger4100Presence and Types of Internet Subscriptions in Household. Total Households. - [B28002_E001]I_INTERNETI_NO_SUBInteger4100Households with an Internet Subscription. Includes: Dial-up, Cellular, Broadband, Satellite, or Other - [B28002_E002]I_NO_SUBI_NO_NETInteger4100Households with Internet Access without a Subscription - [B28002_E012]I_NO_NETPCT_NOTWELDouble8388Households with no Internet Access - [B28002_E013]PCT_NOTWELPCT_NOTATADouble8388Percent Ability to Speak English for the Population 5+ Yrs Speak English 'not well' - ([S_NOTWELL]/[S_TOTAL] * 100)PCT_NOTATAPCT_BACHLRDouble8388Percent Ability to Speak English for the Population 5+ Yrs Speak English 'not at all' - ([S_NOTATALL]/[S_TOTAL] * 100)PCT_BACHLRPCT_POVDouble8388Percent Educational Attainment for the Population 25 Years and over Bachelor's degree only - ([BACHELORS]/[TOTALPOP] * 100)PCT_POVPCT_RU50Double8388Percent Population with income in the past 12 months below poverty level - ([BELOW_POV]/[ABVE_BELW] * 100)PCT_RU50PCT_R50_9Double8388Percent Ratio of Income to Poverty Level in the Past 12 Months Under .50 - ([RU50]/[RTOTAL] * 100)PCT_R50_9PCT_R125ABDouble8388RPercent atio of Income to Poverty Level in the Past 12 Months .50 to .99 - ([R50_99]/[RTOTAL] * 100)PCT_R125ABPCT_RU1Double8388Percent Ratio of Income to Poverty Level in the Past 12 Months 1.25 and over - ([R125ABV]/[RTOTAL] * 100)PCT_RU1DEN_POPDouble8388Percent Ratio of Income to Poverty Level in the Past 12 Months under 1 - ([RU1]/[RTOTAL] * 100)DEN_POPPCT_WHITEDouble8388Population per acre - [TOTALPOP]/[ACRES]PCT_WHITEPCT_BLACKDouble8388Percent of Persons White alone - ([WHITE] /[TOTALPOP] *100)PCT_BLACKPCT_AMERIDouble8388Percent of Persons Black or African American alone - ([BLACK] /[TOTALPOP] *100)PCT_AMERIPCT_ASIANDouble8388Percent of Persons American Indian and Alaska Native alone - ([AMERI_ES] /[TOTALPOP] *100)PCT_ASIANPCT_HAWNDouble8388Percent of Persons Asian alone - ([ASIAN] /[TOTALPOP] *100)PCT_HAWNPCT_OTHERDouble8388Percent of Persons Native Hawaiian and Other Pacific Islander alone - ([HAWN_PI] /[TOTALPOP] *100)PCT_OTHERPCT_MULTIDouble8388Percent of Persons Some other race alone - ([OTHER] /[TOTALPOP] *100)PCT_MULTIPCT_HISPDouble8388Percent of Persons Two or more races - ([MULT_RACE] /[TOTALPOP] *100)PCT_HISPPCT_DIS20Double8388Percent of Persons Hispanic or Latino - ([HISPANIC] /[TOTALPOP] *100)PCT_DIS20DESCRIPTString1200Percent Population 20 To 64 Years With a disability - ([DIS_2064]/[DIS_TOTAL] * 100)DESCRIPTFGDLAQDATEDate800GeoPlan added field based on GEOID00FGDLAQDATETIGERYEARString2500Date ACS data was downloaded from U.S. Census BureauTIGERYEARDATAYEARString2500Source date for Tiger data (spatial portion of this layer)DATAYEARSHAPE.AREADouble000Source Date of ACS dataCOEFF_HSEAUTOIDInteger4100This is a duplicate of HSE_UNITS field used for internal GeoPlan purposes.GeoPlanSHAPE.AREASHAPE.LENDouble000SHAPE.LENCOEFF_HSEInteger4100SimpleFALSE13312TRUEFALSE/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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