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Sub Layers:
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• People and Parcels
• Schools and Parks
• Heating and Flooding
• Surfaces
• City-Specific Data
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Layer: Boundaries (23)

Sub Layers:
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• Urban Areas
• Expanded Metro Areas
• All Municipalities
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Layer: Core Municipalities (3)

Parent Layer: Boundaries

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Layer: Urban Areas (1)

Parent Layer: Boundaries

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Layer: Expanded Metro Areas (89)

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Layer: All Municipalities (2)

Parent Layer: Boundaries

Name: All Municipalities

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Layer: People and Parcels (24)

Sub Layers:
• Land Parcels & Ownership
• Health Statistics
• Demographics and Equity
• Sidewalks (not available for all cities)
• City-Owned Property (not available for all cities)
• Historic redlining
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Layer: Land Parcels & Ownership (4)

Parent Layer: People and Parcels

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Layer: Health Statistics (13)

Parent Layer: People and Parcels

Name: Health Statistics

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Description: This dataset provides eight feature classes. The base feature class is called CensusTracts_tr and isn't generalized. The weighted centroids feature class is called CensusTracts_tr_cent. The centroids are weighted by the U.S. Block Centroids population distribution. Use the weighted centroids in report aggregation and spatial overlay operations. The CensusTracts_tr and CensusTracts_tr_cent feature classes contain all the attributes. There are six generalized boundaries feature classes and called: CensusTracts_tr_gen2, CensusTracts_tr_gen3, CensusTracts_tr_gen4, CensusTracts_tr_gen5, CensusTracts_tr_gen6 and CensusTracts_tr_gen7. These generalized features classes are provided to be used in mapping applications where very detailed feature classes can slow down performance.

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Copyright Text: Esri; U.S. Census Bureau

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Spatial Reference: 102100  (3857)  LatestVCSWkid(0)



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Layer: Demographics and Equity (18)

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Layer: Sidewalks (not available for all cities) (25)

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Layer: Parks (8)

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Description: Extent The ParkServe database maintains an inventory of parks for every urban area in the U.S., including Puerto Rico. This includes all incorporated and Census-designated places that lie within any of the country’s 3,000+ census-designated urban areas. This totals to over 15,000 cities, towns, or villages included in the database, which represents about 75% of the U.S. population. Parks Database Trust for Public land compiled the ParkServe database from 2016 to 2018. TPL contacted each city or town to request parks data, as well as searched for GIS parks data resources on municipal and regional open data websites. If no GIS data were available, we delineated park boundaries based on satellite imagery, and confirmed public access via city park websites or signage viewable through Google Street View. Cities and towns were given the opportunity to confirm our delineated boundaries. Today, there are about 145,000 parks in the ParkServe database. Parks data for the 100 largest cities are updated annually as part of the ParkScore Index, and parks data for all other places are updated on a monthly basis following TPL verification of public submissions via the ParkReviewer tool. How do we define a park? In order to accurately represent park access across large communities, open public access is the key criteria for inclusion in our database. We include a wide variety of parks, trails, and open space, so long as there is no barrier to entry. Examples of parks we include: Publicly-owned local, state, and national parks, trails, and open space School with a joint-use agreement with the local government. Privately-owned parks that are managed for full public use Examples of parks we don’t include: Parks in gated communities Private golf courses Private cemeteries School parks/playgrounds without active joint-use agreements Zoos, museums, professional sports stadiums For field descriptions, see https://www.tpl.org/park-data-downloads

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Layer: Tree Equity Score (lower - more need for trees) (14)

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Description: This dataset contains 2018 Florida Roads derived from the Census Bureau's TIGER/Line data (All Lines County-based Shapefiles). The TIGER/Line Shapefiles are an extract of selected geographic and cartographic information from the Census MAF/TIGER database. The Census MAF/TIGER database 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 the shapefiles can be combined to cover the whole nation. The GeoPlan Center obtained the 2018 TIGER/Line data from the Census Bureau and extracted the roads network from the Census Bureau's MAF/TIGER county-based files. GeoPlan formatted the statewide roads dataset so that it may be used as a reference dataset in an address locator file, see the supplemental information section for more information on creating locator files. Please Note: This roads data layer is Not used in the FDOT ETDM project. This layer is an update to the FGDL layer TIGER_ROADS_2011.shp.

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