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All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The data is from:
https://simplemaps.com/data/world-cities
We're proud to offer a simple, accurate and up-to-date database of the world's cities and towns. We've built it from the ground up using authoritative sources such as the NGIA, US Geological Survey, US Census Bureau, and NASA.
Our database is:
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000. This data comes from the US Census Bureau's 2015 American Community Survey. This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.
This dataset contains a listing of incorporated places (cities and towns) and counties within the United States including the GNIS code, FIPS code, name, entity type and primary point (location) for the entity. The types of entities listed in this dataset are based on codes provided by the U.S. Census Bureau, and include the following: C1 - An active incorporated place that does not serve as a county subdivision equivalent; C2 - An active incorporated place legally coextensive with a county subdivision but treated as independent of any county subdivision; C3 - A consolidated city; C4 - An active incorporated place with an alternate official common name; C5 - An active incorporated place that is independent of any county subdivision and serves as a county subdivision equivalent; C6 - An active incorporated place that partially is independent of any county subdivision and serves as a county subdivision equivalent or partially coextensive with a county subdivision but treated as independent of any county subdivision; C7 - An incorporated place that is independent of any county; C8 - The balance of a consolidated city excluding the separately incorporated place(s) within that consolidated government; C9 - An inactive or nonfunctioning incorporated place; H1 - An active county or statistically equivalent entity; H4 - A legally defined inactive or nonfunctioning county or statistically equivalent entity; H5 - A census areas in Alaska, a statistical county equivalent entity; and H6 - A county or statistically equivalent entity that is areally coextensive or governmentally consolidated with an incorporated place, part of an incorporated place, or a consolidated city.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Update NotesMar 16 2024, remove spaces in the file and folder names.Mar 31 2024, delete the underscore in the city names with a space (such as San Francisco) in the '02_TransCAD_results' folder to ensure correct data loading by TransCAD (software version: 9.0).Aug 31 2024, add the 'cityname_link_LinkFlows.csv' file in the '02_TransCAD_results' folder to match the link from input data and the link from TransCAD results (LinkFlows) with the same Link_ID.IntroductionThis is a unified and validated traffic dataset for 20 US cities. There are 3 folders for each city.01 Input datathe initial network data obtained from OpenStreetMap (OSM)the visualization of the OSM dataprocessed node / link / od data02 TransCAD results (software version: 9.0)cityname.dbd : geographical network database of the city supported by TransCAD (version 9.0)cityname_link.shp / cityname_node.shp : network data supported by GIS software, which can be imported into TransCAD manually. Then the corresponding '.dbd' file can be generated for TransCAD with a version lower than 9.0od.mtx : OD matrix supported by TransCADLinkFlows.bin / LinkFlows.csv : traffic assignment results by TransCADcityname_link_LinkFlows.csv: the input link attributes with the traffic assignment results by TransCADShortestPath.mtx / ue_travel_time.csv : the traval time (min) between OD pairs by TransCAD03 AequilibraE results (software version: 0.9.3)cityname.shp : shapefile network data of the city support by QGIS or other GIS softwareod_demand.aem : OD matrix supported by AequilibraEnetwork.csv : the network file used for traffic assignment in AequilibraEassignment_result.csv : traffic assignment results by AequilibraEPublicationXu, X., Zheng, Z., Hu, Z. et al. (2024). A unified dataset for the city-scale traffic assignment model in 20 U.S. cities. Sci Data 11, 325. https://doi.org/10.1038/s41597-024-03149-8Usage NotesIf you use this dataset in your research or any other work, please cite both the dataset and paper above.A brief introduction about how to use this dataset can be found in GitHub. More detailed illustration for compiling the traffic dataset on AequilibraE can be referred to GitHub code or Colab code.ContactIf you have any inquiries, please contact Xiaotong Xu (email: kid-a.xu@connect.polyu.hk).
This is the complete dataset for the 500 Cities project 2019 release. This dataset includes 2017, 2016 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2017, 2016), Census Bureau 2010 census population data, and American Community Survey (ACS) 2013-2017, 2012-2016 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures (all teeth lost, dental visits, mammograms, pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) from the 2016 BRFSS that are the same in the 2019 release as the previous 2018 release. More information about the methodology can be found at www.cdc.gov/500cities.
This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.
The U.S. Cities elevation data collection program supported the US Department of Homeland Security Homeland Security and Infrastructure Program (HSIP). As part of the HSIP Program, there were 133+ U.S. cities that had imagery and LiDAR collected to provide the Homeland Security, Homeland Defense, and Emergency Preparedness, Response and Recovery (EPR&R) community with common operational, geospatially enabled baseline data needed to analyze threat, support critical infrastructure protection and expedite readiness, response and recovery in the event of a man-made or natural disaster. As a part of that, for some time, recurring LiDAR data was also being collected by a joint agreement of NGA and other federal agencies and the HIFLDS Working Group. The publicly released data excluded US Military Installation coverage, but it is provided in as is. These collects were acquired by contract using commercial collection companies. Some metadata information about the collection can be found at USGS at https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/Non_Standard_Contributed/NGA_US_Cities/Topeka_KS/NGA%20133%20US%20Cities%20Data%20Disclaimer%20and%20Explanation%20Readme.pdf
This data set includes cities in the United States, Puerto Rico and the U.S. Virgin Islands. These cities were collected from the 1970 National Atlas of the United States. Where applicable, U.S. Census Bureau codes for named populated places were associated with each name to allow additional information to be attached. The Geographic Names Information System (GNIS) was also used as a source for additional information. This is a revised version of the December, 2003, data set.
This layer is sourced from maps.bts.dot.gov.
This dataset illustrates the largest difference between high and low temperatures and the smallest difference between high and low temperatures in cities with 50,000 people or more. A value of -1 means that the data was not applicable. Also included are the rankings, the inverse ranking to be used for mapping purposes, the popualtion, the name of city and state, and the temperature degree difference. Source City-Data URL http//www.city-data.com/top2/c489.html http//www.city-data.com/top2/c490.html Date Accessed November 13,2007
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Florida City population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Florida City. The dataset can be utilized to understand the population distribution of Florida City by age. For example, using this dataset, we can identify the largest age group in Florida City.
Key observations
The largest age group in Florida City, FL was for the group of age 5-9 years with a population of 1,729 (13.46%), according to the 2021 American Community Survey. At the same time, the smallest age group in Florida City, FL was the 85+ years with a population of 95 (0.74%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Florida City Population by Age. You can refer the same here
TABLE III. Deaths in 122 U.S. cities – 2016. 122 Cities Mortality Reporting System — Each week, the vital statistics offices of 122 cities across the United States report the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days –1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and ≥ 85 years).
FOOTNOTE: U: Unavailable. —: No reported cases. * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 100,000 or more. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included.
† Pneumonia and influenza.
§ Total includes unknown ages.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Kenneth City population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Kenneth City. The dataset can be utilized to understand the population distribution of Kenneth City by age. For example, using this dataset, we can identify the largest age group in Kenneth City.
Key observations
The largest age group in Kenneth City, FL was for the group of age 60-64 years with a population of 504 (9.99%), according to the 2021 American Community Survey. At the same time, the smallest age group in Kenneth City, FL was the 10-14 years with a population of 102 (2.02%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Kenneth City Population by Age. You can refer the same here
The 2020 cartographic boundary shapefiles 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. A consolidated city is a unit of local government for which the functions of an incorporated place and its county or minor civil division (MCD) have merged. This action results in both the primary incorporated place and the county or MCD continuing to exist as legal entities, even though the county or MCD performs few or no governmental functions and has few or no elected officials. Where this occurs, and where one or more other incorporated places in the county or MCD continue to function as separate governments, even though they have been included in the consolidated government, the primary incorporated place is referred to as a consolidated city. The Census Bureau classifies the separately incorporated places within the consolidated city as place entities and creates a separate place (balance) record for the portion of the consolidated city not within any other place. The generalized boundaries of the consolidated cities in this file are based on those as of January 1, 2020, as reported through the Census Bureau's Boundary and Annexation Survey (BAS).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Phenix City population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Phenix City. The dataset can be utilized to understand the population distribution of Phenix City by age. For example, using this dataset, we can identify the largest age group in Phenix City.
Key observations
The largest age group in Phenix City, AL was for the group of age 30 to 34 years years with a population of 3,094 (8.04%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Phenix City, AL was the 85 years and over years with a population of 400 (1.04%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Phenix City Population by Age. You can refer the same here
The Counties dataset was updated on October 31, 2023 from the United States Census Bureau (USCB) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB 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 they can be combined to cover the entire nation. 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 boundaries for counties and equivalent entities are mostly as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529015
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. 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.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 27808 cities in the United States by American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset illustrates the cities with the largest wind speed differences. Also included are the city and state, the population, the speed differnce, the ranking, and the inverse ranking (to be used only for mapping purposes). Source: City-Data URL: http://www.city-data.com/top2/c466.html Date Accessed: November 9, 2007
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 4 cities in the Dunn County, ND by White population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name