{
 "culture": "en-US",
 "name": "Hillsborough_Census_2022",
 "guid": "4BE147E0-C681-45C7-955D-C589E9E8B368",
 "catalogPath": "",
 "snippet": "This dataset contains the US Census Bureau 2020 Census Block Groups for Hillsborough County with selected fields from the 2018-2022 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.\n\nParent layer: cenacs_2022",
 "description": "<DIV STYLE=\"text-align:Left;\"><DIV><DIV><P><SPAN>This dataset contains the US Census Bureau 2020 Census Block Groups for the State of Florida with selected fields from the 2018-2022 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>",
 "summary": "This dataset contains the US Census Bureau 2020 Census Block Groups for Hillsborough County with selected fields from the 2018-2022 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.\n\nParent layer: cenacs_2022",
 "title": "Hillsborough Census 2022",
 "tags": [
  "socioeconomic",
  "education",
  "housing",
  "boundaries",
  "Florida",
  "block group",
  "population",
  "society",
  "economic"
 ],
 "type": "Feature Service",
 "typeKeywords": [
  "Data",
  "Service",
  "Feature Service",
  "ArcGIS Server",
  "Feature Access",
  "providerSDS"
 ],
 "thumbnail": "thumbnail/thumbnail.png",
 "url": "",
 "extent": [
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   24.3546930728241
  ],
  [
   -79.8122130656807,
   31.0426406600837
  ]
 ],
 "minScale": 0,
 "maxScale": 1.7976931348623157E308,
 "spatialReference": "NAD_1983_HARN_Florida_GDL_Albers",
 "accessInformation": "",
 "licenseInfo": "<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>"
}