24 datasets found
  1. Population density in the U.S. 2023, by state

    • statista.com
    • akomarchitects.com
    Updated Sep 21, 2024
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    Statista (2024). Population density in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/
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    Dataset updated
    Sep 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    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.

  2. TIGER/Line Shapefile, 2021, State, Montana, Census Tracts

    • catalog.data.gov
    Updated Nov 1, 2022
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Publisher) (2022). TIGER/Line Shapefile, 2021, State, Montana, Census Tracts [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2021-state-montana-census-tracts
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    Dataset updated
    Nov 1, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    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.

  3. a

    CENSUS 2020 PL94171 MONTANA RESERVATION

    • hub.arcgis.com
    • ceic-mtdoc.opendata.arcgis.com
    Updated Aug 23, 2021
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    Montana Department of Commerce (2021). CENSUS 2020 PL94171 MONTANA RESERVATION [Dataset]. https://hub.arcgis.com/datasets/4d78337ba485494a81a9aa99c621a6e0
    Explore at:
    Dataset updated
    Aug 23, 2021
    Dataset authored and provided by
    Montana Department of Commerce
    Area covered
    Description

    Population and Housing data for American Indian Reservations within the State of Montana was compiled from the PL 94-171 Redistricting Summary files released by the U.S. Census Bureau for the 2020 Decennial Census. This data set was created by the Montana Department of Commerce for use by the citizens of Montana and the general public. TIGER shapefiles were joined to the tabular summary file data to create this data set. A subset of variables from the release were selected for this dataset. A description of each variable and calculations are provided here.

    VINTAGE - Decennial Census vintage year - Calculation

    SUMLEV - Geography summary level - Calculation

    GEOID - Geography ID - Calculation

    NAME - Geography Name - Calculation

    AREALAND - Area of land in square meters - Calculation

    AREAWATR - Area of water in square meters - Calculation

    INTPTLAT - Geography point latitude - Calculation

    INTPTLON - Geography point longitude - Calculation

    POPTOT - Population Total - Calculation P0010001

    POPPCAP - Population per square mile - Calculation P0010001 / (AREALAND / 2589988.110336)

    POPWH - Population White alone - Calculation P0010003

    POPBL - Population Black alone - Calculation P0010004

    POPAI - Population American Indian or Alaska Native alone - Calculation P0010005

    POPAS - Population Asian alone - Calculation P0010006

    POPNH - Population Native Hawaiian or Pacific Islander alone - Calculation P0010007

    POPOT - Population Some other Race alone - Calculation P0010008

    POP2MO - Population 2 or more races - Calculation P0010009

    POPWHPCT - Population White alone percent - Calculation P0010003 / P0010001 * 100

    POPBLPCT - Population Black alone percent - Calculation P0010004 / P0010001 * 100

    POPAIPCT - Population American Indian or Alaska Native alone percent - Calculation P0010005 / P0010001 * 100

    POPASPCT - Population Asian alone percent - Calculation P0010006 / P0010001 * 100

    POPNHPCT - Population Native Hawaiian or Pacific Islander alone percent - Calculation P0010007 / P0010001 * 100

    POPOTPCT - Population Some other Race alone percent - Calculation P0010008 / P0010001 * 100

    POP2MOPCT - Population 2 or more races percent - Calculation P0010009 / P0010001 * 100

    POPWHC - Population White alone or in combination - Calculation P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071

    POPBLC - Population Black alone or in combination - Calculation P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071

    POPAIC - Population American Indian or Alaska Native alone or in combination - Calculation P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071

    POPASC - Population Asian alone or in combination - Calculation P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071

    POPNHC - Population Native Hawaiian or Pacific Islander alone or in combination - Calculation P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPOTC - Population Some Other Race alone or in combination - Calculation P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPWHCPCT - Population White alone or in combination percent - Calculation (P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071)/ P0010001 * 100

    POPBLCPCT - Population Black alone or in combination percent - Calculation (P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071)/ P0010001 * 100

    POPAICPCT - Population American Indian or Alaska Native alone or in combination percent - Calculation (P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPASCPCT - Population Asian alone or in combination percent - Calculation (P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPNHCPCT - Population Native Hawaiian or Pacific Islander alone or in combination percent - Calculation (P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPOTCPCT - Population Some Other Race alone or in combination percent - Calculation (P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPHSP - Population Hispanic - Calculation P0020002

    POPNHSP - Population Non-Hispanic - Calculation P0020003

    POPHSPPCT - Population Hispanic percent - Calculation P0020002 / P0010001 * 100

    POPNHSPPCT - Population Non-Hispanic percent - Calculation P0020003 / P0010001 * 100

    POP18OV - Population 18 years and over - Calculation P0030001

    POP18OVPCT - Population 18 years and over percent - Calculation P0030001 / P0010001 * 100

    HUTOT - Housing Units Total - Calculation H0010001

    HUOCC - Housing Units Occupied - Calculation H0010002

    HUVAC - Housing Units Vacant - Calculation H0010003

    HUOCCPCT - Housing Units Occupied percent - Calculation H0010002 / H0010001 * 100

    HUVACPCT - Housing Units Vacant percent - Calculation H0010003 / H0010001 * 100

    POPGQ - Population Group Quarters - Calculation P0050001

    POPGQIN - Population Group Quarters - Institutionalized - Calculation P0050002

    POPGQNI - Population Group Quarters - Non-Institutionalized - Calculation P0050007

    POPGQPCT - Population Group Quarters percent - Calculation P0050001 / P0010001 * 100

    POPGQINPCT - Population Group Quarters - Institutionalized percent - Calculation P0050002 / P0010001 * 100

    POPGQNIPCT - Population Group Quarters - Non-Institutionalized percent - Calculation P0050007 / P0010001 * 100

    POPTOT2010 - Population Total 2010 - Calculation

    POPCHG - Population Change from 2010 to 2020 - Calculation

    POPCHGPCT - Population Percent Change from 2010 to 2020 - Calculation

  4. M

    Malta MT: Population Density: People per Square Km

    • ceicdata.com
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    CEICdata.com, Malta MT: Population Density: People per Square Km [Dataset]. https://www.ceicdata.com/en/malta/population-and-urbanization-statistics/mt-population-density-people-per-square-km
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Malta
    Variables measured
    Population
    Description

    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;

  5. a

    CENSUS 2020 PL94171 MONTANA PLACE

    • ceic-mtdoc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Aug 23, 2021
    + more versions
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    Montana Department of Commerce (2021). CENSUS 2020 PL94171 MONTANA PLACE [Dataset]. https://ceic-mtdoc.opendata.arcgis.com/datasets/census-2020-pl94171-montana-place
    Explore at:
    Dataset updated
    Aug 23, 2021
    Dataset authored and provided by
    Montana Department of Commerce
    Area covered
    Description

    Population and Housing data for Census Places (cities, towns, CDPs) within the State of Montana was compiled from the PL 94-171 Redistricting Summary files released by the U.S. Census Bureau for the 2020 Decennial Census. This data set was created by the Montana Department of Commerce for use by the citizens of Montana and the general public. TIGER shapefiles were joined to the tabular summary file data to create this data set. A subset of variables from the release were selected for this dataset. A description of each variable and calculations are provided here.

    VINTAGE - Decennial Census vintage year - Calculation

    SUMLEV - Geography summary level - Calculation

    GEOID - Geography ID - Calculation

    NAME - Geography Name - Calculation

    AREALAND - Area of land in square meters - Calculation

    AREAWATR - Area of water in square meters - Calculation

    INTPTLAT - Geography point latitude - Calculation

    INTPTLON - Geography point longitude - Calculation

    POPTOT - Population Total - Calculation P0010001

    POPPCAP - Population per square mile - Calculation P0010001 / (AREALAND / 2589988.110336)

    POPWH - Population White alone - Calculation P0010003

    POPBL - Population Black alone - Calculation P0010004

    POPAI - Population American Indian or Alaska Native alone - Calculation P0010005

    POPAS - Population Asian alone - Calculation P0010006

    POPNH - Population Native Hawaiian or Pacific Islander alone - Calculation P0010007

    POPOT - Population Some other Race alone - Calculation P0010008

    POP2MO - Population 2 or more races - Calculation P0010009

    POPWHPCT - Population White alone percent - Calculation P0010003 / P0010001 * 100

    POPBLPCT - Population Black alone percent - Calculation P0010004 / P0010001 * 100

    POPAIPCT - Population American Indian or Alaska Native alone percent - Calculation P0010005 / P0010001 * 100

    POPASPCT - Population Asian alone percent - Calculation P0010006 / P0010001 * 100

    POPNHPCT - Population Native Hawaiian or Pacific Islander alone percent - Calculation P0010007 / P0010001 * 100

    POPOTPCT - Population Some other Race alone percent - Calculation P0010008 / P0010001 * 100

    POP2MOPCT - Population 2 or more races percent - Calculation P0010009 / P0010001 * 100

    POPWHC - Population White alone or in combination - Calculation P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071

    POPBLC - Population Black alone or in combination - Calculation P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071

    POPAIC - Population American Indian or Alaska Native alone or in combination - Calculation P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071

    POPASC - Population Asian alone or in combination - Calculation P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071

    POPNHC - Population Native Hawaiian or Pacific Islander alone or in combination - Calculation P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPOTC - Population Some Other Race alone or in combination - Calculation P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPWHCPCT - Population White alone or in combination percent - Calculation (P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071)/ P0010001 * 100

    POPBLCPCT - Population Black alone or in combination percent - Calculation (P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071)/ P0010001 * 100

    POPAICPCT - Population American Indian or Alaska Native alone or in combination percent - Calculation (P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPASCPCT - Population Asian alone or in combination percent - Calculation (P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPNHCPCT - Population Native Hawaiian or Pacific Islander alone or in combination percent - Calculation (P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPOTCPCT - Population Some Other Race alone or in combination percent - Calculation (P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPHSP - Population Hispanic - Calculation P0020002

    POPNHSP - Population Non-Hispanic - Calculation P0020003

    POPHSPPCT - Population Hispanic percent - Calculation P0020002 / P0010001 * 100

    POPNHSPPCT - Population Non-Hispanic percent - Calculation P0020003 / P0010001 * 100

    POP18OV - Population 18 years and over - Calculation P0030001

    POP18OVPCT - Population 18 years and over percent - Calculation P0030001 / P0010001 * 100

    HUTOT - Housing Units Total - Calculation H0010001

    HUOCC - Housing Units Occupied - Calculation H0010002

    HUVAC - Housing Units Vacant - Calculation H0010003

    HUOCCPCT - Housing Units Occupied percent - Calculation H0010002 / H0010001 * 100

    HUVACPCT - Housing Units Vacant percent - Calculation H0010003 / H0010001 * 100

    POPGQ - Population Group Quarters - Calculation P0050001

    POPGQIN - Population Group Quarters - Institutionalized - Calculation P0050002

    POPGQNI - Population Group Quarters - Non-Institutionalized - Calculation P0050007

    POPGQPCT - Population Group Quarters percent - Calculation P0050001 / P0010001 * 100

    POPGQINPCT - Population Group Quarters - Institutionalized percent - Calculation P0050002 / P0010001 * 100

    POPGQNIPCT - Population Group Quarters - Non-Institutionalized percent - Calculation P0050007 / P0010001 * 100

    POPTOT2010 - Population Total 2010 - Calculation

    POPCHG - Population Change from 2010 to 2020 - Calculation

    POPCHGPCT - Population Percent Change from 2010 to 2020 - Calculation

  6. M

    Malta MT: Population Density: Inhabitants per sq km

    • ceicdata.com
    Updated Sep 15, 2025
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    CEICdata.com (2025). Malta MT: Population Density: Inhabitants per sq km [Dataset]. https://www.ceicdata.com/en/malta/social-demography-non-oecd-member-annual/mt-population-density-inhabitants-per-sq-km
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    Dataset updated
    Sep 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Malta, Malta, Montana
    Description

    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.

  7. d

    UA Census Urbanized Areas, 1990 - Montana

    • datamed.org
    Updated Dec 13, 2011
    + more versions
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    (2011). UA Census Urbanized Areas, 1990 - Montana [Dataset]. https://datamed.org/display-item.php?repository=0012&idName=ID&id=56d4b84de4b0e644d3132225
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    Dataset updated
    Dec 13, 2011
    Area covered
    Montana
    Description

    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.

  8. d

    Human Population in the Western United States (1900 - 2000)

    • dataone.org
    • data.wu.ac.at
    Updated Dec 1, 2016
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    Steven Hanser, USGS-FRESC, Snake River Field Station (2016). Human Population in the Western United States (1900 - 2000) [Dataset]. https://dataone.org/datasets/e4102f83-6264-4903-9105-e7d5e160b98a
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    Dataset updated
    Dec 1, 2016
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Steven Hanser, USGS-FRESC, Snake River Field Station
    Area covered
    Variables measured
    FID, AREA, FIPS, STATE, Shape, COUNTY, STFIPS, PC10-00, PC20-10, PC30-20, and 30 more
    Description

    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.

  9. Fort Keogh site, station Custer County, MT (FIPS 30017), study of human...

    • dataone.org
    • search.dataone.org
    • +1more
    Updated Mar 11, 2015
    + more versions
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    Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; EcoTrends Project (2015). Fort Keogh site, station Custer County, MT (FIPS 30017), study of human population density in units of numberPerKilometerSquared on a yearly timescale [Dataset]. https://dataone.org/datasets/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F6907%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; EcoTrends Project
    Time period covered
    Jan 1, 1880 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    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.

  10. Appendix G. Correlations between population density and nest predation rates...

    • figshare.com
    html
    Updated Jun 1, 2023
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    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin (2023). Appendix G. Correlations between population density and nest predation rates for bird species. [Dataset]. http://doi.org/10.6084/m9.figshare.3562407.v1
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    htmlAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Wileyhttps://www.wiley.com/
    Authors
    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

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

  11. n

    Data from: An improved understanding of ungulate population dynamics using...

    • data-staging.niaid.nih.gov
    • data.niaid.nih.gov
    • +2more
    zip
    Updated Jan 3, 2020
    + more versions
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    Terrill Paterson; Kelly Proffitt; Jay Rotella; Robert Garrott (2020). An improved understanding of ungulate population dynamics using count data: insights from western Montana [Dataset]. http://doi.org/10.5061/dryad.34tmpg4g4
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    zipAvailable download formats
    Dataset updated
    Jan 3, 2020
    Dataset provided by
    Montana State University
    ,
    Authors
    Terrill Paterson; Kelly Proffitt; Jay Rotella; Robert Garrott
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Montana, Western Montana
    Description

    Understanding the dynamics of ungulate populations is critical given their ecological and economic importance. In particular, the ability to evaluate the evidence for potential drivers of variation in population trajectories is important for informed management. However, the use of age ratio data (e.g., juveniles:adult females) as an index of variation in population dynamics is hindered by a lack of statistical power and difficult interpretation. Here, we show that the use of a population model based on count, classification and harvest data can dramatically improve the understanding of ungulate population dynamics by: 1) providing estimates of vital rates (e.g., per capita recruitment and population growth) that are easier to interpret and more useful to managers than age ratios and 2) increasing the power to assess potential sources of variation in key vital rates. We used a time series of elk (Cervus canadensis) spring count and classification data (2004 to 2016) and fall harvest data from hunting districts in western Montana to construct a population model to estimate vital rates and assess evidence for an association between a series of environmental covariates and indices of predator abundance on per capita recruitment rates of elk calves. Our results suggest that per capita recruitment rates were negatively associated with cold and wet springs, and severe winters, and positively associated with summer precipitation. In contrast, an analysis of the raw age ratio data failed to detect these relationships. Our approach based on a population model provided estimates of the region-wide mean per capita recruitment rate (mean = 0.25, 90% CI = 0.21, 0.29), temporal variation in hunting-district-specific recruitment rates (minimum = 0.09; 90% CI = [0.07, 0.11], maximum = 0.43; 90% CI = [0.38, 0.48]), and annual population growth rates (minimum = 0.83; 90% CI = [0.78, 0.87], maximum = 1.20; 90% CI = [1.11, 1.29]). We recommend using routinely collected population count and classification data and a population modeling approach rather than interpreting estimated age ratios as a substantial improvement in understanding population dynamics.

  12. M

    Malta MT: Survey Mean Consumption or Income per Capita: Total Population:...

    • ceicdata.com
    Updated May 15, 2018
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    CEICdata.com (2018). Malta MT: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate [Dataset]. https://www.ceicdata.com/en/malta/poverty/mt-survey-mean-consumption-or-income-per-capita-total-population-annualized-average-growth-rate
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    Dataset updated
    May 15, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2014
    Area covered
    Malta, Malta
    Description

    Malta MT: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data was reported at 3.670 % in 2014. Malta MT: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data is updated yearly, averaging 3.670 % from Dec 2014 (Median) to 2014, with 1 observations. Malta MT: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate 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: Poverty. The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

  13. a

    CENSUS 2020 PL94171 MONTANA STATE SENATE DISTRICT

    • hub.arcgis.com
    Updated Aug 23, 2021
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    Montana Department of Commerce (2021). CENSUS 2020 PL94171 MONTANA STATE SENATE DISTRICT [Dataset]. https://hub.arcgis.com/maps/mtdoc::census-2020-pl94171-montana-state-senate-district/about
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    Dataset updated
    Aug 23, 2021
    Dataset authored and provided by
    Montana Department of Commerce
    Area covered
    Description

    Population and Housing data for State Legislature Senate Districts within the State of Montana was compiled from the PL 94-171 Redistricting Summary files released by the U.S. Census Bureau for the 2020 Decennial Census.

    This data set was created by the Montana Department of Commerce for use by the citizens of Montana and the general public. TIGER shapefiles were joined to the tabular summary file data to create this data set. A subset of variables from the release were selected for this dataset. A description of each variable and calculations are provided here.

    VINTAGE - Decennial Census vintage year - Calculation

    SUMLEV - Geography summary level - Calculation

    GEOID - Geography ID - Calculation

    NAME - Geography Name - Calculation

    AREALAND - Area of land in square meters - Calculation

    AREAWATR - Area of water in square meters - Calculation

    INTPTLAT - Geography point latitude - Calculation

    INTPTLON - Geography point longitude - Calculation

    POPTOT - Population Total - Calculation P0010001

    POPPCAP - Population per square mile - Calculation P0010001 / (AREALAND / 2589988.110336)

    POPWH - Population White alone - Calculation P0010003

    POPBL - Population Black alone - Calculation P0010004

    POPAI - Population American Indian or Alaska Native alone - Calculation P0010005

    POPAS - Population Asian alone - Calculation P0010006

    POPNH - Population Native Hawaiian or Pacific Islander alone - Calculation P0010007

    POPOT - Population Some other Race alone - Calculation P0010008

    POP2MO - Population 2 or more races - Calculation P0010009

    POPWHPCT - Population White alone percent - Calculation P0010003 / P0010001 * 100

    POPBLPCT - Population Black alone percent - Calculation P0010004 / P0010001 * 100

    POPAIPCT - Population American Indian or Alaska Native alone percent - Calculation P0010005 / P0010001 * 100

    POPASPCT - Population Asian alone percent - Calculation P0010006 / P0010001 * 100

    POPNHPCT - Population Native Hawaiian or Pacific Islander alone percent - Calculation P0010007 / P0010001 * 100

    POPOTPCT - Population Some other Race alone percent - Calculation P0010008 / P0010001 * 100

    POP2MOPCT - Population 2 or more races percent - Calculation P0010009 / P0010001 * 100

    POPWHC - Population White alone or in combination - Calculation P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071

    POPBLC - Population Black alone or in combination - Calculation P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071

    POPAIC - Population American Indian or Alaska Native alone or in combination - Calculation P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071

    POPASC - Population Asian alone or in combination - Calculation P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071

    POPNHC - Population Native Hawaiian or Pacific Islander alone or in combination - Calculation P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPOTC - Population Some Other Race alone or in combination - Calculation P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPWHCPCT - Population White alone or in combination percent - Calculation (P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071)/ P0010001 * 100

    POPBLCPCT - Population Black alone or in combination percent - Calculation (P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071)/ P0010001 * 100

    POPAICPCT - Population American Indian or Alaska Native alone or in combination percent - Calculation (P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPASCPCT - Population Asian alone or in combination percent - Calculation (P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPNHCPCT - Population Native Hawaiian or Pacific Islander alone or in combination percent - Calculation (P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPOTCPCT - Population Some Other Race alone or in combination percent - Calculation (P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPHSP - Population Hispanic - Calculation P0020002

    POPNHSP - Population Non-Hispanic - Calculation P0020003

    POPHSPPCT - Population Hispanic percent - Calculation P0020002 / P0010001 * 100

    POPNHSPPCT - Population Non-Hispanic percent - Calculation P0020003 / P0010001 * 100

    POP18OV - Population 18 years and over - Calculation P0030001

    POP18OVPCT - Population 18 years and over percent - Calculation P0030001 / P0010001 * 100

    HUTOT - Housing Units Total - Calculation H0010001

    HUOCC - Housing Units Occupied - Calculation H0010002

    HUVAC - Housing Units Vacant - Calculation H0010003

    HUOCCPCT - Housing Units Occupied percent - Calculation H0010002 / H0010001 * 100

    HUVACPCT - Housing Units Vacant percent - Calculation H0010003 / H0010001 * 100

    POPGQ - Population Group Quarters - Calculation P0050001

    POPGQIN - Population Group Quarters - Institutionalized - Calculation P0050002

    POPGQNI - Population Group Quarters - Non-Institutionalized - Calculation P0050007

    POPGQPCT - Population Group Quarters percent - Calculation P0050001 / P0010001 * 100

    POPGQINPCT - Population Group Quarters - Institutionalized percent - Calculation P0050002 / P0010001 * 100

    POPGQNIPCT - Population Group Quarters - Non-Institutionalized percent - Calculation P0050007 / P0010001 * 100

    POPTOT2010 - Population Total 2010 - Calculation

    POPCHG - Population Change from 2010 to 2020 - Calculation

    POPCHGPCT - Population Percent Change from 2010 to 2020 - Calculation

  14. Data from: Fort Keogh site, station Custer County, MT (FIPS 30017), study of...

    • search.dataone.org
    • portal.edirepository.org
    Updated Mar 11, 2015
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    U.S. Bureau of the Census; Inter-University Consortium for Political and Social Research; EcoTrends Project (2015). Fort Keogh site, station Custer County, MT (FIPS 30017), study of percent urban population in units of percent on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F6906%2F2
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    Dataset updated
    Mar 11, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    U.S. Bureau of the Census; Inter-University Consortium for Political and Social Research; EcoTrends Project
    Time period covered
    Jan 1, 1880 - Jan 1, 2000
    Area covered
    Variables measured
    YEAR, S_DEV, S_ERR, ID_OBS, N_TRACE, N_INVALID, N_MISSING, N_EXPECTED, N_OBSERVED, N_ESTIMATED, and 3 more
    Description

    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.

  15. f

    Appendix A. Table with detailed information forest stands studied in western...

    • wiley.figshare.com
    • figshare.com
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    Updated May 30, 2023
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    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin (2023). Appendix A. Table with detailed information forest stands studied in western Montana, USA. [Dataset]. http://doi.org/10.6084/m9.figshare.3562425.v1
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    htmlAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Wiley
    Authors
    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Western Montana, United States, Montana
    Description

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

  16. M

    Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of...

    • ceicdata.com
    Updated Mar 15, 2018
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    CEICdata.com (2018). Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate [Dataset]. https://www.ceicdata.com/en/malta/poverty/mt-survey-mean-consumption-or-income-per-capita-bottom-40-of-population-annualized-average-growth-rate
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    Dataset updated
    Mar 15, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2014
    Area covered
    Malta
    Description

    Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 3.570 % in 2015. Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 3.570 % from Dec 2015 (Median) to 2015, with 1 observations. Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate 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: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

  17. M

    Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of...

    • ceicdata.com
    Updated Dec 15, 2024
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    CEICdata.com (2024). Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day [Dataset]. https://www.ceicdata.com/en/malta/poverty/mt-survey-mean-consumption-or-income-per-capita-bottom-40-of-population-2011-ppp-per-day
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    Dataset updated
    Dec 15, 2024
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2009 - Dec 1, 2014
    Area covered
    Malta, Malta
    Description

    Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data was reported at 23.250 Intl $/Day in 2014. This records an increase from the previous number of 18.640 Intl $/Day for 2009. Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data is updated yearly, averaging 20.945 Intl $/Day from Dec 2009 (Median) to 2014, with 2 observations. The data reached an all-time high of 23.250 Intl $/Day in 2014 and a record low of 18.640 Intl $/Day in 2009. Malta MT: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day 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: Poverty. Mean consumption or income per capita (2011 PPP $ per day) used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in PovcalNet. The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

  18. Appendix B. Taxonomic information for bird species examined in this study.

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    Updated Jun 1, 2023
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    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin (2023). Appendix B. Taxonomic information for bird species examined in this study. [Dataset]. http://doi.org/10.6084/m9.figshare.3562422.v1
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Wileyhttps://www.wiley.com/
    Authors
    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Taxonomic information for bird species examined in this study.

  19. f

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

    • figshare.com
    • wiley.figshare.com
    html
    Updated May 31, 2023
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    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin (2023). Appendix F. Changes in nest predation with both PC axes for bird species. [Dataset]. http://doi.org/10.6084/m9.figshare.3562410.v1
    Explore at:
    htmlAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Wiley
    Authors
    Joseph A. LaManna; Amy B. Hemenway; Vanna Boccadori; Thomas E. Martin
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

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

  20. 马耳他 MT:人口密度:每平方公里人口

    • ceicdata.com
    Updated Sep 15, 2025
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    CEICdata.com (2025). 马耳他 MT:人口密度:每平方公里人口 [Dataset]. https://www.ceicdata.com/zh-hans/malta/population-and-urbanization-statistics/mt-population-density-people-per-square-km
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    Dataset updated
    Sep 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    马耳他
    Variables measured
    Population
    Description

    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。

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Statista (2024). Population density in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/
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Population density in the U.S. 2023, by state

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29 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 21, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

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.

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