The population density of Cross Plains, WI was 2,011 in 2009.

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 - Notes:

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Geographic and Population Datasets Involving Cross Plains, WI

  • API

    Internet Master Plan: Adoption and Infrastructure Data by Neighborhood

    data.cityofnewyork.us | Last Updated 2022-09-23T19:23:10.000Z

    Key indicators of broadband adoption, service and infrastructure in New York City.</p> <b>Data Limitations:</b> Data accuracy is limited as of the date of publication and by the methodology and accuracy of the original sources. The City shall not be liable for any costs related to, or in reliance of, the data contained in these datasets.

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    Broadband Adoption Basic Indicators

    data.cityofnewyork.us | Last Updated 2022-09-23T19:23:10.000Z

    Key indicators of broadband adoption, service and infrastructure in New York City by NTA.

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    LinkNYC Kiosk Locations

    data.cityofnewyork.us | Last Updated 2024-09-10T20:12:43.000Z

    LinkNYC is the City’s program to provide free high-speed Wi-Fi, nationwide calling, a dedicated 911 button, charging ports for mobile devices, and access to social services. The City has recently begun to roll out a new and improved design of the original LinkNYC kiosk: Link5G. This new design will provide all of the amenities of LinkNYC kiosks, with the added benefit of 4G and 5G connectivity to enhance mobile telecommunications networks. This dataset lists locations for LinkNYC kiosks plus four public payphones in the five boroughs.

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    Strategic Measure_EOA.C.6 Number and percentage of residents that are living in an area considered to be a Complete Community

    datahub.austintexas.gov | Last Updated 2024-06-03T17:02:20.000Z

    This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. A resident in a complete community is someone residing in an area that is within a 20 minute walk to multiple essential destinations. Calculation method: This study measured the distance and time it takes for a pedestrian to reach five essential destination, or "indicators," from any point across the city using the existing network of sidewalks and crossings within a 20-minute walk time. Using GIS software, this evaluation resulted in a rasterized overlay of geographic outlines of “walksheds” surrounding each indicator destination. Residential estimates were found using an internal database of residential housing units and applied density assumptions and should not be compared to other demographic datasets. Data was sourced from City of Austin, CapMetro, and Austin ISD. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/rw4g-mrjp

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    Iowa Geographic Names

    mydata.iowa.gov | Last Updated 2024-09-20T22:00:21.000Z

    This dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names. The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.

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    Utah Census Data Cities 2009-2013

    opendata.utah.gov | Last Updated 2019-02-11T22:36:06.000Z

    Data derived from Population Estimates, American Community Survey, Census of Population and Housing, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits

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    Library Services

    data.montgomerycountymd.gov | Last Updated 2023-07-26T17:02:11.000Z

    Demographic and asset information of public libraries Update Frequency: Annual

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    Census Tracts 2010 Centroids

    data.bayareametro.gov | Last Updated 2021-11-19T16:27:25.000Z

    Centroid of 2010 census tracts. Provides 2010 census tracts for the San Francisco Bay Region, clipped by the Metropolitan Transportation Commission to remove major coastal and bay water areas. 2010 Census tracts for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from, and clipped using, California 2018 TIGER/Line shapefiles by the Metropolitan Transportation Commission. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and are reviewed and updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP). The Census Bureau updates census tracts in situations where no local participant existed or where local or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data. Census tracts generally have a population size between 1,200 and 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix; for example, 1457.02. The census tract numbers (used as names) eliminate any leading zeroes and append a suffix only if required. The 6-character numeric census tract codes, however, include leading zeroes and have an implied decimal point for the suffix. Census tract codes range from 000100 to 998999 and are unique within a county or equivalent area. The Census Bureau assigned a census tract code of 9900 to represent census tracts delineated to cover large bodies of water. In addition, census tract codes in the 9400s represent American Indian Areas and codes in the 9800s represent special land use areas. The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes. Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

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    MTA Transit Oriented Development (TOD) Data

    opendata.maryland.gov | Last Updated 2024-03-25T15:38:10.000Z

    *** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. *** This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. ** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.