Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
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 name | Alabama |
Region ID | usa_140002904 |
Model | coarse |
Version | 0_9_0 |
Statistics
Name | Value |
---|---|
Population | 4768478 |
Average age | 37.8 |
Households | 1933164 |
Average household size | 2.5 |
Residence locations | 1933164 |
Activity locations | 398709 |
Average number of activities | 5.7 |
Average travel distance | 65.0 |
Sources
Description | Name | Version | Url |
---|---|---|---|
Activity template data | World Bank | 2021 | https://data.worldbank.org |
Administrative boundaries | ADCW | 7.6 | https://www.adci.com/adc-worldmap |
Curated POIs based on OSM | SLIPO/OSM POIs | http://slipo.eu/?p=1551 https://www.openstreetmap.org/ | |
Household data | IPUMS | https://international.ipums.org/international | |
Population count with demographic attributes | GPW | v4.11 | https://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)
Filename | Description |
---|---|
usa_140002904_person_v_0_9.csv | Data for each person including attributes such as age, gender, and household ID. |
usa_140002904_household_v_0_9.csv | Data at household level. |
usa_140002904_residence_locations_v_0_9.csv | Data about residence locations |
usa_140002904_activity_locations_v_0_9.csv | Data about activity locations, including what activity types are supported at these locations |
usa_140002904_activity_location_assignment_v_0_9.csv | For each person and for each of their activities, this file specifies the location where the activity takes place |
Derived data files
Filename | Description |
---|---|
usa_140002904_contact_matrix_v_0_9.csv | A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model. |
Validation and measures files
Filename | Description |
---|---|
usa_140002904_household_grouping_validation_v_0_9.pdf | Validation plots for household construction |
usa_140002904_activity_durations_{adult,child}_v_0_9.pdf | Comparison of time spent on generated activities with survey data |
usa_140002904_activity_patterns_{adult,child}_v_0_9.pdf | Comparison of generated activity patterns by the time of day with survey data |
usa_140002904_location_construction_0_9.pdf | Validation plots for location construction |
usa_140002904_location_assignement_0_9.pdf | Validation plots for location assignment, including travel distribution plots |
usa_140002904_usa_140002904_ver_0_9_0_avg_travel_distance.pdf | Choropleth map visualizing average travel distance |
usa_140002904_usa_140002904_ver_0_9_0_travel_distr_combined.pdf | Travel distance distribution |
usa_140002904_usa_140002904_ver_0_9_0_num_activity_loc.pdf | Choropleth map visualizing number of activity locations |
usa_140002904_usa_140002904_ver_0_9_0_avg_age.pdf | Choropleth map visualizing average age |
usa_140002904_usa_140002904_ver_0_9_0_pop_density_per_sqkm.pdf | Choropleth map visualizing population density |
usa_140002904_usa_140002904_ver_0_9_0_pop_size.pdf | Choropleth map visualizing population size |
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
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.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
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 name | Alabama |
Region ID | usa_140002904 |
Model | coarse |
Version | 0_9_0 |
Statistics
Name | Value |
---|---|
Population | 4768478 |
Average age | 37.8 |
Households | 1933164 |
Average household size | 2.5 |
Residence locations | 1933164 |
Activity locations | 398709 |
Average number of activities | 5.7 |
Average travel distance | 65.0 |
Sources
Description | Name | Version | Url |
---|---|---|---|
Activity template data | World Bank | 2021 | https://data.worldbank.org |
Administrative boundaries | ADCW | 7.6 | https://www.adci.com/adc-worldmap |
Curated POIs based on OSM | SLIPO/OSM POIs | http://slipo.eu/?p=1551 https://www.openstreetmap.org/ | |
Household data | IPUMS | https://international.ipums.org/international | |
Population count with demographic attributes | GPW | v4.11 | https://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)
Filename | Description |
---|---|
usa_140002904_person_v_0_9.csv | Data for each person including attributes such as age, gender, and household ID. |
usa_140002904_household_v_0_9.csv | Data at household level. |
usa_140002904_residence_locations_v_0_9.csv | Data about residence locations |
usa_140002904_activity_locations_v_0_9.csv | Data about activity locations, including what activity types are supported at these locations |
usa_140002904_activity_location_assignment_v_0_9.csv | For each person and for each of their activities, this file specifies the location where the activity takes place |
Derived data files
Filename | Description |
---|---|
usa_140002904_contact_matrix_v_0_9.csv | A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model. |
Validation and measures files
Filename | Description |
---|---|
usa_140002904_household_grouping_validation_v_0_9.pdf | Validation plots for household construction |
usa_140002904_activity_durations_{adult,child}_v_0_9.pdf | Comparison of time spent on generated activities with survey data |
usa_140002904_activity_patterns_{adult,child}_v_0_9.pdf | Comparison of generated activity patterns by the time of day with survey data |
usa_140002904_location_construction_0_9.pdf | Validation plots for location construction |
usa_140002904_location_assignement_0_9.pdf | Validation plots for location assignment, including travel distribution plots |
usa_140002904_usa_140002904_ver_0_9_0_avg_travel_distance.pdf | Choropleth map visualizing average travel distance |
usa_140002904_usa_140002904_ver_0_9_0_travel_distr_combined.pdf | Travel distance distribution |
usa_140002904_usa_140002904_ver_0_9_0_num_activity_loc.pdf | Choropleth map visualizing number of activity locations |
usa_140002904_usa_140002904_ver_0_9_0_avg_age.pdf | Choropleth map visualizing average age |
usa_140002904_usa_140002904_ver_0_9_0_pop_density_per_sqkm.pdf | Choropleth map visualizing population density |
usa_140002904_usa_140002904_ver_0_9_0_pop_size.pdf | Choropleth map visualizing population size |