81 datasets found
  1. K

    Seattle City Council Districts

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 15, 2022
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    City of Seattle, Washington (2022). Seattle City Council Districts [Dataset]. https://koordinates.com/layer/110944-seattle-city-council-districts/
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    dwg, csv, shapefile, pdf, kml, mapinfo tab, geopackage / sqlite, mapinfo mif, geodatabaseAvailable download formats
    Dataset updated
    Nov 15, 2022
    Dataset authored and provided by
    City of Seattle, Washington
    Area covered
    Description

    Geospatial data about Seattle City Council Districts. Export to CAD, GIS, PDF, CSV and access via API.

  2. a

    Seattle Streets

    • data-seattlecitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated Nov 13, 2024
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    City of Seattle ArcGIS Online (2024). Seattle Streets [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/seattle-streets
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    Dataset updated
    Nov 13, 2024
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Description

    Streets data includes: Arterial Classification, Street Names, Block Number, Direction, One-way, Surface Width, Surface Type, Pavement Condition, Speed Limit, Percent Slope. From the Hansen Asset Management System:The linework is from the SND(Street Network Database) which can be found at our open data site - https://data-seattlecitygis.opendata.arcgis.com/datasets/street-network-database-snd. | Attribute Information: https://www.seattle.gov/Documents/Departments/SDOT/GIS/Seattle_Streets_OD.pdf | Update Cycle: Weekly| Contact Email: DOT_IT_GIS@seattle.gov--- Common SDOT queries and data downloads | Arterial Classification: of Seattle StreetsARTCLASS IN(1,2,3,4)| Transit Classification: of Seattle StreetsTRANCLASS IN(1,2,3,4,5,6)

  3. QuickFacts: Seattle city, Washington

    • census.gov
    csv
    Updated Feb 25, 2022
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    United States Census Bureau > Communications Directorate - Center for New Media and Promotion (2022). QuickFacts: Seattle city, Washington [Dataset]. https://www.census.gov/quickfacts/fact/faq/seattlecitywashington/POP010210
    Explore at:
    csvAvailable download formats
    Dataset updated
    Feb 25, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United States Census Bureau > Communications Directorate - Center for New Media and Promotion
    License

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

    Area covered
    Seattle, Washington
    Description

    U.S. Census Bureau QuickFacts statistics for Seattle city, Washington. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

  4. w

    Washington Cities by Population

    • washington-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Washington Cities by Population [Dataset]. https://www.washington-demographics.com/cities_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
    Tacoma, Washington
    Description

    A dataset listing Washington cities by population for 2024.

  5. K

    Seattle City Light Poles

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 15, 2022
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    City of Seattle, Washington (2022). Seattle City Light Poles [Dataset]. https://koordinates.com/layer/110952-seattle-city-light-poles/
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    mapinfo mif, mapinfo tab, kml, dwg, geopackage / sqlite, pdf, geodatabase, shapefile, csvAvailable download formats
    Dataset updated
    Nov 15, 2022
    Dataset authored and provided by
    City of Seattle, Washington
    Area covered
    Description

    Geospatial data about Seattle City Light Poles. Export to CAD, GIS, PDF, CSV and access via API.

  6. N

    Seattle, WA Annual Population and Growth Analysis Dataset: A Comprehensive...

    • neilsberg.com
    csv, json
    Updated Jul 30, 2024
    + more versions
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    Neilsberg Research (2024). Seattle, WA Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in Seattle from 2000 to 2023 // 2024 Edition [Dataset]. https://www.neilsberg.com/insights/seattle-wa-population-by-year/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jul 30, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Washington, Seattle
    Variables measured
    Annual Population Growth Rate, Population Between 2000 and 2023, Annual Population Growth Rate Percent
    Measurement technique
    The data presented in this dataset is derived from the 20 years data of U.S. Census Bureau Population Estimates Program (PEP) 2000 - 2023. To measure the variables, namely (a) population and (b) population change in ( absolute and as a percentage ), we initially analyzed and tabulated the data for each of the years between 2000 and 2023. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Seattle population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Seattle across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

    Key observations

    In 2023, the population of Seattle was 755,078, a 0.79% increase year-by-year from 2022. Previously, in 2022, Seattle population was 749,134, an increase of 2.37% compared to a population of 731,757 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Seattle increased by 190,969. In this period, the peak population was 755,078 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

    Content

    When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

    Data Coverage:

    • From 2000 to 2023

    Variables / Data Columns

    • Year: This column displays the data year (Measured annually and for years 2000 to 2023)
    • Population: The population for the specific year for the Seattle is shown in this column.
    • Year on Year Change: This column displays the change in Seattle population for each year compared to the previous year.
    • Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Seattle Population by Year. You can refer the same here

  7. Neighborhood Map Atlas Neighborhoods

    • data-seattlecitygis.opendata.arcgis.com
    • data.seattle.gov
    • +3more
    Updated Dec 2, 2020
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    City of Seattle ArcGIS Online (2020). Neighborhood Map Atlas Neighborhoods [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::neighborhood-map-atlas-neighborhoods/explore
    Explore at:
    Dataset updated
    Dec 2, 2020
    Dataset provided by
    https://arcgis.com/
    Authors
    City of Seattle ArcGIS Online
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Description

    Neighborhood Map Atlas neighborhoods are derived from the Seattle City Clerk's Office Geographic Indexing Atlas. These are the smallest neighborhood areas and have been supplemented with alternate names from other sources in 2020. They roll up to the district areas. The sub-neighborhood field contains the most common name and the alternate name field is a comma delimited list of all the alternate names.The original atlas is designed for subject indexing of legislation, photographs, and other documents and is an unofficial delineation of neighborhood boundaries used by the City Clerks Office. Sources for this atlas and the neighborhood names used in it include a 1980 neighborhood map produced by the Department of Community Development, Seattle Public Library indexes, a 1984-1986 Neighborhood Profiles feature series in the Seattle Post-Intelligencer, numerous parks, land use and transportation planning studies, and records in the Seattle Municipal Archives. Many of the neighborhood names are traditional names whose meaning has changed over the years, and others derive from subdivision names or elementary school attendance areas.Disclaimer: The Seattle City Clerk's Office Geographic Indexing Atlas is designed for subject indexing of legislation, photographs, and other records in the City Clerk's Office and Seattle Municipal Archives according to geographic area. Neighborhoods are named and delineated in this collection of maps in order to provide consistency in the way geographic names are used in describing records of the Archives and City Clerk, thus allowing precise retrieval of records. The neighborhood names and boundaries are not intended to represent any "official" City of Seattle neighborhood map.

    The Office of the City Clerk makes no claims as to the completeness, accuracy, or content of any data contained in the Geographic Indexing Atlas; nor does it make any representation of any kind, including, but not limited to, warranty of the accuracy or fitness for a particular use; nor are any such warranties to be implied or inferred with respect to the representations furnished herein. The maps are subject to change for administrative purposes of the Office of the City Clerk. Information contained in the site, if used for any purpose other than as an indexing and search aid for the databases of the Office of the City Clerk, is being used at one's own risk.

  8. K

    Seattle City Council districts

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Dec 3, 2018
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    King County, Washington (2018). Seattle City Council districts [Dataset]. https://koordinates.com/layer/98821-seattle-city-council-districts/
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    shapefile, kml, geopackage / sqlite, csv, pdf, geodatabase, mapinfo tab, dwg, mapinfo mifAvailable download formats
    Dataset updated
    Dec 3, 2018
    Dataset authored and provided by
    King County, Washington
    Area covered
    Description

    Shows the Seattle City Council boundaries approved by voters in 2013. The voters approved a measure amending the City of Seattle charter to establish City Council Districts. Full metadata: http://www5.kingcounty.gov/sdc/Metadata.aspx?Layer=sccdst

    © King County

  9. D

    Sold Fleet Equipment

    • seattle.gov
    • cos-data.seattle.gov
    • +5more
    application/rdfxml +5
    Updated Feb 6, 2014
    + more versions
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    City of Seattle (2014). Sold Fleet Equipment [Dataset]. https://www.seattle.gov/fleet-management/vehicle-auction
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    csv, xml, application/rdfxml, tsv, json, application/rssxmlAvailable download formats
    Dataset updated
    Feb 6, 2014
    Dataset authored and provided by
    City of Seattle
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset includes sales data for fleet equipment that was sold in the current and previous three years. This dataset does not include sales data for Seattle City Light (SCL) fleet equipment.

  10. a

    City Hall

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    Updated Jun 25, 2018
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    City of SeaTac (2018). City Hall [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/cityofseatac::city-hall/about
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    Dataset updated
    Jun 25, 2018
    Dataset authored and provided by
    City of SeaTac
    Area covered
    Description

    This point feature contains geographic and attribute information for the purpose of depicting the location of City Hall within the City of SeaTac, Washington.Incorporated in February 1990, the City of SeaTac is located in the Pacific Northwest, approximately midway between the cities of Seattle and Tacoma in the State of Washington. SeaTac is a vibrant community, economically strong, environmentally sensitive, and people-oriented. The City boundaries surround the Seattle-Tacoma International Airport, (approximately 3 square miles in area) which is owned and operated by the Port of Seattle. For additional information regarding the City of SeaTac, its people, or services, please visit https://www.seatacwa.gov. For additional information regarding City GIS data or maps, please visit https://www.seatacwa.gov/our-city/maps-and-gis.

  11. d

    Absolute % Change

    • catalog.data.gov
    • data.seattle.gov
    • +1more
    Updated May 10, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). Absolute % Change [Dataset]. https://catalog.data.gov/dataset/absolute-change
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    Dataset updated
    May 10, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of hexagons 50-acres in area, or several city blocks. The dataset covers the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeAverage maximum afternoon temperature (F)Tree canopy percentage & average afternoon temperature (F)For more information, please see the 2021 Tree Canopy Assessment.

  12. D

    City Annual Stats

    • data.seattle.gov
    • gimi9.com
    • +3more
    application/rdfxml +5
    Updated Oct 22, 2024
    + more versions
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    (2024). City Annual Stats [Dataset]. https://data.seattle.gov/widgets/d7tc-x4mg?mobile_redirect=true
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    application/rssxml, tsv, application/rdfxml, csv, json, xmlAvailable download formats
    Dataset updated
    Oct 22, 2024
    Description

    Tabular data that powers basic monitoring dashboards for the total population, housing and jobs for the City of Seattle. Each record represents the totals for each year since 2000 (and 1995) through the most recently available data. Includes the change from the previous year.


    Sources include:
    For population and housing the April 1 official population estimates are produced by the Washington State Office of Financial Management (OFM). OFM population estimates are cited in numerous statutes using population as criteria for fund allocations, program eligibility, or program operations, and as criteria for determining county participation under the Growth Management Act.

    For jobs the Washington State Employment Security Department, Quarterly Census of Employment and Wages (QCEW) is a federal/state cooperative program that measures employment and wages in industries covered by unemployment insurance. Data are available by industry and county and used to evaluate labor trends, monitor major industry developments and develop training programs.
    These job estimates are from the March dataset from each year (chosen as a representative month when seasonal fluctuations are minimized). The unit of measurement is jobs, rather than working persons or proportional full-time employment equivalents. Employment by census tract totals are broken down by major sector only. To provide more accurate workplace reporting, the Puget Sound Regional Council gathers supplemental data from the Boeing Company, the Office of Washington Superintendent of Public Instruction (OSPI), and governmental units throughout the central Puget Sound region.

  13. K

    Seattle Zoning Boundaries

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 15, 2022
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    City of Seattle, Washington (2022). Seattle Zoning Boundaries [Dataset]. https://koordinates.com/layer/110945-seattle-zoning-boundaries/
    Explore at:
    csv, dwg, shapefile, mapinfo mif, mapinfo tab, geodatabase, kml, geopackage / sqlite, pdfAvailable download formats
    Dataset updated
    Nov 15, 2022
    Dataset authored and provided by
    City of Seattle, Washington
    Area covered
    Description

    Geospatial data about Seattle Zoning Boundaries. Export to CAD, GIS, PDF, CSV and access via API.

  14. d

    Parks Not SPR

    • catalog.data.gov
    • data.seattle.gov
    • +1more
    Updated Jun 7, 2025
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    City of Seattle ArcGIS Online (2025). Parks Not SPR [Dataset]. https://catalog.data.gov/dataset/parks-not-spr
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    Dataset updated
    Jun 7, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    These are Parks that are not owned by Seattle Parks and Recreation but open to the public. These are parks that are made available to the public by other government agencies (Port of Seattle, King County, Washington State Ferries, Seattle Public Utilities, Seattle City Light, Seattle Department of Transportation, UW) and some private owners.The data does not include Private Open Places aka POPs which are Open Places in private buildings for the public use.

  15. d

    2020 Census Tracts - Seattle

    • catalog.data.gov
    • data.seattle.gov
    • +2more
    Updated Feb 28, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). 2020 Census Tracts - Seattle [Dataset]. https://catalog.data.gov/dataset/2020-census-tracts-seattle
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    Dataset updated
    Feb 28, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    2020 census geography including tracts for the city of Seattle, King County, Washington. Excludes partial tracts with very small populations within the city limits along the southern border of the city.Includes assignment of Seattle Community Reporting Areas (CRA-53), Community Reporting Area Groups (neighborhood roll up-13), Council Districts (7-assigned to the tract with the majority of the population based on the distribution of the component census blocks), and Urban Village Demographic Areas (UVDA). UVDA assignments subject to change based on future planning areas.

  16. d

    Public Schools - Absolute % Change

    • catalog.data.gov
    • data.seattle.gov
    • +2more
    Updated Feb 28, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). Public Schools - Absolute % Change [Dataset]. https://catalog.data.gov/dataset/public-schools-absolute-change
    Explore at:
    Dataset updated
    Feb 28, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Public Schools areas which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

  17. D

    Current Fleet Surplus/Auction List

    • seattle.gov
    • data.seattle.gov
    • +5more
    application/rdfxml +5
    Updated Mar 25, 2014
    + more versions
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    City of Seattle (2014). Current Fleet Surplus/Auction List [Dataset]. https://www.seattle.gov/fleet-management/vehicle-auction
    Explore at:
    application/rdfxml, tsv, csv, application/rssxml, xml, jsonAvailable download formats
    Dataset updated
    Mar 25, 2014
    Dataset authored and provided by
    City of Seattle
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Most recent list of fleet equipment sent to auction

  18. M

    Seattle Metro Area Population (1950-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). Seattle Metro Area Population (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/cities/23140/seattle/population
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    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, 1950 - Jul 4, 2025
    Area covered
    Seattle Metropolitan Area, Seattle, United States
    Description

    Chart and table of population level and growth rate for the Seattle metro area from 1950 to 2025.

  19. c

    Seattle Tree Canopy 2016 2021 Council Districts

    • s.cnmilf.com
    • data.seattle.gov
    • +3more
    Updated Feb 28, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). Seattle Tree Canopy 2016 2021 Council Districts [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/seattle-tree-canopy-2016-2021-council-districts
    Explore at:
    Dataset updated
    Feb 28, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, _location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

  20. d

    Seattle Tree Canopy 2016 2021 Public Schools

    • catalog.data.gov
    • data.seattle.gov
    Updated Feb 28, 2025
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    City of Seattle ArcGIS Online (2025). Seattle Tree Canopy 2016 2021 Public Schools [Dataset]. https://catalog.data.gov/dataset/seattle-tree-canopy-2016-2021-public-schools
    Explore at:
    Dataset updated
    Feb 28, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Public Schools areas which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

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City of Seattle, Washington (2022). Seattle City Council Districts [Dataset]. https://koordinates.com/layer/110944-seattle-city-council-districts/

Seattle City Council Districts

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3 scholarly articles cite this dataset (View in Google Scholar)
dwg, csv, shapefile, pdf, kml, mapinfo tab, geopackage / sqlite, mapinfo mif, geodatabaseAvailable download formats
Dataset updated
Nov 15, 2022
Dataset authored and provided by
City of Seattle, Washington
Area covered
Description

Geospatial data about Seattle City Council Districts. Export to CAD, GIS, PDF, CSV and access via API.

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