20260203 13295100 1.0 FALSE CENPLACE_ACS_2024 77729.663400 799462.445400 62210.639800 780734.593500 1 002 Projected GCS_North_American_1983_HARN Linear 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/3.5.0'><WKT>PROJCS[&quot;NAD_1983_HARN_Florida_GDL_Albers&quot;,GEOGCS[&quot;GCS_North_American_1983_HARN&quot;,DATUM[&quot;D_North_American_1983_HARN&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Albers&quot;],PARAMETER[&quot;False_Easting&quot;,400000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-84.0],PARAMETER[&quot;Standard_Parallel_1&quot;,24.0],PARAMETER[&quot;Standard_Parallel_2&quot;,31.5],PARAMETER[&quot;Latitude_Of_Origin&quot;,24.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3087]]</WKT><XOrigin>-19550100</XOrigin><YOrigin>-7526400</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3087</WKID><LatestWKID>3087</LatestWKID></ProjectedCoordinateSystem> 20260203 16273200 20260203 16273200 500000 5000 FGDC dataset U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch 301-763-1128 301-763-4710 4600 Silver Hill Road, Stop 7400 Washington D.C. 20233-7400 US geo.tiger@census.gov 20260203 ArcGIS Metadata 1.0 0.000 Florida Geographic Data Library (FGDL) Jonathan and Melanie Antevy Hall 1480 Inner Road, Room 431 PO Box 115706 Gainesville FL 32611-5706 US https://fgdl.org/info/contact/ None DOWNLOADABLE DATA https://www.fgdl.org/ Enterprise Geodatabase Feature Class 2024 Census Places in Florida (With Selected Fields From the 2020-2024 American Community Survey) 2026-01-28T00:00:00 U.S. Census Bureau U.S. Census Bureau Washington, DC Vector Digital Data Set (Polygon) State of Florida <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This dataset contains a combination of US Census Bureau 2024 Designated Places and Incorporated Places for the State of Florida with selected fields from the 2020-2024 American Community Survey (ACS). Some of the fields included in this dataset are total population, education, and housing and economic characteristics. The ACS was designed to replace the long-form of the decennial census. The ACS is a survey that releases data annually. 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> This dataset contains a combination of US Census Bureau 2024 Designated Places and Incorporated Places for the State of Florida with selected fields from the 2020-2024 American Community Survey (ACS). Some of the fields included in this dataset are total population, education, and housing and economic characteristics. U.S. Census Bureau (301) 763-4039 (301) 763-4348 4600 Silver Hill Road, Stop 7400 Washington, D.C. 20233-7400 US http://www.census.gov/ Florida Census Place ISO 19115 Topic Category socioeconomic education housing population economic ISO 19115 Topic Category boundaries society socioeconomic education housing boundaries Florida place population society economic 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. <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.html Esri ArcGIS 13.0.3.36057 -87.639356 -79.812215 24.354693 31.042641 publication date 2020-01-01T00:00:00 2024-12-31T00:00:00 1 -87.376525 -79.815270 31.034995 24.503848 2026-12-12T00:00:00 This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topology The 2024 TIGER line files were downloaded from the following site: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-geodatabase-file.html downloaded on 1/28/26. The data was projected to Albers HPGN. Merged layers tlgdb_2024_a_12_fl.gdb\Census_Designated_Place and Incorporated_Place to create CENPLACE_ACS_2024. The American Community Survey data was downloaded from the Census Bureau in dat format from: https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData. date downloaded: 1/28/26. 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 fields. 2026-01-28T00:00:00 GeoPlan Spatial and Attribute Information This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topology. This 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 GeoPlan. This data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlan. 0 956 EPSG 6.12(9.2.0) CENPLACE_ACS_2024 CENPLACE_ACS_2024 U.S. Census Bureau Feature Class 956 OBJECTID Internal feature number. Esri OBJECTID OID 4 10 0 Sequential unique whole numbers that are automatically generated. Shape Feature geometry. Esri Shape Geometry 8 0 0 Coordinates defining the features. PLACENS Current place GNIS code USCB PLACENS String 8 0 0 GEOID Used by GeoPlan for join USCB GEOID String 7 0 0 NAMELSAD Census translated legal/statistical area description USCB NAMELSAD String 100 0 0 CLASSFP Current FIPS class code USCB CLASSFP String 2 0 0 FUNCSTAT Current functional status USCB FUNCSTAT String 1 0 0 ALAND Census land area (square meters) USCB ALAND Double 8 38 8 AWATER Census water area (square meters) USCB AWATER Double 8 38 8 INTPTLAT Census latitude of the internal point USCB INTPTLAT String 11 0 0 INTPTLON Census longitude of the internal point USCB INTPTLON String 12 0 0 ACRES Acres GeoPlan ACRES Double 8 38 8 FILEID Census File ID USCB FILEID String 5 0 0 STUSAB 2 letter state code USCB STUSAB String 2 0 0 SUMLEVEL Census geographic summary level USCB SUMLEVEL Double 8 38 8 STATE State USCB STATE Double 8 38 8 NAME Census place name USCB NAME String 230 0 0 TOTALPOP TOTALPOP Integer 4 10 0 Total Population - [B01003_E001] HOUSEHOLDS HOUSEHOLDS Integer 4 10 0 Total: Households (Includes Living Alone) - [B11001_E001] MALE MALE Integer 4 10 0 Population Male - [B01001_E002] FEMALE FEMALE Integer 4 10 0 Population Female - [B01001_E026] WHITE WHITE Integer 4 10 0 Population White alone - [B02001_E002] BLACK BLACK Integer 4 10 0 Population Black or African American alone - [B02001_E003] AMERI_ES AMERI_ES Integer 4 10 0 Population American Indian and Alaska Native alone - [B02001_E004] ASIAN ASIAN Integer 4 10 0 Population Asian alone - [B02001_E005] HAWN_PI HAWN_PI Integer 4 10 0 Population Native Hawaiian and Other Pacific Islander alone - [B02001_E006] OTHER OTHER Integer 4 10 0 Population Some other race alone - [B02001_E007] MULT_RACE MULT_RACE Integer 4 10 0 Population Two or more races - [B02001_E008] HISPANIC HISPANIC Integer 4 10 0 Population Hispanic or Latino by Race - [B03002_E012] WHITE_NH WHITE_NH Integer 4 10 0 Not Hispanic or Latino: White alone - [B03002_E003] HISPNC_NOT HISPNC_NOT Integer 4 10 0 Total Population minus Hispanic Population - [TOTALPOP] - [HISPANIC] MINORITY MINORITY Integer 4 10 0 "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_SZ AVE_HH_SZ Double 8 38 8 Average household size Total: Average Household Size of Occupied Housing Units by Tenure - [B25010_E001] PH_TOTAL PH_TOTAL Integer 4 10 0 Total: Household Type by Relatives and Nonrelatives for Population in Households - [B11002_E001] PH_FAM PH_FAM Integer 4 10 0 Population in family households - [B11002_E002] PH_NONFAM PH_NONFAM Integer 4 10 0 Population in nonfamily households - [B11002_E012] FAM_HH FAM_HH Integer 4 10 0 Family households - [B11001_E002] AVE_FAM_SZ AVE_FAM_SZ Double 8 38 8 Average family size (Total Population In family households/Family households) - [PH_FAM]/[FAM_HH] AGE_UNDER5 AGE_UNDER5 Integer 4 10 0 Population Under 5 years - [B01001_E003] + [B01001_E027] AGE_5_17 AGE_5_17 Integer 4 10 0 Population 5 to 17 years - [B01001_E004] + [B01001_E028] + [B01001_E005] + [B01001_E029] + [B01001_E006] + [B01001_E030] AGE_18_21 AGE_18_21 Integer 4 10 0 Population 18 to 21 years - [B01001_E007] + [B01001_E031] + [B01001_E008] + [B01001_E032] + [B01001_E009] + [B01001_E033] AGE_22_29 AGE_22_29 Integer 4 10 0 Population 22 to 29 years - [B01001_E010] + [B01001_E034] + [B01001_E011] + [B01001_E035] AGE_30_39 AGE_30_39 Integer 4 10 0 Population 30 to 39 years - [B01001_E012] + [B01001_E036] + [B01001_E013] + [B01001_E037] AGE_40_49 AGE_40_49 Integer 4 10 0 Population 40 to 49 years - [B01001_E014] + [B01001_E038] + [B01001_E015] + [B01001_E039] AGE_50_64 AGE_50_64 Integer 4 10 0 Population 50 to 64 years - [B01001_E016] + [B01001_E040] + [B01001_E017] + [B01001_E041] + [B01001_E018] + [B01001_E042] + [B01001_E019] + [B01001_E043] AGE_65_UP AGE_65_UP Integer 4 10 0 Population 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_74 AGE_65_74 Integer 4 10 0 Population 65 to 74 years - [B01001_E020] + [B01001_E044] + [B01001_E021] + [B01001_E045] + [B01001_E022] + [B01001_E046] AGE_75_84 AGE_75_84 Integer 4 10 0 Population 75 to 84 years - [B01001_E023] + [B01001_E047] + [B01001_E024] + [B01001_E048] AGE_85_UP AGE_85_UP Integer 4 10 0 Population 85 years and over - [B01001_E025] + [B01001_E049] MED_AGE MED_AGE Double 8 38 8 Median age for population - [B01002_E001] HABVBELOW HABVBELOW Integer 4 10 0 Households Total: households for poverty status in the past 12 months by household type by age of householder - [B17017_E001] HBELOW_POV HBELOW_POV Integer 4 10 0 Households with income in the past 12 months below poverty level - [B17017_E002] HABOVE_POV HABOVE_POV Integer 4 10 0 Households with income in the past 12 months at or above poverty level - [B17017_E031] ABVE_BELW ABVE_BELW Integer 4 10 0 Population Total: Poverty Status of Individuals in the Past 12 Months by Living Arrangement - [B17021_E001] ABOVE_POV ABOVE_POV Integer 4 10 0 Population with income in the past 12 months at or above poverty level - [B17021_E019] BELOW_POV BELOW_POV Integer 4 10 0 Population with income in the past 12 months below poverty level - [B17021_E002] ED_TOTAL ED_TOTAL Integer 4 10 0 Population Total: Sex by Educational Attainment for the Population 25 Years and over - [B15002_E001] ED_LESS9TH ED_LESS9TH Integer 4 10 0 Educational 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_12NODIP ED_12NODIP Integer 4 10 0 Educational 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] HSGRAD HSGRAD Integer 4 10 0 Educational 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_SOMECOL ED_SOMECOL Integer 4 10 0 Educational 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_COLLEGE ED_COLLEGE Integer 4 10 0 Educational 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] BACHELORS BACHELORS Integer 4 10 0 Educational Attainment for the Population 25 Years and over Bachelor's degree only - [B15002_E015] + [B15002_E032] HSE_UNITS HSE_UNITS Integer 4 10 0 Total Housing Units - [B25001_E001] HS_PER_AC HS_PER_AC Double 8 38 8 Housing units per acre - [HSE_UNITS]/[ACRES] VACANT VACANT Integer 4 10 0 Total Vacant housing units - [B25004_E001] TRAN_TOTAL TRAN_TOTAL Integer 4 10 0 Means of Transportation to Work Total, workers 16 years and over - [B08301_E001] TRAN_CAR TRAN_CAR Integer 4 10 0 Means of Transportation to Work Car, truck, or van - [B08301_E002] TRAN_MOTO TRAN_MOTO Integer 4 10 0 Means of Transportation to Work Motorcycle - [B08301_E017] TRAN_BIKE TRAN_BIKE Integer 4 10 0 Means of Transportation to Work Bicycle - [B08301_E018] TRAN_PUB TRAN_PUB Integer 4 10 0 Means of Transportation to Work Public transportation - [B08301_E010] TRAN_WALK TRAN_WALK Integer 4 10 0 Means of Transportation to Work Walked - [B08301_E019] TRAN_OTHER TRAN_OTHER Integer 4 10 0 Means of Transportation to Work Other means - [B08301_E020] TRAN_HOME TRAN_HOME Integer 4 10 0 Means of Transportation to Work Worked at home - [B08301_E021] ENROLLED ENROLLED Integer 4 10 0 Population 3 Years And Over Enrolled In School - [B14002_E003] + [B14002_E027] NOT_ENROLD NOT_ENROLD Integer 4 10 0 Population 3 Years And Over Not enrolled in school - [B14002_E025] + [B14002_E049] LESS_10K LESS_10K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months Less than $10,000 (in 2024 Inflation-Adjusted Dollars) - [B19001_E002] I10K_14K I10K_14K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $10,000 to $14,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E003] I15K_19K I15K_19K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $15,000 to $19,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E004] I20K_24K I20K_24K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $20,000 to $24,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E005] I25K_29K I25K_29K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $25,000 to $29,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E006] I30K_34K I30K_34K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $30,000 to $34,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E007] I35K_39K I35K_39K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $35,000 to $39,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E008] I40K_44K I40K_44K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $40,000 to $44,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E009] I45K_49K I45K_49K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $45,000 to $49,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E010] I50K_59K I50K_59K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $50,000 to $59,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E011] I60K_74K I60K_74K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $60,000 to $74,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E012] I75K_99K I75K_99K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $75,000 to $99,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E013] I100K_124K I100K_124K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $100,000 to $124,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E014] I125K_149K I125K_149K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $125,000 to $149,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E015] I150K_199K I150K_199K Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $150,000 to $199,999 (in 2024 Inflation-Adjusted Dollars) - [B19001_E016] I200KMORE I200KMORE Integer 4 10 0 Number of Households with Household Income in The Past 12 Months $200,000 or more (in 2024 Inflation-Adjusted Dollars) - [B19001_E017] MEDHHINC MEDHHINC Integer 4 10 0 Median household income in the past 12 months (in 2024 Inflation-adjusted dollars) - [B19013_E001] MEDFINCOME MEDFINCOME Integer 4 10 0 Median family income in the past 12 months (in 2024 Inflation-adjusted dollars) - [B19113_E001] HH_NOPUBA HH_NOPUBA Integer 4 10 0 Households with No public assistance income - [B19057_E003] HH_PUBA HH_PUBA Integer 4 10 0 Households with public assistance income - [B19057_E002] MEDOOHVAL MEDOOHVAL Integer 4 10 0 Median value (dollars) Owner-occupied housing units - [B25077_E001] H1ATTACH H1ATTACH Integer 4 10 0 Housing Units in Structure 1, attached - [B25024_E003] H1DETACH H1DETACH Integer 4 10 0 Housing Units in Structure 1, detached - [B25024_E002] H2UNIT H2UNIT Integer 4 10 0 Housing Units in Structure 2 - [B25024_E004] H3_4UNIT H3_4UNIT Integer 4 10 0 Housing Units in Structure 3 or 4 - [B25024_E005] H5_9UNIT H5_9UNIT Integer 4 10 0 Housing Units in Structure 5 to 9 - [B25024_E006] H10_19UNIT H10_19UNIT Integer 4 10 0 Housing Units in Structure 10 to 19 - [B25024_E007] H20_49UNIT H20_49UNIT Integer 4 10 0 Housing Units in Structure 20 to 49 - [B25024_E008] H50MORE H50MORE Integer 4 10 0 Housing Units in Structure 50 or more - [B25024_E009] MOBILE MOBILE Integer 4 10 0 Housing Units in Structure Mobile home - [B25024_E010] OTHERHOUSE OTHERHOUSE Integer 4 10 0 Housing Units in Structure Boat, RV, van, etc. - [B25024_E011] H_SF H_SF Integer 4 10 0 Single Family - [H1ATTACH]+ [H1DETACH] H_MF H_MF Integer 4 10 0 Mulit Family - [H2UNIT] + [H3_4UNIT] + [H5_9UNIT] + [H10_19UNIT] + [H20_49UNIT] + [H50MORE] OWNER OWNER Integer 4 10 0 Owner occupied housing units - [B25038_E002] RENTER RENTER Integer 4 10 0 Renter occupied housing units - [B25038_E009] OWN_23 OWN_23 Integer 4 10 0 Owner occupied housing units Moved in 2023 or later - [B25038_E003] RENT_23 RENT_23 Integer 4 10 0 Renter occupied housing units Moved in 2023 or later - [B25038_E010] B20 B20 Integer 4 10 0 Housing Units Built 2020 or later - [B25034_E002] B10_19 B10_19 Integer 4 10 0 Housing Units Built 2010 to 2019 - [B25034_E003] B00_09 B00_09 Integer 4 10 0 Housing Units Built 2000 to 2009 - [B25034_E004] B90_99 B90_99 Integer 4 10 0 Housing Units Built 1990 to 1999 - [B25034_E005] B80_89 B80_89 Integer 4 10 0 Housing Units Built 1980 to 1989 - [B25034_E006] B70_79 B70_79 Integer 4 10 0 Housing Units Built 1970 to 1979 - [B25034_E007] B60_69 B60_69 Integer 4 10 0 Housing Units Built 1960 to 1969 - [B25034_E008] B50_59 B50_59 Integer 4 10 0 Housing Units Built 1950 to 1959 - [B25034_E009] B40_49 B40_49 Integer 4 10 0 Housing Units Built 1940 to 1949 - [B25034_E010] BEFORE39 BEFORE39 Integer 4 10 0 Housing Units Built 1939 or earlier - [B25034_E011] M23 M23 Integer 4 10 0 Occupied housing units moved in 2023 or later - [B25038_E003] + [B25038_E010] M20_22 M20_22 Integer 4 10 0 Occupied housing units Moved in 2020 to 2022 - [B25038_E004] + [B25038_E011] M10_19 M10_19 Integer 4 10 0 Occupied housing units Moved in 2010 to 2019 - [B25038_E005] + [B25038_E012] M00_09 M00_09 Integer 4 10 0 Occupied housing units Moved in 2000 to 2009 - [B25038_E006] + [B25038_E013] M90_99 M90_99 Integer 4 10 0 Occupied housing units Moved in 1990 to 1999 - [B25038_E007] + [B25038_E014] M89BEFORE M89BEFORE Integer 4 10 0 Occupied housing units Moved in 1989 or earlier - [B25038_E008] + [B25038_E015] MO_23 MO_23 Integer 4 10 0 Owner Occupied housing units moved in 2023 or later - [B25038_E003] MO_20_22 MO_20_22 Integer 4 10 0 Owner Occupied housing units Moved in 2020 to 2022 - [B25038_E004] MO_10_19 MO_10_19 Integer 4 10 0 Owner Occupied housing units Moved in 2010 to 2019 - [B25038_E005] MO_00_09 MO_00_09 Integer 4 10 0 Owner Occupied housing units Moved in 2000 to 2009 - [B25038_E006] MO_90_99 MO_90_99 Integer 4 10 0 Owner Occupied housing units Moved in 1990 to 1999 - [B25038_E007] MO89BEFORE MO89BEFORE Integer 4 10 0 Owner Occupied housing units Moved in 1989 or earlier - [B25038_E008] MR_23 MR_23 Integer 4 10 0 Renter Occupied housing units moved in 2023 or later - [B25038_E010] MR_20_22 MR_20_22 Integer 4 10 0 Renter Occupied housing units Moved in 2020 to 2022 - [B25038_E011] MR_10_19 MR_10_19 Integer 4 10 0 Renter Occupied housing units Moved in 2010 to 2019 - [B25038_E012] MR_00_09 MR_00_09 Integer 4 10 0 Renter Occupied housing units Moved in 2000 to 2009 - [B25038_E013] MR_90_99 MR_90_99 Integer 4 10 0 Renter Occupied housing units Moved in 1990 to 1999 - [B25038_E014] MR89BEFORE MR89BEFORE Integer 4 10 0 Renter Occupied housing units Moved in 1989 or earlier - [B25038_E015] MYTOTAL MYTOTAL Integer 4 10 0 Median year householder moved into unit - Occupied Housing Units Total - [B25039_E001] MYOWNER MYOWNER Integer 4 10 0 Median year householder moved into unit - Occupied Housing Units Owner - [B25039_E002] MYRENTER MYRENTER Integer 4 10 0 Median year householder moved into unit - Occupied Housing Units Renter - [B25039_E003] VEHICLE_0 VEHICLE_0 Integer 4 10 0 Occupied Housing Units with No vehicle available - [B25044_E003] + [B25044_E010] VEHICLE_1 VEHICLE_1 Integer 4 10 0 Occupied Housing Units with 1 vehicle available - [B25044_E004] + [B25044_E011] VEHICLE_2 VEHICLE_2 Integer 4 10 0 Occupied Housing Units with 2 vehicles available - [B25044_E005] + [B25044_E012] VEHICLE_3 VEHICLE_3 Integer 4 10 0 Occupied Housing Units with 3 vehicles available - [B25044_E006] + [B25044_E013] VEHICLE_4 VEHICLE_4 Integer 4 10 0 Occupied Housing Units with 4 vehicles available - [B25044_E007] + [B25044_E014] VEHICLE5G VEHICLE5G Integer 4 10 0 Occupied Housing Units with 5 or more vehicles available - [B25044_E008] + [B25044_E015] S_TOTAL S_TOTAL Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs Total - [B16004_E001] S_VERYWELL S_VERYWELL Integer 4 10 0 Ability 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_WELL S_WELL Integer 4 10 0 Ability 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_NOTWELL S_NOTWELL Integer 4 10 0 Ability 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_NOTATALL S_NOTATALL Integer 4 10 0 Ability 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_ENGLISH S_ENGLISH Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs Speak only English - [B16004_E003] + [B16004_E025] + [B16004_E047] S_SPANISH S_SPANISH Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs Speak Spanish - [B16004_E004] + [B16004_E026] + [B16004_E048] S_EUROPE S_EUROPE Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs Speak other Indo-European languages - [B16004_E009] + [B16004_E031] + [B16004_E053] S_ASIAN S_ASIAN Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs Speak Asian and Pacific Island languages - [B16004_E014] + [B16004_E036] + [B16004_E058] S_OTHER S_OTHER Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs Speak other languages - [B16004_E019] + [B16004_E041] + [B16004_E063] S_NOTVERYWELL S_NOTVERYWELL Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs, speak well, not well, or not at all - [s_well] + [s_notwell] + [s_notatall] S_NOT S_NOT Integer 4 10 0 Ability to Speak English for the Population 5+ Yrs, not well, or not at all - [s_notwell] + [s_notatall] HL_TOTAL HL_TOTAL Integer 4 10 0 Total Households by Household Language by Household Limited English Speaking Status - [C16002_E001] HL_ENGLISH HL_ENGLISH Integer 4 10 0 Households 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_L HL_SPAN_L Integer 4 10 0 Households that speak Spanish: Limited English speaking household - [C16002_E004] HL_EURO_L HL_EURO_L Integer 4 10 0 Households that speak Other Indo-European languages: Limited English speaking household - [C16002_E007] HL_ASIAN_L HL_ASIAN_L Integer 4 10 0 Households that speak Asian and Pacific Island languages: Limited English speaking household - [C16002_E010] HL_OTHER_L HL_OTHER_L Integer 4 10 0 Households that speak Other languages: Limited English speaking household - [C16002_E013] LABOR_CIV LABOR_CIV Integer 4 10 0 Civilian Employed Population 16 Years And Over Total - [C24010_E001] RTOTAL RTOTAL Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months. Total population for whom Poverty Status is Determined - [C17002_E001] RU50 RU50 Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months Under .50 - [C17002_E002] R50_99 R50_99 Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months .50 to .99 - [C17002_E003] R1_124 R1_124 Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months 1.00 to 1.24 - [C17002_E004] R125ABV R125ABV Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months 1.25 and over - [C17002_E005] + [C17002_E006] + [C17002_E007] + [C17002_E008] RU1 RU1 Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months under 1 - [RU50] + [R50_99] RU2ABV RU2ABV Integer 4 10 0 Ratio of Income to Poverty Level in the Past 12 Months 2.00 and over - [C17002_E008] DIS_TOTAL DIS_TOTAL Integer 4 10 0 Population 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_2064 DIS_2064 Integer 4 10 0 Population 20 to 64 Years with Income in the past 12 months below and above poverty level with a disability - [B23024_E003] + [B23024_E018] NO_DIS2064 NO_DIS2064 Integer 4 10 0 Population 20 to 64 Years with Income in the past 12 months below and above poverty level with No disability - [B23024_E010] + [B23024_E025] GMTOT GMTOT Integer 4 10 0 Geographical 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] GMSAME GMSAME Integer 4 10 0 Geographical 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] GMDIFF GMDIFF Integer 4 10 0 Geographical 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] GMABROAD GMABROAD Integer 4 10 0 Geographical 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_TOTAL C_TOTAL Integer 4 10 0 Types of Computers in Household. Total Households - [B28001_E001] C_COMPUTER C_COMPUTER Integer 4 10 0 Households 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_COMP C_NO_COMP Integer 4 10 0 Households that have No Computer - [B28001_E011] I_TOTAL I_TOTAL Integer 4 10 0 Presence and Types of Internet Subscriptions in Household. Total Households. - [B28002_E001] I_INTERNET I_INTERNET Integer 4 10 0 Households with an Internet Subscription. Includes: Dial-up, Cellular, Broadband, Satellite, or Other - [B28002_E002] I_NO_SUB I_NO_SUB Integer 4 10 0 Households with Internet Access without a Subscription - [B28002_E012] I_NO_NET I_NO_NET Integer 4 10 0 Households with no Internet Access - [B28002_E013] PCT_NOTWEL PCT_NOTWEL Double 8 38 8 Percent Ability to Speak English for the Population 5+ Yrs Speak English 'not well' - ([S_NOTWELL]/[S_TOTAL] * 100) PCT_NOTATA PCT_NOTATA Double 8 38 8 Percent Ability to Speak English for the Population 5+ Yrs Speak English 'not at all' - ([S_NOTATALL]/[S_TOTAL] * 100) DEN_NOTWEL DEN_NOTWEL Double 8 38 8 Density per acre of Ability to Speak English for the Population 5+ Yrs Speak English 'not well' - [S_NOTWELL]/[ACRES] DEN_NOTATA DEN_NOTATA Double 8 38 8 Density per acre of Ability to Speak English for the Population 5+ Yrs Speak English 'not at all' - [S_NOTATALL]/[ACRES] PCT_BACHLR PCT_BACHLR Double 8 38 8 Percent Educational Attainment for the Population 25 Years and over Bachelor's degree only - ([BACHELORS]/[TOTALPOP] * 100) PCT_POV PCT_POV Double 8 38 8 Percent Population with income in the past 12 months below poverty level - ([BELOW_POV]/[ABVE_BELW] * 100) PCT_RU50 PCT_RU50 Double 8 38 8 Percent Ratio of Income to Poverty Level in the Past 12 Months Under .50 - ([RU50]/[RTOTAL] * 100) PCT_R50_9 PCT_R50_9 Double 8 38 8 RPercent atio of Income to Poverty Level in the Past 12 Months .50 to .99 - ([R50_99]/[RTOTAL] * 100) PCT_R125AB PCT_R125AB Double 8 38 8 Percent Ratio of Income to Poverty Level in the Past 12 Months 1.25 and over - ([R125ABV]/[RTOTAL] * 100) PCT_RU1 PCT_RU1 Double 8 38 8 Percent Ratio of Income to Poverty Level in the Past 12 Months under 1 - ([RU1]/[RTOTAL] * 100) DEN_POP DEN_POP Double 8 38 8 Population per acre - [TOTALPOP]/[ACRES] DEN_WHITE DEN_WHITE Double 8 38 8 Density per acre of Persons White alone - [WHITE]/[ACRES] DEN_BLACK DEN_BLACK Double 8 38 8 Density per acre of Persons Black or African American alone - [BLACK]/[ACRES] DEN_AMERI DEN_AMERI Double 8 38 8 Density per acre of Persons American Indian and Alaska Native alone - [AMERI_ES]/[ACRES] DEN_ASIAN DEN_ASIAN Double 8 38 8 Density per acre of Persons Asian alone - [ASIAN]/[ACRES] DEN_HAWN DEN_HAWN Double 8 38 8 Density per acre of Persons Native Hawaiian and Other Pacific Islander alone - [HAWN_PI]/[ACRES] DEN_OTHER DEN_OTHER Double 8 38 8 Density per acre of Persons Some other race alone - [OTHER]/[ACRES] DEN_MULTI DEN_MULTI Double 8 38 8 Density per acre of Persons Two or more races - [MULT_RACE]/[ACRES] DEN_HISP DEN_HISP Double 8 38 8 Density per acre of Persons Hispanic or Latino - [HISPANIC]/[ACRES] DEN_DIS20 DEN_DIS20 Double 8 38 8 Density per acre of Population 20 To 64 Years With a disability - [DIS_2064]/[ACRES] PCT_WHITE PCT_WHITE Double 8 38 8 Percent of Persons White alone - ([WHITE] /[TOTALPOP] *100) PCT_BLACK PCT_BLACK Double 8 38 8 Percent of Persons Black or African American alone - ([BLACK] /[TOTALPOP] *100) PCT_AMERI PCT_AMERI Double 8 38 8 Percent of Persons American Indian and Alaska Native alone - ([AMERI_ES] /[TOTALPOP] *100) PCT_ASIAN PCT_ASIAN Double 8 38 8 Percent of Persons Asian alone - ([ASIAN] /[TOTALPOP] *100) PCT_HAWN PCT_HAWN Double 8 38 8 Percent of Persons Native Hawaiian and Other Pacific Islander alone - ([HAWN_PI] /[TOTALPOP] *100) PCT_OTHER PCT_OTHER Double 8 38 8 Percent of Persons Some other race alone - ([OTHER] /[TOTALPOP] *100) PCT_MULTI PCT_MULTI Double 8 38 8 Percent of Persons Two or more races - ([MULT_RACE] /[TOTALPOP] *100) PCT_HISP PCT_HISP Double 8 38 8 Percent of Persons Hispanic or Latino - ([HISPANIC] /[TOTALPOP] *100) PCT_DIS20 PCT_DIS20 Double 8 38 8 Percent Population 20 To 64 Years With a disability - ([DIS_2064]/[DIS_TOTAL] * 100) DESCRIPT GeoPlan added field based on GEOID GeoPlan DESCRIPT String 100 0 0 FGDLAQDATE The date GeoPlan acquired the data from the source. GeoPlan FGDLAQDATE Date 8 0 0 TIGERYEAR Source date for Tiger data (spatial portion of this layer) GeoPlan TIGERYEAR String 25 0 0 DATAYEAR Source Date of ACS data GeoPlan DATAYEAR String 25 0 0 AUTOID AUTOID Integer 4 10 Unique ID added by GeoPlan. This field is for historic tracking of features. 0 SHAPE.AREA SHAPE.AREA Double 0 0 Area of feature in internal units 0 SHAPE.LEN SHAPE.LEN Double 0 0 Length of feature in internal units 0 /9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDAREA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2+gAo AKACgBD0NAC0AFABQAUAFABQAUAFABQAnegBaACgAoAKACgAoAKACgAoARiQMgZ/GgDLvHkLbW+6 TuFNAVaYBQAUAFABQAUAFABQAUAFABQAUAb3Pr+lSAo6UAFABQAh6GgBaACgBM+xoAp3Opw2v345 TgnOF6Adz7e9AFzPsaAI5LiKJirlgQhfAUngdaAHq4ZQwzgjI4oAHkWNC7ZwBk8ZoAas8TPsDgtk jHfjGf5igBVkR2O1g2DtbHY0APoAKACgAoAKACgAoAKACgCOf/VE85x2oAxnZnclutUA2gAoAKAC gAoAKACgAoAKACgAoAKAN49KkBaACgAoARuhoAUkAEnoKAI4ZhMm8DAzigBzEqpIGfQe9AHI3Bjk mlvLkxuwKFh5Qx1+7kZ3Y46GghvU2dJl33U5ld5Lh8sxUNsRc8Lz35/SgpF6ylupYGa7gEL72CqD n5c8E9eaBjmuWW6MAgkI8syBx0JBxt+tADElu3wxiijVmXAdju24ycj1oAST7T8sqxxNKu8ABjgr 256Z4Xr70ARQyTWdugvC81xKWZjEhKr3wO4Hp/8AXoAuRSrKu5QwGSPmUj+dAD8igAyPUUALkeoo AKACgAoAKAGF8SKnOWBI+U449+3WgCC71C3slPnyBTtLAdeB3oE3Yyt275s5zzVDCgAoAKACgAoA KACgAoAKACgAoAKANmC4SdRggN3UmpAlFAEDXsK5y3IOMDmiwEY1GMuAVIX1p2Af9thIb5unT3os BHNdxyWr7Tg9MGgA0+RPK8vowOfrQwJ7mURwSMCu5VJAPTgUgOEt13fZ5Jbd3YO2Y9jOAP4Secjv zigxje70Okg1eVLOQpp2JQcqinaG+uR1+mfrRY0W2xBbarepeSXF5HKsboNtvEpkCn1yB16/nTGa sH26TUmlkZFtBGQqA8luOTx9e9IZZQeeoeaDays20Ng45IB/EfzoAlAAAAGAOgFAFDVbqSwsp54l ZpNhK8blDAcDGelAGLqN4bzUIoULLLFMsHmRu3G4HJC8AN8vfIxQBVk1m7uhdW7rHBESieem4uF+ c4b3wuOuBk80EybS0JNK16RrEFwnnlSnmG5Lc7jggYIwAep5J4xQNbGnHr7vL5a2gZRN5fmNKBkA kZxj72R09O/agZsK7eYUkiwCxCFeQRgcn05zQA0pJHLCsKqYizeZuJyM8gj8e3v7UATYH+TQBXmv ba3nSGWZY3YZG9sA846nvk0AUr3U7d1mtoLlRMACXVhhRk5/EbTx9KCJy5Vcr3A04yIJ75vPHyFn OdxIyRgjA6ZwMcUHIqtW97GfcatbW8c7hjOIQWJhA+ZQM5GT+FM64Sco3ZbjmjlLhCTsODwR+Xr0 P5UyySgAoAKACgAoAKACgAoAKACgAoAuG08mPfI5ByMbOaVwGiSeRHKu2xRg5oAq0wCgAoAKAHrK 6HKkA+oAoARpHc5ZifqaAG0AFABQAu59jKsjpkYyrYNAGVfS6va2LRQXTvGg3CTbvk45AOT69/Tt SE7rY6DQWnk07zp7iSZpmMg8xQCoOMAY4xSGaEMnnRh9jpkkYcYNAD6AKl0guFMcnlNasjBxuIbd njBHTvQBNHJG21QU3YztBzigBZpVgTeysRuA+UZPJxQA5iQQQVCj72fSgBvkxtOs/O8KVB3HGDg9 OnYUAVyl4uop5YhWy2neP4ix5z0/zk0AMvdLtr2bfM77iuwAMBxzkD/PagDJvdPt9OU3EMwLMvkL uBYhRxtz04Pr3oMpwv1ILIQX6OLi2lkePdnyXJRQVKnknJJyc+9Bjyz+yQ22lRPZf6VGDJMHEm1j ggnH8lFM6o7F+KCKDf5SBN7bmwT1pjJKACgAoAKACgAoAKACgAoAKACgDfqQKTywwh41XGeo9aYG ceSaYCUAFABQAUAFABQAUAFABQAUASJfSWrI21pIshGVR90HuOMn/CkwNl9oGXxjrzSAqzahGgia ICZH/iRhgD196AKc84mJPlhW9R6f5NMCEEg5BwaYF+0vGZxHIc56GkwL/WkA1yqLuZtiryT0GKAM vUdch0mdUuElYytiNVQdABk5z0yR6UA2S2N9DdwXFzDyB/EMFjxnBA546YIzQFywttFLAI5QZWTI LuPmBI5wcD16igCOTTbbyp1XdEJiC5VuMj2PFAmrqxnXvnRav5TBjbtCpjJ6AgkFfr0P400MSmAU AFABQAUAFABQAUAFABQAUAFAGlHfrI211wCP1pWAqzQEEtHllPPTpQBXIx1pgFABQAUAFABQAUAF ABQAUAFACqxRgynBFACXZe6h2MwDDkMRuwfXB79aQDIYhDEIwzMB3Y0wH0AFAADg5FAGlYuG3M0r GRuNrMccegpMBNRvG0+2SXYZVMgD8chT1PA7CkBk67b3bXmnTRyRmaNTuCsFZzuXIUE9xnrQJ7o0 YLRUuvtbygCQ5jCqBjIAAYg4PoP60CUbO5ajS7MUfmzRiRXy5jTh1z0wTxxigop36GNrhhJcyl0A ERIEanPGCRjPp70CZhvrX7+SO4mlzGUVIHj+YtjkdM7jnI7GghykmkaIIYAg5B5FUaC0AFABQAUA FABQAUAFABQAUAFACglTkEg+1AEsFw0MhbG7I9aQFi4CNbK7cSE596AKNMAoAKACgAoAKACgAoAK ACgAoAKACgAoAKACgBVYqwYdRyDQBrwXUcyfeUN3UnmpAh1BQtk0rzrE6HKzbM7cnsP0oBkBvbDT 7QxyXbMEAYsZCWOenPqfT+lAr2LFnfQanBK0DHarFCQw9Acggn1oBO4TxNDprxrNKzgfK5I3Fs8D OMdeOlAWMnVLGa4U36iOCcQbGHUxsTkMSPTg+uKCZL7RVsLrzA0MkqPKhOGD7tw+pAzjvTQQldal 2mWFABQAUAFABQAUAFABQAUAFABQAoODmgAJJ6mgBKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA KACgBMDOcDPrQA8XxsrWSS9uHmjKlQnlDHTgZHr05qRbbmRplqNWsTbxTKJ7dywywzgnGMFTxwOc cEfU0EK8kXJLyKLxELRnnhld0LSJKCpO3dtKn+E4IBHegq6vY1YtUS+untrORQRCsiu6HkE9gcZ4 x+YoKMu5vLq015GZgUEJ+1Js+VuRggDPOCBk8cYzQS5WdiO80u607UjdxfvLJ/vqMlgxJwQP+BHp QLls7lyqLCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo AKACgBJo4JrZkuLjyVX5wSePfI7jHWkyZJNWZJYiI36JbXUM5t4AkhV/mIOSuRzx070gSZyOradf 20ReeyYOJRuuUG4dDj3xzjJ7cdaAcdSqlxCLZZbRWW4hnB86Tgy9CUwM9CPUDj1oGPj1LULy+l1N 4cTsuYlhdmbIjz8q9+PyJNBLfU37bXru4091ACtFJw7SE/KO+4ryo7sfagbemhuTRI8CXUTAo4Bw O2aaKK1MAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKA CgDPuGWbU4o41aWaLH7vcu3kHqCOvy5zSZE48ysTy/2baaS0sUQknmEgJMojJ4wx64AGMD0wBSBN RidLFjyUC8rtGOc0FnLeILCEX4Z4owlwyruzgqemR6en4igzlfmVjLsrA+azMYoZ5pl+ztKSxb/g JycHGCSBjBoCzv5HZTabH/Z9zb24WNplwSwLDpgcelBaSWxzGjXdzCX02WRcxMyuu0DOCQMHrjj0 pomN02a1MsKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAC gBGJCkhSxAyAOpoA5WPVHSSURPPHPPGGZhKVAYgbehwTgcc9xx2qTF861LtvdxfaAt/88DKnyLll YFcEngnIX3x160CppXuTXGs3LwyWduVtoQBEiyMM4AHRs5xhsnjtjNBpzapGNY3V7catBbmTzp32 rJ5hLbwP4S3IPHzZ6ZPX0Ad2rHoltaACOSeNDLHkR8ZKKe2e59/8kHFNJX3LlBRx9xa3C6/LeTFG PnFVAyWSPGOe2OVb25oMnO07M0ao1CgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA KACgAoAKACgAoAKACgAoAKAOf0zRoYZ7hpUVp7Z4hbjnDFQNv8XoOfr7VJjOUlNRXUsCza71JLeS 1ePewRgGK4VQBkjJzwBQOz5rHRNoVhHA8MUSReajIWJJbkD1+lBqYkvh6SPS4p4orc3sTCXMYXLn cMkHGMYzj60ERg073Opg+0Mxkl2qrKMRjnae/PegsldtgBCs3IGF9z1oA5vxHZzyTtcLZrPEsYX5 zkKe7DByCPpQS7lfSr5ryGQSFDLE+0lOhHY/jzTQ0y/TGFABQAUAFABQAUAFABQAUAFABQAUAFAB QAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBk6tdX1pIjWoiTcVCzMuShz07/8A6s0mJux0enar FekgTQSKAAJI24Y9Dx25/lSEpXbQayQkdvNtRmjmBUNnjg5I+g5596Ak7K4kVnbX1vCTc/aY0VkJ XGHB9cD+WKB2TdyfS45oNPiguGBkjBX6qCQp/ICgZcoAKAON+2w/2/ciGHbFMNyNtHzlc7sHPrng +nvTRDkk2afUZFMsKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACg AoAKACgCOeFbiFonJAPdTgg+oPY0A1cg0K4soNPFjcqpltJ8LlwWZieCATn09qkm6SuzoDKLuGZI gBIowPMAIBxwe9ARkpK6J4lKxKGChsDdtGBnvigoURoJGkCgOwALY5IHT+ZoAJM7DtBJPHBxQBXd EttNaOaeVkSMq0pyXx0zwOvvQBjXui/2jaWb2F58sByhbGDgcZGOeRigzVOKd0ELK0Q2RtGB8uxl wVxxjFUaElABQAUAFABQAUAGDQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQA UAFAFOXT1n1K3uMxgK6lww64I5yPp/nmkxNa3LWnxx2WpTzS3qJbRoFVC4UAknkj3AHXuDSFFctz b+12wXcZ4gM4zuFA7q1yNNSs5PM2XMbiL75U5C+2fX2oC6JjMi7d5ADttTn7xoGNeVxcxxKqlSCz MWHGPQdTQBl+Irz7LZxwRu0TytkMpK4CkEjI6E0ETdloYuj74pbu1aR5PLcEO5yWzwTnJ7qT+NNB TlzK7NWmWFABgmgB8cZlfYOp6UASfY592PLP1pXAGtXRSzMgwOm7mi4EQdwMBjj60wJCsT4Icrxy Md6QENMAoAKACgAoAKACgAoAKAEbO07euOKAI8yAcKfxIoAAZAhPVs8CgB0ZY7i3rwKAH0AFABQA UAFABQAUAFABQAhOFJwTgdBQBgvJm2ntRC1x57j7PvwvcZG489MD86kwlHmkmmaWn6XDcGe7CRXT SSD7khJVcg4bd16dz2oD2ctLPY6OGGz8p4IUjMYOWQcgHNBto9Bba1W28wK7FWbIU9F9hQCVhq6d aJdi7WBBOF2hx6UDEvNOtr7aZkBKggHAJwfqDQTKKluczY24g1fUPKkZ4SwwXfce4656cd+efxpo FuzSplBQAqsVORQBPHcLEpKRgSH+InpSAjeaSQ5ZyfbNMCOgAoAKACgAoAKACgAoAKACgAoAKAEJ wCetAEQeVSAyZ6DIoAcJGIB2H6UAORiy5IxQA6gAoAKACgAoAKACgAoAKACgCJraF1kDRJ+8GG46 0AO0Iv8AaJ0g+RUXYVZflJVioOfXA9hyOOKkmMeXY2ra1FvLcSbgTK+7gYxx0oGkWKBhQBheI9R+ zWgjglkFzuOFhPzcKT6fSgiUrLczNHklntTNMGDtjhhjjaD69CST+NNBDY0aZYUAFABQAUAFABQA oUnoDQAlABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAOspVt7/mEqpUj erHHJzyOnUH35pC6m0ksbsVV1LAZwD2pDH0AMlkSGJ5ZG2oilmPoB1oA4jxVeQW+oYEjSeagkbaz AIpGB/EASdpOPagynC7uO0C5jGnDzTDDKzljGDtxzgYB57U0XHY10cOu5TkUyh1ABQAUAFABQApB BwRQAmT60AFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAE1vL5Uuc 4zwT6UgNkdPWkBHPEJ7eWFiQJEKkjtkYoA4TVNOf/hIxaBZWiUCVWRvuLhhgnHGAcD6D1oIkm9i8 mjQ7BvZy5B3NnuQ4/wDZz+Qp2LNBEWNdq9OaYDqACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAC gAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA1IbjZFEsoILDhqQFukBh30Nlp0jyRRFrm8k6g 5yeSfoOppoQymMKACgAoAKACgB5ikVdxU4xnNAFX7bb+bJF5nzxuqMNp4LdP50ASCWNhkSIR7GgB 9ABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBOl3LHGEBGB6ikBH LeOkRMkxCDqSaAKkIkmkFxNkYBEUZH3AepPucCgCxTAKACgAoAKACgDWgjL2IRu471PUDnLjShJd mUyFHEyycL2Xblfx2imAQabHErea4mdjks6Z7AdyfSiwF2mAUAFABQAUAFABQAUAFABQAUAFABQA UAFABQAUAFABQAUAFABQAUAFAB1oAg+1xeesPO4syZxwGHUfXFABLLMJRHFATxkyMcKP6k0ASNGr sjOAWXkegPrQA+gAoAKACgAoAKAJ7WHzpOcYHOPWkwNdc7RkYOOlIDJvraZd8ocli45PQDFNAZTp c5HDngZIPfHP8QoAu0wCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAgaE pI0qvIWYggbshceg7UAOZ5cE7dxoAXMmenH/ANegCSgAoAKACgAoAKACgBVZkYMpII7igC/bXxJK y8nsRSsAStJcl1AcLj5Vx/OgDPPBpgFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQ AUAFABQAUARiXc4VR35JoAQykYJGATigAMwAztNACpJubbjnGTQBJQAUAFABQAUAFABQAA4ORQBp Wz/aIWjOd38RzSAiu7f99lRgEDtQgP/Z Simple FALSE 956 TRUE FALSE