This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

A dataset listing Florida counties by population for 2024.

The 2022 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 cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

This EnviroAtlas dataset is a summary of key demographic groups for the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

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 county boundaries 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). Please see the Data Dictionary for more information on data fields. Data Sources:FDOT FTO 2020 and 2021 Population Estimates by 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

Total population, by county, for the state of Florida according to the US Census Bureau estimates for 2015For technical assistance, contact the Florida's Roadmap to Healthy Living Administrator

This dataset was developed under the guidance of the U.S. National Grid Institute due to a mission request from theFL-TF4 US&R Team operating in Louisiana after HurricaneLaura, August 2020, to support future similar Search-and-Rescue missions. The original population data are from WorldPop.org, converted to a 1-km USNG format courtesy of the USNGCenter.org, and mapped and hosted at the Florida Resources and Environmental Analysis Center (FREAC), Florida State University (FSU). Web-based map viewers are available as a courtesy of CalTopo, GISsurfer, and Esri.More Details: https://usng-gis.org/docs/TheSARTopoProject.pdf

Public Law (P.L.) 94-171, enacted in 1975, directs the U.S. Census Bureau to make special preparations to provide redistricting data needed by the 50 states. It specifies that within a year following Census Day (by April 1, 2011), the Census Bureau must send the governor and legislature in each state the data they need to redraw districts for the United States Congress and state legislature. The Census 2010 Redistricting Data Program was set up to afford state officials an opportunity to define the small areas for which they wish to receive census population totals for redistricting purposes. Officials then could receive data for voting districts (e.g., election precincts, wards, state house and senate districts) in addition to standard census geographic areas, such as counties, cities, census tracts, and blocks. State participation in defining areas is voluntary and nonpartisan. There are four map types that support the 2010 Census Redistricting Data (Public Law [P.L.] 94-171) program. Each of these large format map types is produced in Adobeâ s portable document format (PDF). These georeferenced PDF files were created in compliance with the OGC PDF Geo-registration Encoding Best Practice Version 2.2 (OGC project document reference number OGC 08-139r2). They will also be available through the U.S. Census Bureau Map Products web site. In addition to the maps, other geographic products include the State Redistricting Data (P.L.94-171) Shapefiles and the 2010 Census Block Assignment Files, which provide census block relationships to voting districts, state legislative districts, school districts, and congressional districts. All four map types are produced in a set for each county or statistically equivalent entity (school district maps for the District of Columbia, Florida, Hawaii, Maryland, Nevada, and West Virginia are state-based). Each map set consists of one or more numbered parent sheets which cover the entire county. If necessary, separate inset sheets show areas of dense features at a larger scale. Inset areas are identified with letters. If the set has more than one parent sheet, an index sheet is also included which depicts the arrangement of the parent sheets and inset areas in relation to the county boundary and selected major features. All of the parent sheets within a county are produced at the same scale, while maps for adjacent counties may be at different scales. The objective of each map type is to use the smallest number of sheets while preserving legibility of geographic entity names and feature identifiers. The physical size of the county and the density of features also affect the number of parent sheets and insets.

The Florida Fish and Wildlife Conservation Commission (FWC) collected annual trawl data at 27 open-water sites from 1987 to 1991 (Bull et al. 1995). Nearly 37,000 fish were recorded in 438 10-minute open-water trawls (Bull et al. 1995). Seven species accounted for 98% of the total number and total fish biomass. Clustering of sites based on mean catch of the primary species expressed as number and weight produced four distinct groups. The groups were labeled as the northeast shore, northwest shore, south-southwest shore and open water area. Areal fish distribution patterns also were compared using analysis of variance (ANOVA) and Tukey’s HSD post hoc test. Within the four groups there were significant differences in the distribution of certain fish species. In addition to the open-water trawl sites, the FWC has utilized electrofishing techniques to collect annual largemouth bass (Micropterous salmodies) (LMB) data from 22 near-shore and interior marsh locations since 1999 (Havens et al. 2004). Although the trawl and electrofishing data provide some baseline information, still there is limited data regarding temporal changes in the community structure, density and condition of the primary sport fish LMB, black crappie (Pomoxis nigromaculatus), bluegill (Lepomis macrochirus) and redear (Lepomis microlophus) sunfish) and other fish species in Lake Okeechobee. During this study, fish species will be collected from 49 historic sampling locations. Fish assemblages in the 27 open water regions of the lake will be sampled with an Otter Trawl net. The 22 near-shore and interior marsh sites will be sampled utilizing electrofishing gear. Ancillary data, including water temperature, dissolved oxygen, pH, turbidity, conductivity, and sediment/aquatic plant type will be recorded at the 49 sampling locations.
The two historic sets of non-MAP data will be used to help establish baseline conditions for the near-shore, interior marsh and open-water fishery. It is appropriate to include the non-MAP data in our analysis as current sampling will occur at the historical locations and sampling methods will be similar. We anticipate significant spatial differences in fish abundance and biomass will exist at the near-shore, interior marsh and open water sites. Therefore, similar statistical tests including cluster analysis and analysis of variance should be used to evaluate temporal changes in the near-shore and open water fishery. Detailed statistical analysis should be conducted at a minimum of every three years to evaluate long-term trends and establish relationships between fish distribution, condition, and community structure and environmental conditions including habitat and water depth.
The objectives of this project are to evaluate temporal changes in Lake Okeechobee’s fishery by determining annual changes in the areal distribution, condition, density and community structure (year classes) of all major fish species found in the near-shore, interior marsh and open-water regions of the lake. Ancillary data including water temperature, dissolved oxygen, pH, turbidity, conductivity, and sediment type also will be recorded.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

The development of Brevard County, Florida, and more specifically Merritt Island, began after World War II when air-conditioning and the interstate highway system encouraged migration from northern states. In 1960 the estimated population of Florida was 550,823, with Brevard County reporting a population of 111,435. This is in stark contrast to more current numbers. According to the 2013 census, Florida’s population was 19,552,860, with Brevard County home to 4,956,560.The John F. Kennedy Space Center was named to honor the late president by President Lyndon B. Johnson shortly after Kennedy’s death and has been the site of every NASA human space flight since 1963. Located midway between Jacksonville and Miami, the site’s low latitude and proximity to the open ocean made it ideal for the space program launch site. The space center’s infrastructure is visible in the 2014 natural color imagery to the right, and the future site locations are highlighted here in the 1958 aerial imagery. 1958 imagery provided by: University of Florida Digital Collections Story Map Contact: coastal.info@noaa.gov NOAA Office for Coastal Management