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 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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. 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 and situations 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. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

California was the state with the highest resident population in the United States in 2024, with 39.43 million people. Wyoming had the lowest population with about 590,000 residents. Living the American Dream Ever since the opening of the West in the United States, California has represented the American Dream for both Americans and immigrants to the U.S. The warm weather, appeal of Hollywood and Silicon Valley, as well as cities that stick in the imagination such as San Francisco and Los Angeles, help to encourage people to move to California. Californian demographics California is an extremely diverse state, as no one ethnicity is in the majority. Additionally, it has the highest percentage of foreign-born residents in the United States. By 2040, the population of California is expected to increase by almost 10 million residents, which goes to show that its appeal, both in reality and the imagination, is going nowhere fast.

Map containing historical census data from 1900 - 2000 throughout the western United States at the county level. Data includes total population, population density, and percent population change by decade for each county. Population data was obtained from the US Census Bureau and joined to 1:2,000,000 scale National Atlas counties shapefile.

The 2015 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. 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 boundaries for counties and equivalent entities are as of January 1, 2010.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Glacier Lakes Ecosystems Experiments Site (GLA) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

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.

This page allows for the download of data regarding the WUI, including non-WUI vegetated areas and non-vegetated or agriculture. The wildland-urban interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. This makes the WUI a focal area for human-environment conflicts such as wildland fires, habitat fragmentation, invasive species, and biodiversity decline. Using geographic information systems (GIS), the USFS integrated U.S. Census and USGS National Land Cover Data, to map the Federal Register definition of WUI (Federal Register 66:751, 2001) for the conterminous United States from 1990-2010. These data are useful within a GIS for mapping and analysis at national, state, and local levels. Data are available as a geodatabase and include information such as housing and population densities for 1990, 2000, and 2010; wildland vegetation percentages for 1992, 2001, and 2011; as well as WUI classes in 1990, 2000, and 2010.

1Mean well density in 2009 within a 20 km radius of northeast Wyoming leks.2Maximum well density in 2009 within a 20 km radius of northeast Wyoming leks.3Permitting levels for well density on United States federal land.

Comprehensive demographic dataset for Yellowstone National Park, WY, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Microsatellite genotypes for greater sage-grouse.Microsatellite genotypes (number of repeats for 14 loci) for 781 individuals from 10 subpopulations of the greater sage-grouse in Wyoming.rowetal_mol_ecol_2016.csv

This CSV file contains landscape factors representing anthropogenic disturbances to stream habitats summarized within local and network stream catchments as well as 90 m local and network buffer of stream reaches throughout the conterminous U.S. The source datasets compiled and attributed to spatial units were identified as being: (1) meaningful for assessing fluvial fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) broadly representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. Variables summarized at the catchment scale include measures of anthropogenic land uses, population density, roads, dams, mines, water withdrawals, sediment and nutrient loading to rivers, and point-source pollution sites, whereas buffers were attributed with only land use variables. In this data set, variable summaries are linked to catchments and buffers developed for the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). Like the catchment variables the buffer variables are labeled using a LB and NB prefix for local buffer and network buffer variables, respectively.

Macrofossils from woodrat (Neotoma) middens serve as an important proxy for reconstructing past vegetation in arid and semiarid regions of North America. The presence/absence of plant macrofossils in middens can provide valuable information on temporal and spatial patterns of plant migration and range boundaries. The primary aim of this study was to determine how local plant abundance, distance of plant populations from midden sites, and species population density on the landscape affect the probability of occurrence of macrofossils in middens. The study was designed with the primary intent of determining the reliability of middens in detecting scattered populations of Pinus ponderosa. We analyzed macrofossil assemblages from 42 modern woodrat middens from West Carrizo Canyon in southeastern Colorado, near the current eastern range margin of Pinus ponderosa. We compared midden contents with composition of the surrounding vegetation, measuring distance from the midden to the nearest individual of selected plant species, and the percent cover of each species within 30 m of the midden. We used this information to model the probability of species presence in a midden across a range of population densities on the landscape. Macrofossils of Juniperus spp., Quercus gambelii, and Opuntia spp. were consistently found in middens regardless of their local abundance in vegetation, although populations occurred within 30 m of all middens. Pinus edulis and P. ponderosa occurred in nearly all middens within 20-30 m of individual trees. P. ponderosa was rare in middens >20-30 m away from individual trees. Results of a simple simulation model suggest that middens become absolutely reliable indicators of P. ponderosa presence on the landscape only when average tree density exceeds 50 stems ha-1. Woodrats reliably collected macrofossils of Pinus edulis, P. ponderosa, Juniperus spp., Quercus gambelii, and Opuntia spp. when populations of these taxa occur within 20-30 m of a midden site. Woodrats did not collect P. ponderosa when the nearest individuals were more than 30 m away. Low-density populations of these and other species may be difficult to detect in fossil woodrat-midden series owing to reduced probability that individuals grow within foraging distance of the middens. Data from this and similar studies can be used to construct and parameterize a forward model of macrofossil representation in woodrat middens.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Glacier Lakes Ecosystems Experiments Site (GLA) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

This CSV file contains cumulative fish habitat condition index (HCI) scores generated for river reaches of the conterminous United States as well as indices generated specifically for four spatial units including local and network catchments and 90 m local and network buffers of river reaches. Note that the cumulative HCI score is determined from limiting index scores generated for the four spatial units listed above. Detailed methods for calculating cumulative fish habitat condition index scores as well as the indices for each spatial extent can be found on the following website: http://assessment.fishhabitat.org/: The variables used to create indices in catchments vs. buffers differ due to differences in resolution of datasets. The following anthropogenic disturbance variables were used to create local and network catchment indices: Percent of urban land use, percent of impervious surface, human population density, road density, percent of pasture/hay, percent of cultivated crops, density of point source pollution sites (National Pollution Discharge Elimination, Toxic Inventory Release and National Superfund), nutrient and sediment loading to watersheds, habitat fragmentation metrics (density of dams and road crossings), density of mines and water withdrawals. The following anthropogenic disturbance variables were analyzed to create the local and network buffer indices: percent of urban land use, percent of agriculture, percent of pasture/hay and percent of impervious surface. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment and buffer units. Also included in this CSV file are the most limiting and severe disturbances to stream reaches operating within each of the four spatial extents. Limiting disturbances are defined as those disturbances that result in a stream reach not being in the best available condition determined for the region. Severe disturbances are a subset of limiting disturbances that are associated with stream reaches in a given region that were scored as having high or very high risk of habitat degradation (red and orange color groups). In this data set, indices as well as limiting and severe disturbances are linked to the stream reaches, catchments and buffers created for the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. It is important to recognize that these broadly-defined disturbance variables often act together with other measured or unmeasured threats to degrade habitat. Thus, while we may identify “urbanization” as a major threat to fish habitat in some regions, “urbanization” represents an umbrella term that describes many facets of urban development that could cause degradation to habitats. Fields in this dataset that begin with the "L_" prefix represent the local catchment whereas network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix. Like the catchment variables the buffer variables are labeled using a "LB_" and "NB_" prefix for local buffer and network buffer variables, respectively. More information about the processes used to create scores can be found in the processes section. Version 2.0 includes the addition of severe disturbances for each spatial scale and fixes errors documented in the change log.