3 datasets found
  1. Synthetic population for USA_ALABAMA

    • zenodo.org
    • explore.openaire.eu
    bin, pdf, zip
    Updated Jul 16, 2024
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    Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie; Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie (2024). Synthetic population for USA_ALABAMA [Dataset]. http://doi.org/10.5281/zenodo.6505866
    Explore at:
    pdf, zip, binAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie; Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Alabama, United States
    Description

    Synthetic populations for regions of the World (SPW) | Alabama

    Dataset information

    A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).

    License

    CC-BY-4.0

    Acknowledgment

    This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).

    Contact information

    Henning.Mortveit@virginia.edu

    Identifiers

    Region nameAlabama
    Region IDusa_140002904
    Modelcoarse
    Version0_9_0

    Statistics

    NameValue
    Population4768478
    Average age37.8
    Households1933164
    Average household size2.5
    Residence locations1933164
    Activity locations398709
    Average number of activities5.7
    Average travel distance65.0

    Sources

    DescriptionNameVersionUrl
    Activity template dataWorld Bank2021https://data.worldbank.org
    Administrative boundariesADCW7.6https://www.adci.com/adc-worldmap
    Curated POIs based on OSMSLIPO/OSM POIshttp://slipo.eu/?p=1551 https://www.openstreetmap.org/
    Household dataIPUMShttps://international.ipums.org/international
    Population count with demographic attributesGPWv4.11https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11

    Files description

    Base data files (usa_140002904_data_v_0_9.zip)

    FilenameDescription
    usa_140002904_person_v_0_9.csvData for each person including attributes such as age, gender, and household ID.
    usa_140002904_household_v_0_9.csvData at household level.
    usa_140002904_residence_locations_v_0_9.csvData about residence locations
    usa_140002904_activity_locations_v_0_9.csvData about activity locations, including what activity types are supported at these locations
    usa_140002904_activity_location_assignment_v_0_9.csvFor each person and for each of their activities, this file specifies the location where the activity takes place

    Derived data files

    FilenameDescription
    usa_140002904_contact_matrix_v_0_9.csvA POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.

    Validation and measures files

    FilenameDescription
    usa_140002904_household_grouping_validation_v_0_9.pdfValidation plots for household construction
    usa_140002904_activity_durations_{adult,child}_v_0_9.pdfComparison of time spent on generated activities with survey data
    usa_140002904_activity_patterns_{adult,child}_v_0_9.pdfComparison of generated activity patterns by the time of day with survey data
    usa_140002904_location_construction_0_9.pdfValidation plots for location construction
    usa_140002904_location_assignement_0_9.pdfValidation plots for location assignment, including travel distribution plots
    usa_140002904_usa_140002904_ver_0_9_0_avg_travel_distance.pdfChoropleth map visualizing average travel distance
    usa_140002904_usa_140002904_ver_0_9_0_travel_distr_combined.pdfTravel distance distribution
    usa_140002904_usa_140002904_ver_0_9_0_num_activity_loc.pdfChoropleth map visualizing number of activity locations
    usa_140002904_usa_140002904_ver_0_9_0_avg_age.pdfChoropleth map visualizing average age
    usa_140002904_usa_140002904_ver_0_9_0_pop_density_per_sqkm.pdfChoropleth map visualizing population density
    usa_140002904_usa_140002904_ver_0_9_0_pop_size.pdfChoropleth map visualizing population size

  2. a

    2021 Population Density by Urbanized Area

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gis-fdot.opendata.arcgis.com
    • +2more
    Updated Aug 9, 2023
    + more versions
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    Florida Department of Transportation (2023). 2021 Population Density by Urbanized Area [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/fdot::2021-population-density-by-urbanized-area
    Explore at:
    Dataset updated
    Aug 9, 2023
    Dataset authored and provided by
    Florida Department of Transportation
    Area covered
    Description

    Each year, the Forecasting and Trends Office (FTO) publishes population estimates and future year projections. The population estimates can be used for a variety of planning studies including statewide and regional transportation plan updates, subarea and corridor studies, and funding allocations for various planning agencies. The 2021 population estimates are based on the population estimates developed by the Bureau of Economic and Business Research (BEBR) at the University of Florida. BEBR uses the decennial census count for April 1, 2020, as the starting point for state-level projections. More information is available from BEBR here. This dataset contains boundaries for all 2010 Census Urbanized Areas (UAs) in the State of Florida with 2021 population density estimates. All legal boundaries and names in this dataset are from the US Census Bureau’s TIGER/Line Files (2021). BEBR provides 2021 population estimates for counties in Florida. However, UA boundaries may not coincide with the jurisdictional boundaries of counties and UAs often spread into several counties. To estimate the population for an UA, first the ratio of the subject UA that is contained within a county (or sub-area) to the area of the entire county was determined. That ratio was multiplied by the estimated county population to obtain the population for that sub-area. The population for the entire UA is the sum of all sub-area populations estimated from the counties they are located within. For the 2010 Census, urban areas comprised a “densely settled core of census tracts and/or census blocks that meet minimum population density requirements, along with adjacent territory containing non-residential urban land uses as well as territory with low population density included to link outlying densely settled territory with the densely settled core.” In 2010, the US Census Bureau identified two types of urban areas—UAs and Urban Clusters (UCs). UAs have a population of 50,000 or more people. Note: Pensacola, FL--AL Urbanized Area is located in two states: Florida (Escambia County and Santa Rosa County) and Alabama (Baldwin County). 2021 population of Baldwin County, AL used for this estimation is from the US Census annual population estimates (2020-2021). All other Urbanized Areas are located entirely within the state of Florida. Please see the Data Dictionary for more information on data fields. Data Sources:FDOT FTO 2020 and 2021 Population Estimates by Urbanized Area and CountyUS Census Bureau 2020 Decennial CensusUS Census Bureau’s TIGER/Line Files (2021)Bureau of Economic and Business Research (BEBR) – Florida Estimates of Population 2021 Data Coverage: StatewideData Time Period: 2021 Date of Publication: October 2022 Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

  3. d

    2016 Cartographic Boundary File, 2010 Urban Areas (UA) within 2010 County...

    • datadiscoverystudio.org
    • data.wu.ac.at
    html, zip
    Updated Jun 5, 2017
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    (2017). 2016 Cartographic Boundary File, 2010 Urban Areas (UA) within 2010 County and Equivalent for Alabama, 1:500,000. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/39d328dabf7f4529bc15b96638aaf3ac/html
    Explore at:
    html, zipAvailable download formats
    Dataset updated
    Jun 5, 2017
    Description

    description: The 2016 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.; abstract: The 2016 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.

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Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie; Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie (2024). Synthetic population for USA_ALABAMA [Dataset]. http://doi.org/10.5281/zenodo.6505866
Organization logo

Synthetic population for USA_ALABAMA

Explore at:
pdf, zip, binAvailable download formats
Dataset updated
Jul 16, 2024
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie; Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Alabama, United States
Description

Synthetic populations for regions of the World (SPW) | Alabama

Dataset information

A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).

License

CC-BY-4.0

Acknowledgment

This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).

Contact information

Henning.Mortveit@virginia.edu

Identifiers

Region nameAlabama
Region IDusa_140002904
Modelcoarse
Version0_9_0

Statistics

NameValue
Population4768478
Average age37.8
Households1933164
Average household size2.5
Residence locations1933164
Activity locations398709
Average number of activities5.7
Average travel distance65.0

Sources

DescriptionNameVersionUrl
Activity template dataWorld Bank2021https://data.worldbank.org
Administrative boundariesADCW7.6https://www.adci.com/adc-worldmap
Curated POIs based on OSMSLIPO/OSM POIshttp://slipo.eu/?p=1551 https://www.openstreetmap.org/
Household dataIPUMShttps://international.ipums.org/international
Population count with demographic attributesGPWv4.11https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11

Files description

Base data files (usa_140002904_data_v_0_9.zip)

FilenameDescription
usa_140002904_person_v_0_9.csvData for each person including attributes such as age, gender, and household ID.
usa_140002904_household_v_0_9.csvData at household level.
usa_140002904_residence_locations_v_0_9.csvData about residence locations
usa_140002904_activity_locations_v_0_9.csvData about activity locations, including what activity types are supported at these locations
usa_140002904_activity_location_assignment_v_0_9.csvFor each person and for each of their activities, this file specifies the location where the activity takes place

Derived data files

FilenameDescription
usa_140002904_contact_matrix_v_0_9.csvA POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.

Validation and measures files

FilenameDescription
usa_140002904_household_grouping_validation_v_0_9.pdfValidation plots for household construction
usa_140002904_activity_durations_{adult,child}_v_0_9.pdfComparison of time spent on generated activities with survey data
usa_140002904_activity_patterns_{adult,child}_v_0_9.pdfComparison of generated activity patterns by the time of day with survey data
usa_140002904_location_construction_0_9.pdfValidation plots for location construction
usa_140002904_location_assignement_0_9.pdfValidation plots for location assignment, including travel distribution plots
usa_140002904_usa_140002904_ver_0_9_0_avg_travel_distance.pdfChoropleth map visualizing average travel distance
usa_140002904_usa_140002904_ver_0_9_0_travel_distr_combined.pdfTravel distance distribution
usa_140002904_usa_140002904_ver_0_9_0_num_activity_loc.pdfChoropleth map visualizing number of activity locations
usa_140002904_usa_140002904_ver_0_9_0_avg_age.pdfChoropleth map visualizing average age
usa_140002904_usa_140002904_ver_0_9_0_pop_density_per_sqkm.pdfChoropleth map visualizing population density
usa_140002904_usa_140002904_ver_0_9_0_pop_size.pdfChoropleth map visualizing population size

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