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 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.

Malta MT: Population Density: People per Square Km data was reported at 1,454.037 Person/sq km in 2017. This records an increase from the previous number of 1,422.987 Person/sq km for 2016. Malta MT: Population Density: People per Square Km data is updated yearly, averaging 1,096.006 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 1,454.037 Person/sq km in 2017 and a record low of 943.737 Person/sq km in 1974. Malta MT: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malta – Table MT.World Bank: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted Average;

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.

Malta MT: Population Density: Inhabitants per sq km data was reported at 1,691.920 Person in 2023. This records an increase from the previous number of 1,676.800 Person for 2022. Malta MT: Population Density: Inhabitants per sq km data is updated yearly, averaging 1,321.665 Person from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 1,691.920 Person in 2023 and a record low of 1,167.960 Person in 1990. Malta MT: Population Density: Inhabitants per sq km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Malta – Table MT.OECD.GGI: Social: Demography: Non OECD Member: Annual.

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.

This datalayer displays the Urbanized Areas (UAs) for the state based on a January 1, 1990 ground condition. Note that the Census Bureau made significant changes in Urban/Rural designations for the Census 2000 data layers. Some of these delineations and definitions are explained below. 1990 Urban/Rural The U.S. Census Bureau defined urban for the 1990 census as consisting of all territory and population in urbanized areas (UAs) and in the urban portion of places with 2,500 or more people located outside of the UAs. The 1990 urban and rural classification applied to the 50 states, the District of Columbia, and Puerto Rico. 1990 Urbanized Areas A 1990 urbanized area (UA) consisted of at least one central place and the adjacent densely settled surrounding territory that together had a minimum population of 50,000 people. The densely settled surrounding territory generally consisted of an area with continuous residential development and a general overall population density of at least 1,000 people per square mile. 1990 Extended Cities For the 1990 census, the U.S. Census Bureau distinguished the urban and rural population within incorporated places whose boundaries contained large, sparsely populated, or even unpopulated area. Under the 1990 criteria, an extended city had to contain either 25 percent of the total land area or at least 25 square miles with an overall population density lower than 100 people per square mile. Such pieces of territory had to cover at least 5 square miles. This low-density area was classified as rural and the other, more densely settled portion of the incorporated place was classified as urban. Unlike previous censuses where the U.S. Census Bureau defined extended cities only within UAs, for the 1990 census the U.S. Census Bureau applied the extended city criteria to qualifying incorporated places located outside UAs. 1990 Urbanized Area Codes Each 1990 UA was assigned a 4-digit numeric census code in alphabetical sequence on a nationwide basis based on the metropolitan area codes. Note that in Record Type C, the 1990 UA 4-digit numeric censu s code and Census 2000 UA 5-digit numeric census code share a 5-character field. Because of this, the 1990 4-digit UA code, in Record Type C only, appears with a trailing blank. For Census 2000 the U.S. Census Bureau classifies as urban all territory, population, and housing units located within urbanized areas (UAs) and urban clusters (UCs). It delineates UA and UC boundaries to encompass densely settled territory, which generally consists of: - A cluster of one or more block groups or census blocks each of which has a population density of at least 1,000 people per square mile at the time - Surrounding block groups and census blocks each of which has a population density of at least 500 people per square mile at the time, and - Less densely settled blocks that form enclaves or indentations, or are used to connect discontiguous areas with qualifying densities. Rural consists of all territory, population, and housing units located outside of UAs and UCs. For Census 2000 this urban and rural classification applies to the 50 states, the District of Columbia, Puerto Rico, American Samoa, Guam, the Northern Mariana Islands, and the Virgin Islands of the United States. Urbanized Areas (UAs) An urbanized area consists of densely settled territory that contains 50,000 or more people. The U.S. Census Bureau delineates UAs to provide a better separation of urban and rural territory, population, and housing in the vicinity of large places. For Census 2000, the UA criteria were extensively revised and the delineations were performed using a zero-based approach. Because of more stringent density requirements, some territory that was classified as urbanized for the 1990 census has been reclassified as rural. (Area that was part of a 1990 UA has not been automatically grandfathered into the 2000 UA.) In addition, some areas that were identified as UAs for the 1990 census have been reclassified as urban clusters. Urban Clusters (UCs) An urban cluster consists of densely settled territory that has at least 2,500 people but fewer than 50,000 people. The U.S. Census Bureau introduced the UC for Census 2000 to provide a more consistent and accurate measure of the population concentration in and around places. UCs are defined using the same criteria that are used to define UAs. UCs replace the provision in the 1990 and previous censuses that defined as urban only those places with 2,500 or more people located outside of urbanized areas. Urban Area Title and Code The title of each UA and UC may contain up to three incorporated place names, and will include the two-letter U.S. Postal Service abbreviation for each state into which the UA or UC extends. However, if the UA or UC does not contain an incorporated place, the urban area title will include the single name of a census designated place (CDP), minor civil division, or populated place recognized by the U.S. Geological Survey's Geographic Names Information System. Each UC and UA is assigned a 5-digit numeric code, based on a national alphabetical sequence of all urban area names. For the 1990 census, the U.S. Census Bureau assigned as four-digit UA code based on the metropolitan area codes. Urban Area Central Places A central place functions as the dominant center of an urban area. The U.S. Census Bureau identifies one or more central places for each UA or UC that contains a place. Any incorporated place or census designated place (CDP) that is in the title of the urban area is a central place of that UA or UC. In addition, any other incorporated place or CDP that has an urban population of 50,000 or an urban population of at least 2,500 people and is at least 2/3 the size of the largest place within the urban area also is a central place. Extended Places As a result of the UA and UC delineations, an incorporated place or census designated place (CDP) may be partially within and partially outside of a UA or UC. Any place that is split by a UA or UC is referred to as an extended place.

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 Fort Keogh (FTK) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

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.

Correlations between population density and nest predation rates for bird species.

This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Montana. 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 Montana. 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 Montana. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F7ZG6Q77

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 Fort Keogh (FTK) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

Table with detailed information forest stands studied in western Montana, USA.

MT：人口密度：每平方公里人口在12-01-2017达1,454.037Person/sq km，相较于12-01-2016的1,422.987Person/sq km有所增长。MT：人口密度：每平方公里人口数据按年更新，12-01-1961至12-01-2017期间平均值为1,096.006Person/sq km，共57份观测结果。该数据的历史最高值出现于12-01-2017，达1,454.037Person/sq km，而历史最低值则出现于12-01-1974，为943.737Person/sq km。CEIC提供的MT：人口密度：每平方公里人口数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的马耳他 – 表 MT.世界银行：人口和城市化进程统计。

Tabular and raster data containing spatial capture recapture records for male and female black bears (Ursus americanus) in Glacier National Park and surrounding landscape collected from June - October 2004 and associated tabular data files required for analysis of data with spatial capture connectivity models and raster data describing the ouput from SCR models. Associated tables and rasters include details for traps, the state space and connectivity space required modeling and associated spatial covariates tested in models, as well as rasters describing black bear population density, habitat use, and population connectivity.

Occupied and potential wild turkey habitat in Montana. The species (Merriam's, Eastern, or both) is indicated in occupied habitat polygons.

人口密度：每平方公里的居民在12-01-2023达1,691.920人，相较于12-01-2022的1,676.800人有所增长。人口密度：每平方公里的居民数据按年更新，12-01-1990至12-01-2023期间平均值为1,321.665人，共34份观测结果。该数据的历史最高值出现于12-01-2023，达1,691.920人，而历史最低值则出现于12-01-1990，为1,167.960人。CEIC提供的人口密度：每平方公里的居民数据处于定期更新的状态，数据来源于Organisation for Economic Co-operation and Development，数据归类于全球数据库的马耳他 – Table MT.OECD.GGI: Social: Demography: Non OECD Member: Annual。

Taxonomic information for bird species examined in this study.

Conifer removal effects on densities of bird species and combined nest predators.

Changes in nest predation with both PC axes for bird species.

A table showing spatial capture–recapture model estimates for the total number (N) and density of mountain lions in the 5912 km² statespace in western Montana from all 16 candidate models.