13 datasets found
  1. TIGER/Line Shapefile, 2022, State, Oregon, OR, Census Tract

    • catalog.data.gov
    • datasets.ai
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, State, Oregon, OR, Census Tract [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-state-oregon-or-census-tract
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    United States Census Bureauhttp://census.gov/
    Area covered
    Oregon
    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, 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.

  2. d

    Population Density in the Western United States (Individuals / ha)

    • search.dataone.org
    Updated Oct 29, 2016
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    Steve Hanser, USGS-FRESC, Snake River Field Station (2016). Population Density in the Western United States (Individuals / ha) [Dataset]. https://search.dataone.org/view/04f758d8-9caa-40ab-af6e-bb72b1b7a007
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    Dataset updated
    Oct 29, 2016
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Steve Hanser, USGS-FRESC, Snake River Field Station
    Area covered
    Variables measured
    Value, ObjectID
    Description

    This map of human habitation was developed, following a modification of Schumacher et al. (2000), by incorporating 2000 U.S Census Data and land ownership. The 2000 U.S. Census Block data and ownership map of the western United States were used to correct the population density for uninhabited public lands. All census blocks in the western United States were merged into one shapefile which was then clipped to contain only those areas found on private or indian reservation lands because human habitation on federal land is negligible. The area (ha) for each corrected polygon was calculated and the 2000 census block data table was joined to the shapefile. In a new field, population density (individuals/ha) corrected for public land in census blocks was calculated . SHAPEGRID in ARC/INFO was used to convert population density values to grid with 90m resolution.

  3. 2020 Census Tracts

    • catalog.data.gov
    • geohub.oregon.gov
    • +2more
    Updated Jan 31, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (2025). 2020 Census Tracts [Dataset]. https://catalog.data.gov/dataset/census-tracts
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    This data layer is an element of the Oregon GIS Framework. 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.

  4. Oregon Population density

    • knoema.es
    • knoema.de
    csv, json, sdmx, xls
    Updated Jun 28, 2023
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    Knoema (2023). Oregon Population density [Dataset]. https://knoema.es/atlas/Estados-Unidos-de-Am%C3%A9rica/Oregon/Population-density
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    csv, json, xls, sdmxAvailable download formats
    Dataset updated
    Jun 28, 2023
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    2011 - 2022
    Area covered
    Oregón, Estados Unidos
    Variables measured
    Population density
    Description

    17,05 (persons per sq. km) in 2022.

  5. d

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

    • dataone.org
    • datadiscoverystudio.org
    • +1more
    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.

  6. Eastern Oregon Agricultural Research Center site, station Harney County, OR...

    • search.dataone.org
    • portal.edirepository.org
    Updated Mar 11, 2015
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    Inter-University Consortium for Political and Social Research; U.S. Bureau of the Census; EcoTrends Project (2015). Eastern Oregon Agricultural Research Center site, station Harney County, OR (FIPS 41025), study of human population density in units of numberPerKilometerSquared on a yearly timescale [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fecotrends%2F4479%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, 1900 - 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 Eastern Oregon Agricultural Research Center (EOA) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

  7. Eastern Oregon Agricultural Research Center site, station Harney County, OR...

    • 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). Eastern Oregon Agricultural Research Center site, station Harney County, OR (FIPS 41025), 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%2F4478%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, 1890 - 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 Eastern Oregon Agricultural Research Center (EOA) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

  8. o

    20 Richest Counties in Oregon

    • oregon-demographics.com
    Updated Jun 20, 2024
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    20 Richest Counties in Oregon [Dataset]. https://www.oregon-demographics.com/counties_by_population
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    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.oregon-demographics.com/terms_and_conditionshttps://www.oregon-demographics.com/terms_and_conditions

    Area covered
    Oregon
    Description

    A dataset listing Oregon counties by population for 2024.

  9. d

    2015 Cartographic Boundary File, Urban Area-State-County for Oregon,...

    • catalog.data.gov
    Updated Jan 13, 2021
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    (2021). 2015 Cartographic Boundary File, Urban Area-State-County for Oregon, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2015-cartographic-boundary-file-urban-area-state-county-for-oregon-1-5000001
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    Dataset updated
    Jan 13, 2021
    Description

    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.

  10. e

    Cumulative Human Impacts to California Current Marine Ecosystems, 2008

    • knb.ecoinformatics.org
    • dataone.org
    Updated Dec 7, 2018
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    Benjamin Halpern; Carrie Kappel; Kimberly Selkoe; Fiorenza Micheli; Colin Ebert; Caitlin Kontgis; Caitlin Crain; Rebecca Martone; Christine Shearer; Sarah Teck (2018). Cumulative Human Impacts to California Current Marine Ecosystems, 2008 [Dataset]. http://doi.org/10.5063/F11Z42N8
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    Dataset updated
    Dec 7, 2018
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Benjamin Halpern; Carrie Kappel; Kimberly Selkoe; Fiorenza Micheli; Colin Ebert; Caitlin Kontgis; Caitlin Crain; Rebecca Martone; Christine Shearer; Sarah Teck
    Time period covered
    Jan 1, 2008
    Area covered
    Description

    Quantitative assessment of spatial patterns of all human uses of the oceans and their cumulative effects is needed for implementing ecosystem-based management, marine protected areas, and ocean zoning. Researchers applied methods developed to map cumulative impacts globally to the California Current using more comprehensive and higher-quality data for 25 human activities and 19 marine ecosystems. They first surveyed experts in six sub-regions of the California Current to explore geographic variation in the effects of threats. A workshop was held to use decision theory to evaluate the tradeoffs of using expert opinion to assess threats and associated impacts. Data on ecosystems and threats were gathered at resolutions of approximately one square kilometer. By synthesizing information and inferences regarding anticipated impacts of threats, project participants developed a spatially-explicit understanding of the distribution and magnitude of human threats in the California Current. The analysis indicates where protection and threat mitigation are most needed in the California Current and reveals that coastal ecosystems near high human population density and the continental shelves off Oregon and Washington are the most heavily impacted. Climate change is the top threat, and impacts from multiple threats are ubiquitous. Remarkably, these results were highly spatially correlated with the global results for this region (R2=.92), suggesting that the global model provides guidance to areas without local data or resources to conduct similar regional-scale analyses. This dataset contains raster layers for the 25 human activities and 19 ecosystems used to build the cumulative impact model in the California Current marine ecosystems. A zip file for all impacts, a zip file for all ecosystems, and a raster of the final model are included along with the individual impacts and ecosystems raster layers. For more information on methods, see Halpern et al, Mapping cumulative human impacts to California Current marine ecosystems. Conservation Letters, 2009. https://doi.org/10.1111/j.1755-263X.2009.00058.x

  11. Z

    Data from: Coastal upwelling may strengthen the controls of herbivory and...

    • data.niaid.nih.gov
    • zenodo.org
    • +1more
    Updated Jul 29, 2022
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    Menge, Bruce (2022). Coastal upwelling may strengthen the controls of herbivory and light over the population dynamics of Hedophyllum sessile in the Oregon rocky intertidal [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_6928509
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    Dataset updated
    Jul 29, 2022
    Dataset provided by
    Menge, Bruce
    Spiecker, Barbara
    License

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

    Area covered
    Oregon
    Description

    Survival of early life history stages is critical to the successful establishment of benthic populations. Although light availability and herbivory are likely to influence passage of marine macroalgae through a "recruitment bottleneck" at the sporeling stage, the interactive effect of these factors on subsequent community patterns of macroalgae is not well studied. We experimentally tested the effect of light and grazing on sporelings of the common intertidal kelp Hedophyllum sessile. Studies were conducted at two sites along the Oregon coast: Strawberry Hill (an intermittent upwelling region) and Cape Blanco North (a persistent upwelling region). Herbivory and light availability were manipulated and kelp performance metrics (density and length) were measured monthly from May to November 2019. We found that the effects of herbivory and light availability were pronounced at Cape Blanco North but negligible at Strawberry Hill. At Cape Blanco North, herbivory had strong but opposing effects on density and length of H. sessile. Kelp density was higher in treatments without herbivores while kelp length was greater in treatments with herbivores. Responses also differed with life history stage. Herbivory had negative effects on juvenile kelp but positive effects on adult kelp while light availability had opposing effects on length of juvenile and adult kelps. Length of juvenile kelps was higher in shaded treatments while length of adult kelps was higher in unshaded treatments. Our study highlights the potential importance of coastal geophysical processes (and subsequently, nutrients) in modifying herbivore and light effects on population dynamics of H. sessile, and how these dynamics may be further influenced by different characteristics of the kelp (i.e., demographic traits and life history stages).

  12. o

    All equity focus areas

    • regionalbarometer.oregonmetro.gov
    • hub.arcgis.com
    Updated Oct 3, 2019
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    Metro (2019). All equity focus areas [Dataset]. https://regionalbarometer.oregonmetro.gov/datasets/drcMetro::all-equity-focus-areas/about
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    Dataset updated
    Oct 3, 2019
    Dataset authored and provided by
    Metro
    Area covered
    Description

    Equity focus areas are Census tracts that represent communities where the rate of people of color (POC) or people with limited English proficiency (LEP) is greater than the regional average, or people with low income, i.e., incomes equal to or less than 200% of the Federal Poverty Level (LI). Additionally the density (persons per acre) of one or more of these populations must be double the regional average. The original development of the equity focus areas occurred in conjunction with the 2018 Regional Transportation Plan and were informed through discussions of the transportation equity work group, regional advisory committees (TPAC, MTAC, JPACT, and MPAC), four Regional Leadership Forums, and direction from Metro Council.The equity focus areas here are based on data from the American Community Survey 2017 5-year estimates. We include census tracts outside the Metro boundary. However, only census tracts inside the Metro jurisdictional boundary were used when determining criteria to qualify a census tract as an equity focus area.Tract-level compilation and aggregation of population estimates, including sets of attributes related to sex, age, race/ethnicity, language, income, and educational attainment. Estimates are accompanied by margins of error. Aggregate estimates are accompanied by recalculated margins of error. Geometry source: 2010 Census. Attribute source: 2013-2017 ACS 5-year estimates, tables B01001, B03002, B06001, B06007, B06009, B16004, C16001, and C17002.

  13. d

    2019 Cartographic Boundary KML, 2010 Urban Areas (UA) within 2010 County and...

    • catalog.data.gov
    Updated Jan 15, 2021
    + more versions
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    (2021). 2019 Cartographic Boundary KML, 2010 Urban Areas (UA) within 2010 County and Equivalent for Oregon, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2019-cartographic-boundary-kml-2010-urban-areas-ua-within-2010-county-and-equivalent-for-oregon
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    Dataset updated
    Jan 15, 2021
    Description

    The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.

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    Learn how you can add new datasets to our index.

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U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, State, Oregon, OR, Census Tract [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-state-oregon-or-census-tract
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TIGER/Line Shapefile, 2022, State, Oregon, OR, Census Tract

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Dataset updated
Jan 27, 2024
Dataset provided by
United States Department of Commercehttp://commerce.gov/
United States Census Bureauhttp://census.gov/
Area covered
Oregon
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, 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.

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