38 datasets found
  1. a

    WA County Boundaries

    • data-wadnr.opendata.arcgis.com
    • geo.wa.gov
    • +3more
    Updated Mar 14, 2017
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    Washington State Department of Natural Resources (2017). WA County Boundaries [Dataset]. https://data-wadnr.opendata.arcgis.com/datasets/wa-county-boundaries
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    Dataset updated
    Mar 14, 2017
    Dataset authored and provided by
    Washington State Department of Natural Resources
    Area covered
    Description

    Washington State County Boundaries including Department of Natural Resources (DNR) county codes. This data is created from the WA Public Land Survey source data maintained by the DNR.WA County Boundaries Metadata

  2. WSDOT - County Boundaries

    • idaho-epscor-gem3-uidaho.hub.arcgis.com
    Updated Oct 29, 2012
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    WSDOT Online Map Center (2012). WSDOT - County Boundaries [Dataset]. https://idaho-epscor-gem3-uidaho.hub.arcgis.com/datasets/WSDOT::wsdot-county-boundaries
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    Dataset updated
    Oct 29, 2012
    Dataset provided by
    Washington State Department of Transportationhttp://www.wsdot.wa.gov/
    Authors
    WSDOT Online Map Center
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This data set depicts the county boundaries of the State of Washington. This data set was created by the Washington State Department of Natural Resources to meet that agency's need for land surveying, land title, and land management GIS data. It is part of the Washington State Cadastral Framework Data set. The Washington Cadastral Framework data represents an integrated set of geographic-referencing data covering the State of Washington. It is derived from Land Surveys, DNR Orthophotos, USGS 7-1/2 minute quadrangles, DNR Ownership Tract Book, and various public organizations. The initial data population includes Public Land Survey System information, state boundary, county boundaries, and Department of Natural Resource parcel information.If you have any questions about this data, please contact Thomas A. Blake, GIS Data Products Supervisor - blaket@wsdot.wa.gov - (360) 570-2363. If you're having trouble viewing these services, please contact our Online Map Support.Attribute Definitions:Jurisdiction Name – Provides the name of the county.County Number – Provides the counties number.County FIPS Code - The unique code that identifies the counties of Washington State.

  3. a

    WA State Funding

    • broadband-wacommerce.hub.arcgis.com
    • hub.arcgis.com
    Updated Sep 19, 2023
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    Timmons@WACOM (2023). WA State Funding [Dataset]. https://broadband-wacommerce.hub.arcgis.com/datasets/8291214c287a4ad6993bafd94d2ebf9f
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    Dataset updated
    Sep 19, 2023
    Dataset authored and provided by
    Timmons@WACOM
    Area covered
    Description

    Counties in WA State with state funding awards. For use in the State Funding Awards map.

  4. a

    WA State Funding Awards

    • hub.arcgis.com
    Updated Jun 12, 2023
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    Timmons@WACOM (2023). WA State Funding Awards [Dataset]. https://hub.arcgis.com/maps/468e7f23714343b28704bba4e7dcf529
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    Dataset updated
    Jun 12, 2023
    Dataset authored and provided by
    Timmons@WACOM
    Area covered
    Description

    Broadband State Funding layer for the WA State Broadband Office Digital Equity Dashboard. WA State Funding - Counties contains an overview of grant award programs in each county. CERB PWB WSBO Combined Awards table contains additional information about individual projects in each county.This feature layer is referenced by the WA State Funding Awards Map (Web Map).

  5. w

    20 Richest Counties in Washington

    • washington-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). 20 Richest Counties in Washington [Dataset]. https://www.washington-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.washington-demographics.com/terms_and_conditionshttps://www.washington-demographics.com/terms_and_conditions

    Area covered
    Washington
    Description

    A dataset listing Washington counties by population for 2024.

  6. a

    Washington State City Urban Growth Areas

    • hub.arcgis.com
    • geo.wa.gov
    • +1more
    Updated May 1, 2025
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    Washington State Geospatial Portal (2025). Washington State City Urban Growth Areas [Dataset]. https://hub.arcgis.com/maps/wa-geoservices::washington-state-city-urban-growth-areas
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    Dataset updated
    May 1, 2025
    Dataset authored and provided by
    Washington State Geospatial Portal
    Area covered
    Description

    Unincorporated Urban Growth Areas (UGA) as defined by the Growth Management Act (GMA). The annual update is conducted by collecting UGA polygons directly from each of Washington's 39 counties. As of 2025, there are 27 counties with UGAs.All UGA polygons are normalized against the Department of Revenue's (DOR) "City Boundaries" layer (shared to the Washington Geoportal a.k.a. the GIS Open Data site: geo.wa.gov). The City Boundaries layer was processed into this UGA layer such that any overlapping area of UGA polygons (from authoritative individual counties) was erased. Since DOR polygons and county-sourced UGA polygons do not have perfect topology, many slivers resulted after the erase operation. These are attempted to be irradicated by these processing steps. "Multipart To Singlepart" Esri tool; exploded all polygons to be individualSlivers were mathematically identified using a 4 acre area threshold and a 0.3 "thinness ratio" threshold as described by Esri's "Polygon Sliver" tool. These slivers are merged into the neighboring features using Esri's "Eliminate" tool.Polygons that are less than 5,000 sq. ft. and not part of a DOR city (CITY_NM = Null) were also merged via the "Eliminate" tool. (many very small slivers were manually found yet mathematically did not meet the thinness ratio threshold)The final 8 polygons less than 25 sq. ft. were manually deleted (also slivers but were not lined up against another feature and missed by the "Eliminate" tool runs)Dissolved all features back to multipart using all fieldsAll UGAs polygons remaining are unincorporated areas beyond the city limits. Any polygon with CITY_NM populated originated from the DOR "City Boundaries" layer. The DOR's City Boundaries are updated quarterly by DOR. For the purposes of this UGA layer, the city boundaries was downloaded one time (4/24/2025) and will not be updated quarterly. Therefore, if precise city limits are required by any user of UGA boundaries, please refer to the city boundaries layer and conduct any geoprocessing needed. The DOR's "City Boundaries" layer is available here:https://www.arcgis.com/home/item.html?id=69fcb668dc8d49ea8010b6e33e42a13aData is updated in conjunction with the annual statewide parcel layer update. Latest update completed April 2025.

  7. K

    Virginia Cities and Counties

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 13, 2018
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    State of Virginia (2018). Virginia Cities and Counties [Dataset]. https://koordinates.com/layer/97232-virginia-cities-and-counties/
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    shapefile, mapinfo mif, dwg, geodatabase, kml, geopackage / sqlite, csv, pdf, mapinfo tabAvailable download formats
    Dataset updated
    Sep 13, 2018
    Dataset authored and provided by
    State of Virginia
    Area covered
    Description

    The VA_TOWN dataset is a feature class component of the Virginia Administrative Boundaries dataset from the Virginia Geographic Information Network (VGIN). VA_COUNTY represents the best available city and county boundary information to VGIN.VGIN initially sought to develop an improved locality and town boundary dataset in late 2013, spurred by response of the Virginia Administrative Boundaries Workgroup community. The feature class initially started from the locality boundaries from the Census TIGER dataset for Virginia. VGIN solicited input from localities in Virginia through the Road Centerlines data submission process as well as through public forums such as the Virginia Administrative Boundaries Workgroup and VGIN listservs. Data received were analyzed and incorporated into the VA_COUNTY feature class where locality data were a superior representation of the city or county boundary.

    © Virginia Geographic Information Network (VGIN), and the Census and Localities and Towns submitting data to the project

    This layer is a component of Feature classes representing locality (county, city, and town) boundaries in the Commonwealth of Virginia..

  8. o

    Data from: US County Boundaries

    • public.opendatasoft.com
    • smartregionidf.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 27, 2017
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    (2017). US County Boundaries [Dataset]. https://public.opendatasoft.com/explore/dataset/us-county-boundaries/
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    json, csv, excel, geojsonAvailable download formats
    Dataset updated
    Jun 27, 2017
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    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. 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, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  9. w

    Limited English Proficiency v2 Map

    • geo.wa.gov
    • hub.arcgis.com
    Updated Jun 26, 2019
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    Washington State Military Department (2019). Limited English Proficiency v2 Map [Dataset]. https://geo.wa.gov/maps/c70de16e18b6474db25a27983ac3adf2
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    Dataset updated
    Jun 26, 2019
    Dataset authored and provided by
    Washington State Military Department
    Area covered
    Description

    Revised Limited English Proficiency dataAs Of: 6/27/2019There are two data sources for the LEP map. LEP County layer represents OFM 2016 “estimate of population with limited English proficiency for the state and counties.” LEP County Subdivision and Census tract layers represent 2015 Census “Language spoken at home by ability to speak English for the population 5 years and over.” The both data sets were trimmed to display LEP speakers of at least 1,000 or 5% of the population.Point Of Contact:Lewis LujánLimited English Proficiency CoordinatorMitigation & Recovery SectionWashington Emergency Management DivisionOffice: (253) 512-7138 | Mobile: (253) 651-6185lewis.lujan@mil.wa.gov | www.mil.wa.govOffice Hours: Tues-Fri 7:00 a.m. – 5:30 p.m.Links:OFM :https://www.ofm.wa.gov/sites/default/files/public/legacy/pop/subject/ofm_pop_limited_english_proficiency_estimates_2016.xlsxCensus:https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_15_5YR_B16001&prodType=table

  10. d

    Digital terrain model of upper North Fork Toutle River valley, Washington,...

    • catalog.data.gov
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). Digital terrain model of upper North Fork Toutle River valley, Washington, derived from historical topographic maps [Dataset]. https://catalog.data.gov/dataset/digital-terrain-model-of-upper-north-fork-toutle-river-valley-washington-derived-from-hist
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Washington, North Fork Toutle River, North Fork Toutle River
    Description

    This digital terrain model represents historical elevations along the valley of the North Fork Toutle River upstream of its confluence with the Green River in Cowlitz and Skamania Counties, Washington. Most elevations were derived from U.S. Geological Survey 1:62,500 scale topographic quadrangle maps published from 1953 to 1958 that were derived from aerial photographs taken in 1951 and 1952. Elevations representing the bed of Spirit Lake, at the head of the valley, were derived from a bathymetric map based on survey data from 1974. Elevations are in units of meters and have been adjusted to the North American Vertical Datum of 1988.

  11. a

    CERB Funding Awards

    • broadband-wacommerce.hub.arcgis.com
    • hub.arcgis.com
    Updated Sep 19, 2023
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    Timmons@WACOM (2023). CERB Funding Awards [Dataset]. https://broadband-wacommerce.hub.arcgis.com/maps/ba14c13de7884de281d99858586828e8
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    Dataset updated
    Sep 19, 2023
    Dataset authored and provided by
    Timmons@WACOM
    Area covered
    Description

    Counties in WA State with CERB funding awards. For use in the WA State Funding Awards Map (Web Map).

  12. d

    Spatial database of the Cardwell quadrangle, Washington and Mercer Counties,...

    • catalog.data.gov
    Updated Jan 5, 2021
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    U.S. Geological Survey (Point of Contact) (2021). Spatial database of the Cardwell quadrangle, Washington and Mercer Counties, Kentucky (NGMDB) [Dataset]. https://catalog.data.gov/dataset/spatial-database-of-the-cardwell-quadrangle-washington-and-mercer-counties-kentucky-ngmdb
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    Dataset updated
    Jan 5, 2021
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Kentucky
    Description

    This record is maintained in the National Geologic Map Database (NGMDB). The NGMDB is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information, developed according to standards defined by the cooperators, i.e., the USGS and the Association of American State Geologists (AASG). Included in this system is a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 90,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies. For more information, please see http://ngmdb.usgs.gov/.

  13. w

    Current Parcels

    • geo.wa.gov
    • hub.arcgis.com
    Updated Apr 28, 2025
    + more versions
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    Washington State Geospatial Portal (2025). Current Parcels [Dataset]. https://geo.wa.gov/maps/569bb6050d634ff7a7f2462378ca974c
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    Dataset updated
    Apr 28, 2025
    Dataset authored and provided by
    Washington State Geospatial Portal
    Area covered
    Description

    The Washington State Parcels Project provides a statewide data set of tax parcels attributes that cover those counties that currently have digital tax parcels. Attribute data has been normalized so that the field names are the same across all counties. The data set contains the tax parcel identification number, situs addresses, the Department of Revenue land use codes, improvement and land values, and a link to the county's assessor's website for parcel information (if it exists).

  14. a

    STATES

    • hub.arcgis.com
    • mce-data-uscensus.hub.arcgis.com
    • +1more
    Updated Feb 4, 2024
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    US Census Bureau (2024). STATES [Dataset]. https://hub.arcgis.com/datasets/9990b3e300b64f6c98d00dc571c4e1d9
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    Dataset updated
    Feb 4, 2024
    Dataset authored and provided by
    US Census Bureau
    Area covered
    Description

    This layer shows Households by Type. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show Average Household Size and the Total Households in a bi-variate map. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): B11001, B25010, B25044, DP02, DP04Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

  15. w

    Soil Survey Geographic (SSURGO) Soil Polygons for the State of Rhode Island:...

    • data.wu.ac.at
    Updated May 17, 2013
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    University of Rhode Island Geospatial Extension Program (2013). Soil Survey Geographic (SSURGO) Soil Polygons for the State of Rhode Island: Bristol, Kent, Newport, Providence, and Washington Counties [Dataset]. https://data.wu.ac.at/schema/data_gov/NWYyMWQwNzUtMmFiOC00YTdiLWFkZjAtMGE1OTgxYWY4Njcw
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    Dataset updated
    May 17, 2013
    Dataset provided by
    University of Rhode Island Geospatial Extension Program
    Area covered
    Rhode Island, e3e9b3612991f5261d65c1f36924e1c67aa742ed
    Description

    2013 VERSION 6 Spatial: This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. Special soil features layers (point and line features) are available as a separate download. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes (via the MUKEY attribute field) in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. Attribute data is also created and joined to the spatial data created by RIGIS and the RI NRCS.

  16. d

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

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

  17. a

    WA Counties

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    Updated Nov 21, 2016
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    Washington State Labor and Industries (2016). WA Counties [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/LNI::li-regions?layer=0
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    Dataset updated
    Nov 21, 2016
    Dataset authored and provided by
    Washington State Labor and Industries
    Area covered
    Description

    Feature layer displaying Labor and Industries' region boundaries within Washington State. L&I's regions are individually labeled, as well as the counties that reside within each regions borders.Last update: BH (11/21/2016).APPLICATION LAYER - DO NOT DELETE

  18. a

    COUNTIES

    • covid19-uscensus.hub.arcgis.com
    • mce-data-uscensus.hub.arcgis.com
    • +1more
    Updated Feb 2, 2024
    + more versions
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    US Census Bureau (2024). COUNTIES [Dataset]. https://covid19-uscensus.hub.arcgis.com/maps/USCensus::counties-41
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    Dataset updated
    Feb 2, 2024
    Dataset authored and provided by
    US Census Bureau
    Area covered
    Description

    This layer shows Population. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the point by Population Density and size of the point by Total Population. The size of the symbol represents the total count of housing units. Population Density was calculated based on the total population and area of land fields, which both came from the U.S. Census Bureau. Formula used for Calculating the Pop Density (B01001_001E/GEO_LAND_AREA_SQ_KM). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): B01001, B09020Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

  19. Race and Ethnicity 2018-2022 - STATES

    • mce-data-uscensus.hub.arcgis.com
    • covid19-uscensus.hub.arcgis.com
    • +1more
    Updated Feb 5, 2024
    + more versions
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    US Census Bureau (2024). Race and Ethnicity 2018-2022 - STATES [Dataset]. https://mce-data-uscensus.hub.arcgis.com/maps/973245d9cd914f58a8fe87baacea1f4a
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    Dataset updated
    Feb 5, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    US Census Bureau
    Area covered
    Description

    This layer shows Race and Ethnicity. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of population that are Hispanic or Latino (of any race). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): B02001, B03001, DP05Data downloaded from: CensusBureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

  20. a

    WSBO Funding Awards

    • hub.arcgis.com
    Updated Sep 20, 2023
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    Timmons@WACOM (2023). WSBO Funding Awards [Dataset]. https://hub.arcgis.com/maps/e6cdcac1037141d6a3f058c3dcc9d06a
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    Dataset updated
    Sep 20, 2023
    Dataset authored and provided by
    Timmons@WACOM
    Area covered
    Description

    Counties in WA State with WSBO funding awards. For use in the State Funding Awards map.

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Washington State Department of Natural Resources (2017). WA County Boundaries [Dataset]. https://data-wadnr.opendata.arcgis.com/datasets/wa-county-boundaries

WA County Boundaries

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11 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 14, 2017
Dataset authored and provided by
Washington State Department of Natural Resources
Area covered
Description

Washington State County Boundaries including Department of Natural Resources (DNR) county codes. This data is created from the WA Public Land Survey source data maintained by the DNR.WA County Boundaries Metadata

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