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) System (MTS). The MTS 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 because of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division 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 Bureau 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.

The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File 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 2010 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.

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.

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 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.

In 1800, the present-day region of Mexico had a population of just over six million people. Mexico gained its independence from the Spanish crown in 1821, and population growth remained steady for the next 85 years. Growth then halted with with the Panic of 1907, an American financial crisis whose ripple effects in Mexico would set the stage for the Mexican Revolution in 1910. This revolution would see population flatline at just over fifteen million between 1910 and 1920, as widespread conflict and result in the death of between 1.7 to 2.7 million over the decade, and the coinciding 1918 Spanish Flu epidemic would see the loss of another 300,000 in this time period. Following the end of both the Mexican Revolution and the Spanish Flu epidemic in 1920, the population of Mexico would begin to increase rapidly as modernization would see mortality rates fall and standards of living rise throughout the country. This growth has continued steadily into the 21st century, and in 2020, Mexico is estimated to have a population of just under 129 million.

Created using ArcGIS Pro Geoprocessing tools (Create Space Time Cube, Emerging Hot Spot Analysis, and Enrich Layer) and the ArcGIS R Bridge. The EBest function, part of the spdep package was used to calculate an Empirical Bayes smoothed crime rate with 2016 population estimates. This procedure is presented as part of the R-ArcGIS Workflow Demo on GeoNet.Relative Burglary Risk is the natural log (Ln) of the kernel density of burglaries g(x) divided by the kernel density of households g(y) calculated using CrimeStat. Note: Ten months of burglary data (the minimum required) were used for this initial analysis. Also Note: These locations are one-half kilometer square polygons. It will be updated in the future as more data from the Albuquerque Police Department is obtained (see ABQ Data).Please see the web map for another similar way to present these results.More information at (http://www.unm.edu/~lspear/other_nm.html).

This study measured the population dynamics of coyotes in the grasslands and creosote shrublands of McKenzie Flats, Sevilleta National Wildlife Refuge. The study was begun in January, 1992, and continued quarterly each year. Coyotes were sampled via scat counts along the roads of McKenzie Flats during winter, spring, summer, and fall of each year. The entire road transect was 21.5 miles in length. Scat counts over a week period (number of scats/mile/day) in each season along the roads were used to calculate the densities of coyotes (number of coyotes per square kilometer). Results from 1992 to 2002 indicated that autumn was the peak density period of the year, with generally steady declines through the year until the following autumn. Coyote populations appeared to fluctuate seasonally, but remained relatively stable at 0.27 +/- 0.03 (SE) coyotes per km2 during summer periods (this likely represents the "breeding pair" density, during which coyote pairs have set up territories and are raising young, but the pups have not as yet joined the parents in foraging activities).

This study measured the population dynamics of black-tail jackrabbits (Lepus californicus) and desert cottontail rabbits (Sylvilagus auduboni) in the grasslands and creosote shrublands of McKenzie Flats, Sevilleta National Wildlife Refuge. The study was begun in January, 1992, and continued quarterly each year. Rabbits were sampled via night-time spotlight transect sampling along the roads of McKenzie Flats during winter, spring, summer, and fall of each year. The entire road transect was 21.5 miles in length. Measurements of perpendicular distance of each rabbit from the center of the road were used to estimate densities (number of rabbits per square kilometer) via Program DISTANCE. Results from 1992 to 2002 indicated that spring was the peak density period of the year, with generally steady declines through the year until the following spring. Evidence of a long-term "cycle" (e.g., the 11 year cycle reported for rabbits in the Great Basin Desert) did not appear in the Sevilleta rabbit populations.

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. 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 and beyond, 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.

The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File 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 2020 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.

Future county population was based on projections for 2100 from the Spatially Explicit Regional Growth Model (SERGoM; Theobald 2005). SERGoM simulates population based on existing patterns of growth by census block, groundwater well and road density, and transportation distance to urban areas, while constraining the pattern of development to areas outside of protected areas and urban areas (Theobald 2005). The dataset here is a projection for a “baseline” growth scenario that assumes a similar trajectory to that of current urban growth (Bierwagen et al. 2010). SERGoM accuracy is estimated as 79–99% when compared to 1990 and 2000 census data, with the accuracy varying by urban/exurban/rural categories and increasing slightly with coarser resolution (Theobald 2005). The accuracy of future model predictions with different economic scenarios is most sensitive to fertility rates, which are subject to cultural change, economic recessions, and the current pattern of lands protected from development (Bierwagen et al. 2010). Bierwagen, B. G., D. M. Theobald, C. R. Pyke, A. Choate, P. Groth, J. V. Thomas, and P. Morefield. 2010. National housing and impervious surface scenarios for integrated climate impact assessments. Proceedings of the National Academy of Sciences of the United States of America 107:20887-20892. Theobald, D. M. 2005. Landscape patterns of exurban growth in the USA from 1980 to 2020. Ecology and Society 10: article 32.

The 2023 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. 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 and beyond, 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.

In Mexico, the number of practicing doctors amounted to **** professionals per 1,000 inhabitants in 2023, an increase compared to the figures reported a year earlier when there were **** practicing physicians per every thousand people. During 2022, the number of physicians in Mexico totaled approximately ******* professionals. Density of doctors worldwide In a global comparison, Mexico ranks in a middle category for density of medical doctors per 1,000 population, similar to Canada and Colombia. Among the countries in the upper bracket for highest density of doctors are Cuba, Sweden, Belgium, and Uruguay. Along with Mexico’s moderate density of doctors, over ** percent of the population was considered vulnerable due to lack of access to health services in Mexico as of 2022, up from around **** percent a decade earlier. Health care in Mexico Nearly ** ******* people in Mexico held public health insurance through Seguro Popular in 2020, which was replaced by a new institution at the beginning of that year, called INSABI (Instituto Nacional de Salud para el Bienestar). However, the IMSS (Instituto Mexicano del Seguro Social) led by a large margin as the largest provider of health insurance in the North American country.

This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of New Mexico. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of New Mexico. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. 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 units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the 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). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for New Mexico. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F79S1P1F

Detailed description of study areas and methods used to test predictions.

This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sev/23/121705. The abstract below was extracted from the Level 0 data package and is included for context: This study explores the population dynamics of black-tail jackrabbits (Lepus californicus) and desert cottontail rabbits (Sylvilagus auduboni) in the grasslands and creosote shrublands of McKenzie Flats, Sevilleta National Wildlife Refuge. The study was initiated in January 1992, and continues quarterly each year. Rabbits are sampled via night-time spotlight transect sampling along the roads of McKenzie Flats once during winter, spring, summer, and fall. The route is 21.5 miles long. Measurements of perpendicular distance of each rabbit from the center of the road are used to estimate densities (number of rabbits per square kilometer) via Program DISTANCE. Results from January 1992 to May 2004 indicated that spring was the period of peak density period, with generally steady declines through the rest of the year until the following spring. Evidence of a long-term "cycle" (e.g., the 11-year-cycle reported for rabbits in the Great Basin Desert) does not appear in the Sevilleta rabbit populations.

Map prepared by Srini Vasan; data for liquor store locations supplied by Tom Scharman

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.

This site contains data files and model code for a dynamic nesting territory occupance model and 2-sex integrated population model for Cooper's hawks in Albuquerque, New Mexico, USA, 2011 - 2020.