- Population
The population density of Alafaya, FL was 2,169 in 2013. The population density of Town, FL was 3,628 in 2013.
Population Density
Population Density is computed by dividing the total population by Land Area Per Square Mile.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Population Datasets Involving Town, FL or Alafaya, FL
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GRU Customer Electric Consumption 2012-2022
data.cityofgainesville.org | Last Updated 2023-05-23T14:43:38.000ZData is provided by Gainesville Regional Utilities
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Stormwater_Features
data.cityofgainesville.org | Last Updated 2024-04-10T19:07:06.000ZFor NPDES Stormwater sewer system enhanced mapping project. Contains a GIS polygon feature class of stormwater basins in Gainesville, FL as a result of the NPDES stormwater system mapping project. This feature does not participate in the GIS network, and is for cartographic purposes only. This file is current only up to 02/04/08 and may be incomplete, and only covers those areas of Gainesville, FL that have been mapped up to 02/04/08. The file is also subject to constant updating as project progresses. This feature class is for informational purposes only. Do not rely on this file for accuracy of dimensions, size or location. The City of Gainesville does not assume responsibility to update this information for any error or omission in this file. This shapefile may indicate the zoning/land use on the properties as shown. Do not rely on this file for accuracy of dimensions. For specific information, contact the City of Gainesville, Florida.
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Homeless Survey Zones_data
data.cityofgainesville.org | Last Updated 2024-04-10T19:07:07.000ZHomeless Survey Zones as defined by: Theresa Theresa Lowe, Executive Director tlowe@gracemarketplace.org North Central Florida Coalition for the Homeless and Hungry Operating GRACE Marketplace 3055 NE 28th Drive Gainesville, FL 32609 (352) 792-0800, ext. 105 www.gracemarketplace.org
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Public Housing
data.bayareametro.gov | Last Updated 2021-12-10T20:13:08.000ZThe feature set indicates the locations, and tenant characteristics of public housing development buildings for the San Francisco Bay Region. This feature set, extracted by the Metropolitan Transportation Commission, is from the statewide public housing buildings feature layer provided by the California Department of Housing and Community Development (HCD). HCD itself extracted the California data from the United States Department of Housing and Urban Development (HUD) feature service depicting the location of individual buildings within public housing units throughout the United States. According to HUD's Public Housing Program, "Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. There are approximately 1.2 million households living in public housing units, managed by some 3,300 housing agencies. HUD administers federal aid to local housing agencies that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments. HUD administers Federal aid to local Housing Agencies (HAs) that manage housing for low-income residents at rents they can afford. Likewise, HUD furnishes technical and professional assistance in planning, developing, and managing the buildings that comprise low-income housing developments. This feature set provides the location, and resident characteristics of public housing development buildings. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information, the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. HCD downloaded the HUD data