100+ datasets found
  1. g

    United States Estimated Water Sources - 2020 Census Blocks | gimi9.com

    • gimi9.com
    Updated Nov 26, 2024
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    (2024). United States Estimated Water Sources - 2020 Census Blocks | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_united-states-estimated-water-sources-2020-census-blocks/
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    Dataset updated
    Nov 26, 2024
    Area covered
    United States
    Description

    This dataset contains the results of EPAs estimates for domestic water supply in The United States for 2020 census blocks. The file is a comma-delimited text file, which contains records for 2020 census blocks. This data can be used to estimate the number of housing units and populations that are estimated to be using either private water supplies such as domestic wells or connected to a community water system. These results are estimates and should not be used to convey exact counts of well or public water users. For a full description of the data, please refer to the GitHub page: https://github.com/USEPA/ORD_Water_Source_2020/tree/main/outputs.

  2. o

    Bengaluru Urban and Karnataka Water Bodies Census Data - Collections -...

    • data.opencity.in
    Updated Sep 11, 2024
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    (2024). Bengaluru Urban and Karnataka Water Bodies Census Data - Collections - OpenCity - Urban Data Portal [Dataset]. https://data.opencity.in/dataset/bengaluru-urban-and-karnataka-water-bodies-census-data
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    Dataset updated
    Sep 11, 2024
    License

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

    Area covered
    Bengaluru Urban, Bengaluru, Karnataka
    Description

    Data from the Jal Dharohar Water bodies census conducted by the Department of Water Resources, River Development and Ganga Rejuvenation. The census was conducted in 2018-19 and the data released in 2023.

  3. s

    Census Water Bodies, 2000 - San Francisco Bay Area, California

    • searchworks.stanford.edu
    zip
    Updated Oct 10, 2016
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    (2016). Census Water Bodies, 2000 - San Francisco Bay Area, California [Dataset]. https://searchworks.stanford.edu/view/mb777jk0330
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    zipAvailable download formats
    Dataset updated
    Oct 10, 2016
    Area covered
    San Francisco Bay Area, California, San Francisco
    Description

    This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

  4. w

    Spatial Agent Central Asia Water and Energy Data

    • wbwaterdata.org
    Updated Jul 12, 2020
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    (2020). Spatial Agent Central Asia Water and Energy Data [Dataset]. https://wbwaterdata.org/dataset/spatial-agent-central-asia-water-and-energy-data
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    Dataset updated
    Jul 12, 2020
    License

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

    Area covered
    Central Asia
    Description

    45 data sources of hydrological/hydromet, water quality, water resource, environmental, agro-environmental and development indicators. Datasets include: Achieving National Development Strategy in Tajikistan (Nurek), Water Transition, Central Asia Hydrometeorology Modernization Project, Lake Levels, Night Lights, Landscan Population Density, Satellite Precipitation, Solar Energy Data, Earth Wind Map, Land Cover Comparison, Earth Engine NDVI Analysis, Kyrgyz Republic DRM Portal, Climate Adaptation and Mitigation Program for Aral Sea Basin, Croplands, Watershed Mapper, Forest Cover, Kyrgyz Republic Hydromet Portal, World Water Quality, Human Footprint, Glacier Inventory, MODIS layers, Cropping Extent, Fire Data, Surface Water Explorer, Human Influence Index, Development Data, GADAS (Agriculture) Wind Potential, ESRI Water Balance, Air Quality, Tajikistan Hydromet Website, Open Street Map Data, Land-Water Changes, Himawari, GEOGRLAM RAPP, Google Earth Data, GEOSS Portal, USGS Global Visualization Viewer (GloVis), STRM Topography Data, UNEP Database, DIVA GIS Country Boundaries, ARCGIS Hub- Water Bodies, ARCGIS Hub- World Cities, WUEMoCA, World Bank Climate Change Portal

  5. A

    Population Density of Mexico

    • data.amerigeoss.org
    • hub.arcgis.com
    • +1more
    csv, esri rest +4
    Updated Feb 8, 2019
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    AmeriGEOSS (2019). Population Density of Mexico [Dataset]. https://data.amerigeoss.org/ro/dataset/population-density-of-mexico
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    html, geojson, csv, kml, esri rest, zipAvailable download formats
    Dataset updated
    Feb 8, 2019
    Dataset provided by
    AmeriGEOSS
    Area covered
    Mexico
    Description

    This map shows the population density of Mexico in relation to freshwater sources and water bodies.

  6. a

    2020 Census Block Groups Top 50 American Community Survey Data with Seattle...

    • hub.arcgis.com
    Updated Feb 6, 2024
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    City of Seattle ArcGIS Online (2024). 2020 Census Block Groups Top 50 American Community Survey Data with Seattle Neighborhoods [Dataset]. https://hub.arcgis.com/datasets/ff59dc88bfab4eb3bc4cd11eaf67ec2a
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    Dataset updated
    Feb 6, 2024
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Description

    U.S. Census Bureau 2020 block groups within the City of Seattle with American Community Survey (ACS) 5-year series data of frequently requested topics. Data is pulled from block group tables for the most recent ACS vintage. Seattle neighborhood geography of Council Districts, Comprehensive Plan Growth Areas are also included based on block group assignment.The census block groups have been assigned to a neighborhood based on the distribution of the total population from the 2020 decennial census for the component census blocks. If the majority of the population in the block group were inside the boundaries of the neighborhood, the block group was assigned wholly to that neighborhood.Feature layer created for and used in the Neighborhood Profiles application.The attribute data associated with this map is updated annually to contain the most currently released American Community Survey (ACS) 5-year data and contains estimates and margins of error. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintages: 2023ACS Table(s): Select fields from the tables listed here.Data downloaded from: Census Bureau's Explore Census Data The 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 US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).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 file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  7. d

    Atlas of Water Resources and Irrigation in Africa

    • search.dataone.org
    Updated Nov 17, 2014
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    Food and Agriculture Organization of the United Nations (FAO) (2014). Atlas of Water Resources and Irrigation in Africa [Dataset]. https://search.dataone.org/view/Atlas_of_Water_Resources_and_Irrigation_in_Africa.xml
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    Dataset updated
    Nov 17, 2014
    Dataset provided by
    Regional and Global Biogeochemical Dynamics Data (RGD)
    Authors
    Food and Agriculture Organization of the United Nations (FAO)
    Time period covered
    Jan 1, 1961
    Area covered
    Description

    The Land and Water Development Division of FAO is developing a global information system of water and agriculture with the objective to provide users with comprehensive information on the state of agricultural water management across the world. Such a system should help in assessing the role of irrigation in global food production and the relation between irrigation and water scarcity. The system combines classical country-based statistics on all aspects of agricultural water management (water resources and use, irrigation, drainage, etc.), known as AQUASTAT, and a set of maps, data and models combined through a Geographical Information System (GIS). Africa is the first continent for which the information system has been completed.

    The Atlas of Water Resources and Irrigation in Africa is available on CD-ROM published as part of FAO Land and Water Digital Media Series (#13). GIS coverages from the Atlas can be downloaded from the FAO-UN GeoNetwork Portal to Spatial Data and Information at [http://www.fao.org/geonetwork/srv/en/main.search]. The coverages are also available as interactive maps.

    The CD-ROM contains all the information collected and processed concerning the African continent, namely:

    1. A set of digital tables and maps on water resources and irrigation at continental level and by river basin (major basins and sub-basins) resulting from simulations on the water balance model.
    2. A set of GIS coverages and Avenue scripts on water resources and irrigation (Annex 1) intended for advanced users willing to adapt the model to their specific needs.
    3. A georeferenced database of African dams in Microsoft® Excel.
    4. AQUASTAT country profiles for the 53 countries of Africa.

    GIS coverages and interactive maps from FAO-UN GeoNetwork include:

    1. Hydrological Basins in Africa
    2. Inland Water Bodies in Africa
    3. Rivers of Africa
    4. Database of African Dams
    5. Irrigation Cropping Pattern Zones in Africa

    The programme was partly financed by the Dutch Directorate-General for International Cooperation through the Associate Professional Officer Programme. The geographical modelling tool was initially developed with technical assistance of the Center for Research in Water Resources of the University of Texas in Austin under the joint FAO/UNESCO project Water Balance of Africa.

  8. Census Designated Place

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Jun 1, 2023
    + more versions
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    Esri (2023). Census Designated Place [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/esri::census-designated-place
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    Dataset updated
    Jun 1, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  9. United Kingdom: monitored water bodies 2018/19, by band classes of fish...

    • statista.com
    Updated Feb 13, 2020
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    Statista (2020). United Kingdom: monitored water bodies 2018/19, by band classes of fish population [Dataset]. https://www.statista.com/statistics/696607/monitored-water-bodies-by-band-classes-of-fish-population/
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    Dataset updated
    Feb 13, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United Kingdom
    Description

    The statistic displays the distribution of water bodies assessed for fish by the Water Framework Directive (WFD) in the United Kingdom (UK) in 2019, by band classes of fish population. In 2019, it was found that *** percent of assessed water bodies classified with a "bad" fish population. More information on fishing and other water sports in the UK can be found in the report Water sports in the United Kingdom.

  10. Water File - Lakes and Rivers (polygons) - 2011 Census

    • open.canada.ca
    • ouvert.canada.ca
    • +1more
    gml, html, shp
    Updated Feb 24, 2022
    + more versions
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    Statistics Canada (2022). Water File - Lakes and Rivers (polygons) - 2011 Census [Dataset]. https://open.canada.ca/data/en/dataset/448ec403-6635-456b-8ced-d3ac24143add
    Explore at:
    gml, shp, htmlAvailable download formats
    Dataset updated
    Feb 24, 2022
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Jan 1, 2011
    Description

    Water files are provided for the mapping of inland and coastal waters, Great Lakes and the St. Lawrence River. These files were created to be used in conjunction with the boundary files.

  11. c

    Population

    • data.clevelandohio.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Aug 21, 2023
    + more versions
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    Cleveland | GIS (2023). Population [Dataset]. https://data.clevelandohio.gov/datasets/population/explore
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    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows total population count by sex and age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released 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 the population that are considered dependent (ages 65+ and <18). 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: 2019-2023
    ACS Table(s): B01001

    The United States Census Bureau's American Community Survey (ACS):
    This 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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • 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 file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.




  12. ACS Children in Immigrant Families Variables - Boundaries

    • demographics.roanokecountyva.gov
    • mapdirect-fdep.opendata.arcgis.com
    • +1more
    Updated Nov 27, 2018
    + more versions
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    Esri (2018). ACS Children in Immigrant Families Variables - Boundaries [Dataset]. https://demographics.roanokecountyva.gov/maps/71f0c22b02f54372a9e33bd5ec57fb79
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    Dataset updated
    Nov 27, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows children by nativity of parents by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released 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 children who are in immigrant families (children who are foreign born or live with at least one parent who is foreign born). 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: 2019-2023ACS Table(s): B05009Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 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. For more information about ACS layers, visit the FAQ. 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:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).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 file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  13. Lakes and Rivers (polygons), Boundary files - 2016 Census

    • open.canada.ca
    gml, html, shp
    Updated Feb 23, 2022
    + more versions
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    Statistics Canada (2022). Lakes and Rivers (polygons), Boundary files - 2016 Census [Dataset]. https://open.canada.ca/data/en/dataset/d0cdef71-9343-46c3-b2e7-c1ded5907686
    Explore at:
    shp, gml, htmlAvailable download formats
    Dataset updated
    Feb 23, 2022
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    There are two types of boundary files: cartographic and digital. Cartographic boundary files portray the geographic areas using only the major land mass of Canada and its coastal islands. Digital boundary files portray the full extent of the geographic areas, including the coastal water area.

  14. u

    Census MAF/TIGER database

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Jun 6, 2011
    + more versions
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    Earth Data Analysis Center (2011). Census MAF/TIGER database [Dataset]. http://gstore.unm.edu/apps/rgis/datasets/4cc47ede-98c2-4951-83de-3c3ec3f2adeb/metadata/FGDC-STD-001-1998.html
    Explore at:
    csv(5), gml(5), geojson(5), kml(5), xls(5), zip(1), json(5), shp(5)Available download formats
    Dataset updated
    Jun 6, 2011
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 2010
    Area covered
    West Bounding Coordinate -106.381796 East Bounding Coordinate -105.39073 North Bounding Coordinate 34.997338 South Bounding Coordinate 34.259983, Socorro County (35053)
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Census Bureau includes landmarks in the MTDB for locating special features and to help enumerators during field operations. Some of the more common landmark types include area landmarks such as airports, cemeteries, parks, schools, and churches and other religious institutions. The Census Bureau added landmark features to MTDB on an as-needed basis and made no attempt to ensure that all instances of a particular feature were included. The presence or absence of a landmark such as a hospital or prison does not mean that the living quarters associated with that landmark were geocoded to that census tabulation block or excluded from the census enumeration. The Area Landmark Shapefile does not include military installations or water bodies because they each appear in their own separate shapefiles, MIL.shp and AREAWATER.shp respectively.

  15. N

    Nigeria NG: Population with Access to Improved Drinking Water Sources: % of...

    • ceicdata.com
    Updated Sep 15, 2018
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    CEICdata.com (2018). Nigeria NG: Population with Access to Improved Drinking Water Sources: % of Total Population [Dataset]. https://www.ceicdata.com/en/nigeria/social-access-to-services-non-oecd-member-annual/ng-population-with-access-to-improved-drinking-water-sources--of-total-population
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    Dataset updated
    Sep 15, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2009 - Dec 1, 2020
    Area covered
    Nigeria
    Description

    Nigeria NG: Population with Access to Improved Drinking Water Sources: % of Total Population data was reported at 22.000 % in 2020. This records an increase from the previous number of 21.000 % for 2019. Nigeria NG: Population with Access to Improved Drinking Water Sources: % of Total Population data is updated yearly, averaging 18.000 % from Dec 2000 (Median) to 2020, with 21 observations. The data reached an all-time high of 22.000 % in 2020 and a record low of 14.000 % in 2001. Nigeria NG: Population with Access to Improved Drinking Water Sources: % of Total Population data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Nigeria – Table NG.OECD.GGI: Social: Access to Services: Non OECD Member: Annual.

  16. u

    Census MAF/TIGER database

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Jun 6, 2011
    + more versions
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    Earth Data Analysis Center (2011). Census MAF/TIGER database [Dataset]. http://gstore.unm.edu/apps/rgis/datasets/0071d1bc-aaed-4929-81f2-ae6e621692a6/metadata/FGDC-STD-001-1998.html
    Explore at:
    csv(5), geojson(5), kml(5), shp(5), xls(5), zip(1), gml(5), json(5)Available download formats
    Dataset updated
    Jun 6, 2011
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 2010
    Area covered
    Torrance County (35057), West Bounding Coordinate -105.18183 East Bounding Coordinate -104.275358 North Bounding Coordinate 35.194203 South Bounding Coordinate 34.59276
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Census Bureau includes landmarks in the MTDB for locating special features and to help enumerators during field operations. Some of the more common landmark types include area landmarks such as airports, cemeteries, parks, schools, and churches and other religious institutions. The Census Bureau added landmark features to MTDB on an as-needed basis and made no attempt to ensure that all instances of a particular feature were included. The presence or absence of a landmark such as a hospital or prison does not mean that the living quarters associated with that landmark were geocoded to that census tabulation block or excluded from the census enumeration. The Area Landmark Shapefile does not include military installations or water bodies because they each appear in their own separate shapefiles, MIL.shp and AREAWATER.shp respectively.

  17. u

    Census MAF/TIGER database

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Jun 6, 2011
    + more versions
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    Earth Data Analysis Center (2011). Census MAF/TIGER database [Dataset]. http://gstore.unm.edu/apps/rgis/datasets/9d306d90-f0e0-494e-9f35-38535869b49d/metadata/FGDC-STD-001-1998.html
    Explore at:
    gml(5), zip(1), xls(5), csv(5), geojson(5), json(5), kml(5), shp(5)Available download formats
    Dataset updated
    Jun 6, 2011
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 2010
    Area covered
    Rio Arriba County (35039), West Bounding Coordinate -108.962251 East Bounding Coordinate -107.422394 North Bounding Coordinate 37.000006 South Bounding Coordinate 36.036345
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Census Bureau includes landmarks in the MTDB for locating special features and to help enumerators during field operations. Some of the more common landmark types include area landmarks such as airports, cemeteries, parks, schools, and churches and other religious institutions. The Census Bureau added landmark features to MTDB on an as-needed basis and made no attempt to ensure that all instances of a particular feature were included. The presence or absence of a landmark such as a hospital or prison does not mean that the living quarters associated with that landmark were geocoded to that census tabulation block or excluded from the census enumeration. The Area Landmark Shapefile does not include military installations or water bodies because they each appear in their own separate shapefiles, MIL.shp and AREAWATER.shp respectively.

  18. Fiji Population with Access to Improved Drinking Water Sources: % of Total...

    • ceicdata.com
    Updated Mar 15, 2016
    + more versions
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    CEICdata.com (2016). Fiji Population with Access to Improved Drinking Water Sources: % of Total Population [Dataset]. https://www.ceicdata.com/en/fiji/social-access-to-services-non-oecd-member-annual/population-with-access-to-improved-drinking-water-sources--of-total-population
    Explore at:
    Dataset updated
    Mar 15, 2016
    Dataset provided by
    CEIC Data
    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, 2011 - Dec 1, 2022
    Area covered
    Fiji
    Description

    Fiji Population with Access to Improved Drinking Water Sources: % of Total Population data was reported at 41.860 % in 2022. This records an increase from the previous number of 41.740 % for 2021. Fiji Population with Access to Improved Drinking Water Sources: % of Total Population data is updated yearly, averaging 40.440 % from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 41.860 % in 2022 and a record low of 39.230 % in 2000. Fiji Population with Access to Improved Drinking Water Sources: % of Total Population data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Fiji – Table FJ.OECD.GGI: Social: Access to Services: Non OECD Member: Annual.

  19. a

    Elderly Population

    • hub.arcgis.com
    • data.clevelandohio.gov
    Updated Aug 21, 2023
    + more versions
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    Elderly Population [Dataset]. https://hub.arcgis.com/datasets/ClevelandGIS::demographic-profiles?layer=11
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    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows demographic context for senior well-being work. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released 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.

    The layer is symbolized to show the percentage of population aged 65 and up (senior population). 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: 2019-2023
    ACS Table(s): B01001, B09021, B17020, B18101, B23027, B25072, B25093, B27010, B28005, C27001B-I

    The United States Census Bureau's American Community Survey (ACS):
    This 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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • 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 file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

  20. a

    Census Tract Top 50 American Community Survey Data

    • data-seattlecitygis.opendata.arcgis.com
    • data.seattle.gov
    Updated May 19, 2023
    + more versions
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    City of Seattle ArcGIS Online (2023). Census Tract Top 50 American Community Survey Data [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::census-tract-top-50-american-community-survey-data/about
    Explore at:
    Dataset updated
    May 19, 2023
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Description

    Data from: American Community Survey, 5-year SeriesKing County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 of over 50 attributes of the most requested data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): DP02, DP03, DP04, DP05Data downloaded from: Census Bureau's Explore Census Data The 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 US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).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 file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

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(2024). United States Estimated Water Sources - 2020 Census Blocks | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_united-states-estimated-water-sources-2020-census-blocks/

United States Estimated Water Sources - 2020 Census Blocks | gimi9.com

Explore at:
Dataset updated
Nov 26, 2024
Area covered
United States
Description

This dataset contains the results of EPAs estimates for domestic water supply in The United States for 2020 census blocks. The file is a comma-delimited text file, which contains records for 2020 census blocks. This data can be used to estimate the number of housing units and populations that are estimated to be using either private water supplies such as domestic wells or connected to a community water system. These results are estimates and should not be used to convey exact counts of well or public water users. For a full description of the data, please refer to the GitHub page: https://github.com/USEPA/ORD_Water_Source_2020/tree/main/outputs.

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