100+ datasets found
  1. US GDP Marine Construction

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Aug 30, 2018
    + more versions
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    US National Oceanic and Atmospheric Administration (NOAA) (2018). US GDP Marine Construction [Dataset]. https://koordinates.com/layer/20927-us-gdp-marine-construction/
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    mapinfo tab, mapinfo mif, geopackage / sqlite, geodatabase, csv, kml, dwg, pdf, shapefileAvailable download formats
    Dataset updated
    Aug 30, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    US National Oceanic and Atmospheric Administration (NOAA)
    Area covered
    Description

    This layer is a component of ENOW_Counties.

    This map service presents spatial information about the Economics: National Ocean Watch (ENOW) data in the Web Mercator projection. The ENOW data provides time-series data on the ocean and Great Lakes economy, which includes six economic sectors dependent on the oceans and Great Lakes, and measures four economic indicators: Establishments, Employment, Wages, and Gross Domestic Product (GDP). The annual time-series data are available for about 400 coastal counties, 30 coastal states, 8 regions, and the nation. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

    © NOAA Office for Coastal Management

  2. Economic Characteristics by Zip Code Tabulation Area Geographic Data

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). Economic Characteristics by Zip Code Tabulation Area Geographic Data [Dataset]. https://www.johnsnowlabs.com/marketplace/economic-characteristics-by-zip-code-tabulation-area-geographic-data/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    Jan 1, 2010 - Dec 31, 2014
    Area covered
    United States
    Description

    This dataset identifies selected economic characteristics by zip code tabulation areas within the United States. This dataset resulted from the American Community Survey (ACS) conducted from 2010 through 2014. The economic characteristics include employment status, commuting to work, occupation, class of worker, income and benefits, health insurance coverage, and percentage of families and people whose income in the past 12 months is below the poverty level.

  3. d

    American FactFinder

    • dknet.org
    • scicrunch.org
    • +1more
    Updated Sep 19, 2024
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    (2024). American FactFinder [Dataset]. http://identifiers.org/RRID:SCR_002932/resolver/mentions
    Explore at:
    Dataset updated
    Sep 19, 2024
    Description

    Database that provides access to population, housing, economic, and geographic data from several censuses and surveys about the United States, Puerto Rico and the Island Areas. Census data may be compiled into tables, maps and downloadable files, which can be viewed or printed. A large selection of pre-made tables and maps satisfies many information requests. By law, no one is permitted to reveal information from these censuses and surveys that could identify any person, household, or business. The following data are available: * American Community Survey * ACS Content Review * American Housing Survey * Annual Economic Surveys * Annual Surveys of Governments * Census of Governments * Decennial Census * Economic Census * Equal Employment Opportunity (EEO) Tabulation * Population Estimates Program * Puerto Rico Community Survey

  4. K

    US General Exclusive Economic Zone area

    • koordinates.com
    csv, dwg, geodatabase +6
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    noaa.gov, US General Exclusive Economic Zone area [Dataset]. https://koordinates.com/layer/14384-us-general-exclusive-economic-zone-area/
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    mapinfo tab, csv, geodatabase, kml, shapefile, dwg, mapinfo mif, geopackage / sqlite, pdfAvailable download formats
    Dataset provided by
    noaa.gov
    Area covered
    Description

    This layer is sourced from maritimeboundaries.noaa.gov.

    The ENC_General map service displays ENC data within the scale range of 1:600,001 and 1:1,500,000. The ENC data will be updated weekly. This map service is not intended for navigation purpose.

  5. a

    Justice40 Disadvantaged or Partially Disadvantaged Tracts by Race/Ethnicity...

    • hub.arcgis.com
    • regionaldatahub-brag.hub.arcgis.com
    • +1more
    Updated Jun 10, 2022
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    ArcGIS Living Atlas Team (2022). Justice40 Disadvantaged or Partially Disadvantaged Tracts by Race/Ethnicity (Archive) [Dataset]. https://hub.arcgis.com/maps/945b3f2e39a64569ab2d0700a527361b
    Explore at:
    Dataset updated
    Jun 10, 2022
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map uses an archive of Version 1.0 of the CEJST data as a fully functional GIS layer. See an archive of the latest version of the CEJST tool using Version 2.0 of the data released in December 2024 here.This map shows Census tracts throughout the US based on if they are considered disadvantaged or partially disadvantaged according to Justice40 Initiative criteria. This is overlaid with the most recent American Community Survey (ACS) figures from the U.S. Census Bureau to communicate the predominant race that lives within these disadvantaged or partially disadvantaged tracts. Predominance helps us understand the group of population which has the largest count within an area. Colors are more transparent if the predominant race has a similar count to another race/ethnicity group. The colors on the map help us better understand the predominant race or ethnicity:Hispanic or LatinoWhite Alone, not HispanicBlack or African American Alone, not HispanicAsian Alone, not HispanicAmerican Indian and Alaska Native Alone, not HispanicTwo or more races, not HispanicNative Hawaiian and Other Pacific Islander, not HispanicSome other race, not HispanicSearch for any region, city, or neighborhood throughout the US, DC, and Puerto Rico to learn more about the population in the disadvantaged tracts. Click on any tract to learn more. Zoom to your area, filter to your county or state, and save this web map focused on your area to share the pattern with others. You can also use this web map within an ArcGIS app such as a dashboard, instant app, or story. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.Note: Justice40 tracts use 2010-based boundaries, while the most recent ACS figures are offered on 2020-based boundaries. When you click on an area, there will be multiple pop-ups returned due to the differences in these boundaries. From Justice40 data source:"Census tract geographical boundaries are determined by the U.S. Census Bureau once every ten years. This tool utilizes the census tract boundaries from 2010 because they match the datasets used in the tool. The U.S. Census Bureau will update these tract boundaries in 2020.Under the current formula, a census tract will be identified as disadvantaged in one or more categories of criteria:IF the tract is above the threshold for one or more environmental or climate indicators AND the tract is above the threshold for the socioeconomic indicatorsCommunities are identified as disadvantaged by the current version of the tool for the purposes of the Justice40 Initiative if they are located in census tracts that are at or above the combined thresholds in one or more of eight categories of criteria.The goal of the Justice40 Initiative is to provide 40 percent of the overall benefits of certain Federal investments in [eight] key areas to disadvantaged communities. These [eight] key areas are: climate change, clean energy and energy efficiency, clean transit, affordable and sustainable housing, training and workforce development, the remediation and reduction of legacy pollution, [health burdens] and the development of critical clean water infrastructure." Source: Climate and Economic Justice Screening toolPurpose"Sec. 219. Policy. To secure an equitable economic future, the United States must ensure that environmental and economic justice are key considerations in how we govern. That means investing and building a clean energy economy that creates well‑paying union jobs, turning disadvantaged communities — historically marginalized and overburdened — into healthy, thriving communities, and undertaking robust actions to mitigate climate change while preparing for the impacts of climate change across rural, urban, and Tribal areas. Agencies shall make achieving environmental justice part of their missions by developing programs, policies, and activities to address the disproportionately high and adverse human health, environmental, climate-related and other cumulative impacts on disadvantaged communities, as well as the accompanying economic challenges of such impacts. It is therefore the policy of my Administration to secure environmental justice and spur economic opportunity for disadvantaged communities that have been historically marginalized and overburdened by pollution and underinvestment in housing, transportation, water and wastewater infrastructure, and health care." Source: Executive Order on Tackling the Climate Crisis at Home and AbroadUse of this Data"The pilot identifies 21 priority programs to immediately begin enhancing benefits for disadvantaged communities. These priority programs will provide a blueprint for other agencies to help inform their work to implement the Justice40 Initiative across government." Source: The Path to Achieving Justice 40

  6. United States GDP: PCE: 1996p: DG: Others: Books & Maps

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). United States GDP: PCE: 1996p: DG: Others: Books & Maps [Dataset]. https://www.ceicdata.com/en/united-states/nipa-1999-personal-consumption-expenditure/gdp-pce-1996p-dg-others-books--maps
    Explore at:
    Dataset updated
    Feb 15, 2025
    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
    Nov 1, 2002 - Oct 1, 2003
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    United States GDP: PCE: 1996p: DG: Others: Books & Maps data was reported at 36.437 USD bn in Oct 2003. This records an increase from the previous number of 36.225 USD bn for Sep 2003. United States GDP: PCE: 1996p: DG: Others: Books & Maps data is updated monthly, averaging 14.997 USD bn from Jan 1967 (Median) to Oct 2003, with 442 observations. The data reached an all-time high of 38.497 USD bn in Jan 2002 and a record low of 8.736 USD bn in Feb 1977. United States GDP: PCE: 1996p: DG: Others: Books & Maps data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A203: NIPA 1999: Personal Consumption Expenditure.

  7. a

    Where is the US GDP Coming From?

    • hub.arcgis.com
    Updated Aug 24, 2017
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    ArcGIS Living Atlas Team (2017). Where is the US GDP Coming From? [Dataset]. https://hub.arcgis.com/maps/b2675a2de25048968059245d547e980d
    Explore at:
    Dataset updated
    Aug 24, 2017
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This web map shows annual Gross Domestic Product (GDP) by state and metro area in the USA for 2015. Clicking on the map reveals information about how the GDP has changed over time since 2001.The overlay of metro areas over states helps to put emphasis on where the country's GDP is coming from. The darkest green states produce the largest amount of GDP, and the largest circles show which major metropolitan areas contribute the most GDP within each state. Data is from the US Bureau of Economic Analysis and was downloaded from here. The state boundaries are generalized 2010 state boundaries from the Census Bureau's 2010 MAF/TIGER database. Note-- NAICS Industry detail is based on the 2007 North American Industry Classification System (NAICS).

  8. U

    United States GDP: PCE: DG: Others: Books & Maps

    • ceicdata.com
    + more versions
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    CEICdata.com, United States GDP: PCE: DG: Others: Books & Maps [Dataset]. https://www.ceicdata.com/en/united-states/nipa-1999-personal-consumption-expenditure/gdp-pce-dg-others-books--maps
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Nov 1, 2002 - Oct 1, 2003
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    United States GDP: PCE: DG: Others: Books & Maps data was reported at 38.362 USD bn in Oct 2003. This records an increase from the previous number of 38.219 USD bn for Sep 2003. United States GDP: PCE: DG: Others: Books & Maps data is updated monthly, averaging 7.195 USD bn from Jan 1959 (Median) to Oct 2003, with 538 observations. The data reached an all-time high of 40.328 USD bn in Jan 2002 and a record low of 1.055 USD bn in Feb 1959. United States GDP: PCE: DG: Others: Books & Maps data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A203: NIPA 1999: Personal Consumption Expenditure.

  9. US Approach Exclusive Economic Zone area

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Aug 31, 2018
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    noaa.gov (2018). US Approach Exclusive Economic Zone area [Dataset]. https://koordinates.com/layer/13978-us-approach-exclusive-economic-zone-area/
    Explore at:
    dwg, geopackage / sqlite, mapinfo mif, csv, shapefile, pdf, geodatabase, kml, mapinfo tabAvailable download formats
    Dataset updated
    Aug 31, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Description

    This layer is a component of Bands 4 and 5.

    The ENC_Approach map service displays data compiled for ENC products with a scale range of 1:50,001 and 1:150,000. The ENC data used within this application will be updated weekly. This map service is not intended for navigation purpose.

  10. Material stock map of CONUS - Rocky Mountains

    • zenodo.org
    • data.europa.eu
    zip
    Updated Dec 5, 2023
    + more versions
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    David Frantz; David Frantz; Franz Schug; Franz Schug; Dominik Wiedenhofer; Dominik Wiedenhofer; André Baumgart; André Baumgart; Doris Virág; Doris Virág; Sam Cooper; Sam Cooper; Camila Gomez-Medina; Camila Gomez-Medina; Fabian Lehmann; Fabian Lehmann; Thomas Udelhoven; Thomas Udelhoven; Sebastian van der Linden; Sebastian van der Linden; Patrick Hostert; Patrick Hostert; Helmut Haberl; Helmut Haberl (2023). Material stock map of CONUS - Rocky Mountains [Dataset]. http://doi.org/10.5281/zenodo.6873596
    Explore at:
    zipAvailable download formats
    Dataset updated
    Dec 5, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    David Frantz; David Frantz; Franz Schug; Franz Schug; Dominik Wiedenhofer; Dominik Wiedenhofer; André Baumgart; André Baumgart; Doris Virág; Doris Virág; Sam Cooper; Sam Cooper; Camila Gomez-Medina; Camila Gomez-Medina; Fabian Lehmann; Fabian Lehmann; Thomas Udelhoven; Thomas Udelhoven; Sebastian van der Linden; Sebastian van der Linden; Patrick Hostert; Patrick Hostert; Helmut Haberl; Helmut Haberl
    License

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

    Area covered
    Rocky Mountains
    Description

    Humanity's role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the 'anthropocene', as humans are 'overwhelming the great forces of nature'. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed 'manufactured capital', 'technomass', 'human-made mass', 'in-use stocks' or 'socioeconomic material stocks', they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with 'real' (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called 'built structures') represent the overwhelming majority of all socioeconomic material stocks.

    This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

    Spatial extent
    This subdataset covers the Rocky Mountains CONUS, i.e.

    • CO
    • ID
    • MT
    • UT
    • WY

    For the remaining CONUS, see the related identifiers.

    Temporal extent
    The map is representative for ca. 2018.

    Data format
    The data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

    Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).

    Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.

    • t at 10m x 10m
    • kt at 100m x 100m
    • Mt at 1km x 1km
    • Gt at 10km x 10km

    For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming.

    Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv.

    Material layers
    Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers):

    A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337.

    Further information
    For further information, please see the publication.
    A web-visualization of this dataset is available here.
    Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

    Publication
    D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gómez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, and H. Haberl (2023): Unveiling patterns in human dominated landscapes through mapping the mass of US built structures. Nature Communications 14, 8014. https://doi.org/10.1038/s41467-023-43755-5

    Funding
    This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404.

    Acknowledgments
    We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

  11. Unemployment Rate by County in the USA, 2000-2018

    • kaggle.com
    Updated Mar 27, 2019
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    Carlos Aguayo (2019). Unemployment Rate by County in the USA, 2000-2018 [Dataset]. https://www.kaggle.com/carlosaguayo/2018-unemployment-rate-by-county/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 27, 2019
    Dataset provided by
    Kaggle
    Authors
    Carlos Aguayo
    Area covered
    United States
    Description

    Content

    2018 unemployment rate in percent, per county in the USA.

    Acknowledgements

    This data was downloaded on March 23, 2019 from GeoFRED https://geofred.stlouisfed.org/map/?th=rdpu&cc=5&rc=false&im=fractile&sb&lng=-90.000&lat=40.028&zm=5&sl&sv&am=Average&at=Not%20Seasonally%20Adjusted,%20Monthly,%20Percent&sti=1224&fq=Annual&rt=county&un=lin&dt=2018-01-01

    How Can I Use the Data? In https://research.stlouisfed.org/fred_terms.html states that: "As long as you don’t engage in a prohibited/restricted use and do adhere to any applicable copyright restrictions, you are free to use FRED for your own non-commercial, educational, and personal uses."

  12. Material stock map of CONUS - South

    • zenodo.org
    zip
    Updated Dec 5, 2023
    + more versions
    Share
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    David Frantz; David Frantz; Franz Schug; Franz Schug; Dominik Wiedenhofer; Dominik Wiedenhofer; André Baumgart; André Baumgart; Doris Virág; Doris Virág; Sam Cooper; Sam Cooper; Camila Gomez-Medina; Camila Gomez-Medina; Fabian Lehmann; Fabian Lehmann; Thomas Udelhoven; Thomas Udelhoven; Sebastian van der Linden; Sebastian van der Linden; Patrick Hostert; Patrick Hostert; Helmut Haberl; Helmut Haberl (2023). Material stock map of CONUS - South [Dataset]. http://doi.org/10.5281/zenodo.6873598
    Explore at:
    zipAvailable download formats
    Dataset updated
    Dec 5, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    David Frantz; David Frantz; Franz Schug; Franz Schug; Dominik Wiedenhofer; Dominik Wiedenhofer; André Baumgart; André Baumgart; Doris Virág; Doris Virág; Sam Cooper; Sam Cooper; Camila Gomez-Medina; Camila Gomez-Medina; Fabian Lehmann; Fabian Lehmann; Thomas Udelhoven; Thomas Udelhoven; Sebastian van der Linden; Sebastian van der Linden; Patrick Hostert; Patrick Hostert; Helmut Haberl; Helmut Haberl
    License

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

    Description

    Humanity's role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the 'anthropocene', as humans are 'overwhelming the great forces of nature'. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed 'manufactured capital', 'technomass', 'human-made mass', 'in-use stocks' or 'socioeconomic material stocks', they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with 'real' (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called 'built structures') represent the overwhelming majority of all socioeconomic material stocks.

    This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

    Spatial extent
    This subdataset covers the South CONUS, i.e.

    • AL
    • AR
    • FL
    • GA
    • KY
    • LA
    • MS
    • NC
    • SC
    • TN
    • VA
    • WV

    For the remaining CONUS, see the related identifiers.

    Temporal extent
    The map is representative for ca. 2018.

    Data format
    The data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

    Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).

    Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.

    • t at 10m x 10m
    • kt at 100m x 100m
    • Mt at 1km x 1km
    • Gt at 10km x 10km

    For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming.

    Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv.

    Material layers
    Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers):

    A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337.

    Further information
    For further information, please see the publication.
    A web-visualization of this dataset is available here.
    Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

    Publication
    D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gómez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, and H. Haberl (2023): Unveiling patterns in human dominated landscapes through mapping the mass of US built structures. Nature Communications 14, 8014. https://doi.org/10.1038/s41467-023-43755-5

    Funding
    This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404.

    Acknowledgments
    We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

  13. Material stock map of CONUS - Great Plains

    • data.europa.eu
    • data.niaid.nih.gov
    • +1more
    unknown
    Updated Jul 20, 2023
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    Zenodo (2023). Material stock map of CONUS - Great Plains [Dataset]. https://data.europa.eu/data/datasets/oai-zenodo-org-8167633?locale=en
    Explore at:
    unknownAvailable download formats
    Dataset updated
    Jul 20, 2023
    Dataset authored and provided by
    Zenodohttp://zenodo.org/
    License

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

    Description

    Humanity’s role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the ‘anthropocene’, as humans are ‘overwhelming the great forces of nature’. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed ‘manufactured capital’, ‘technomass’, ‘human-made mass’, ‘in-use stocks’ or ‘socioeconomic material stocks’, they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with ‘real’ (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called ‘built structures’) represent the overwhelming majority of all socioeconomic material stocks. This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Spatial extent This subdataset covers the Great Plains CONUS, i.e. KS ND NE OK SD For the remaining CONUS, see the related identifiers. Temporal extent The map is representative for ca. 2018. Data format The data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided. Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types). Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e. t at 10m x 10m kt at 100m x 100m Mt at 1km x 1km Gt at 10km x 10km For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming. Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv. Material layers Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers): A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337. Further information For further information, please see the publication. A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gomez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, H. Haberl. Weighing the US Economy: Map of Built Structures Unveils Patterns in Human-Dominated Landscapes. In prep Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404. Acknowledgments We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

  14. U

    United States Exports: Maps & Hydrographic Charts etc, Atlases etc

    • ceicdata.com
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    CEICdata.com, United States Exports: Maps & Hydrographic Charts etc, Atlases etc [Dataset]. https://www.ceicdata.com/en/united-states/exports-by-commodity-4-digit-hs-code/exports-maps--hydrographic-charts-etc-atlases-etc
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    United States
    Description

    United States Exports: Maps & Hydrographic Charts etc, Atlases etc data was reported at 0.454 USD mn in Jan 2025. This records a decrease from the previous number of 0.498 USD mn for Dec 2024. United States Exports: Maps & Hydrographic Charts etc, Atlases etc data is updated monthly, averaging 1.053 USD mn from Jan 2002 (Median) to Jan 2025, with 277 observations. The data reached an all-time high of 4.156 USD mn in May 2023 and a record low of 0.268 USD mn in Apr 2022. United States Exports: Maps & Hydrographic Charts etc, Atlases etc data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.JA021: Exports: by Commodity: 4 Digit HS Code.

  15. Justice40 Tracts May 2022 (Archive)

    • resilience.climate.gov
    • gis-for-racialequity.hub.arcgis.com
    • +1more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). Justice40 Tracts May 2022 (Archive) [Dataset]. https://resilience.climate.gov/datasets/990e8d269a0348cba9ae28b344d2957d
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map uses an archive of Version 1.0 of the CEJST data as a fully functional GIS layer. See an archive of the latest version of the CEJST tool using Version 2.0 of the data released in December 2024 here.Note: A new version of this data was released November 22, 2022 and is available here. There are significant changes, see the Justice40 Initiative criteria for details.This layer assesses and identifies communities that are disadvantaged according to Justice40 Initiative criteria. Census tracts in the U.S. and its territories that meet the Version 0.1 criteria are shaded in a semi-transparent blue to work with a variety of basemaps.Details of the assessment are provided in the popup for every census tract in the United States and its territories American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. This map uses 2010 census tracts from Version 0.1 of the source data downloaded May 30, 2022.Use this layer to help plan for grant applications, to perform spatial analysis, and to create informative dashboards and web applications. See this blog post for more information.From the source:"Census tract geographical boundaries are determined by the U.S. Census Bureau once every ten years. This tool utilizes the census tract boundaries from 2010 because they match the datasets used in the tool. The U.S. Census Bureau will update these tract boundaries in 2020.Under the current formula, a census tract will be identified as disadvantaged in one or more categories of criteria:IF the tract is above the threshold for one or more environmental or climate indicators AND the tract is above the threshold for the socioeconomic indicatorsCommunities are identified as disadvantaged by the current version of the tool for the purposes of the Justice40 Initiative if they are located in census tracts that are at or above the combined thresholds in one or more of eight categories of criteria.The goal of the Justice40 Initiative is to provide 40 percent of the overall benefits of certain Federal investments in [eight] key areas to disadvantaged communities. These [eight] key areas are: climate change, clean energy and energy efficiency, clean transit, affordable and sustainable housing, training and workforce development, the remediation and reduction of legacy pollution, [health burdens] and the development of critical clean water infrastructure." Source: Climate and Economic Justice Screening toolPurpose"Sec. 219. Policy. To secure an equitable economic future, the United States must ensure that environmental and economic justice are key considerations in how we govern. That means investing and building a clean energy economy that creates well‑paying union jobs, turning disadvantaged communities — historically marginalized and overburdened — into healthy, thriving communities, and undertaking robust actions to mitigate climate change while preparing for the impacts of climate change across rural, urban, and Tribal areas. Agencies shall make achieving environmental justice part of their missions by developing programs, policies, and activities to address the disproportionately high and adverse human health, environmental, climate-related and other cumulative impacts on disadvantaged communities, as well as the accompanying economic challenges of such impacts. It is therefore the policy of my Administration to secure environmental justice and spur economic opportunity for disadvantaged communities that have been historically marginalized and overburdened by pollution and underinvestment in housing, transportation, water and wastewater infrastructure, and health care." Source: Executive Order on Tackling the Climate Crisis at Home and AbroadUse of this Data"The pilot identifies 21 priority programs to immediately begin enhancing benefits for disadvantaged communities. These priority programs will provide a blueprint for other agencies to help inform their work to implement the Justice40 Initiative across government." Source: The Path to Achieving Justice 40The layer has some transparency applied to allow it to work sufficiently well on top of many basemaps. For optimum map display where streets and labels are clearly shown on top of this layer, try one of the Human Geography basemaps and set transparency to 0%, as is done in this example web map.Browse the DataView the Data tab in the top right of this page to browse the data in a table and view the metadata available for each field, including field name, field alias, and a field description explaining what the field represents.

  16. A

    The Ocean Economies of Puerto Rico and the U.S. Virgin Islands

    • data.amerigeoss.org
    • caribbeangeoportal.com
    esri rest, html
    Updated May 12, 2017
    + more versions
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    NOAA GeoPlatform (2017). The Ocean Economies of Puerto Rico and the U.S. Virgin Islands [Dataset]. https://data.amerigeoss.org/fi/dataset/the-ocean-economies-of-puerto-rico-and-the-u-s-virginislands
    Explore at:
    esri rest, htmlAvailable download formats
    Dataset updated
    May 12, 2017
    Dataset provided by
    NOAA GeoPlatform
    License

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

    Area covered
    U.S. Virgin Islands, Puerto Rico
    Description

    This story map illustrates the different ocean economies of Puerto Rico and the U.S. Virgin Islands. The story map highlights NOAA's Economics: National Ocean Watch (ENOW) dataset. This story map addresses the caveats and limiting factors faced when collecting economic information in the Caribbean territories. For more information, please see the ENOW website.

  17. United States PCE: sa: DG: Others: Books and Maps

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). United States PCE: sa: DG: Others: Books and Maps [Dataset]. https://www.ceicdata.com/en/united-states/nipa-2003-personal-consumption-expenditure/pce-sa-dg-others-books-and-maps
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    Dataset updated
    Feb 15, 2025
    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
    Jun 1, 2008 - May 1, 2009
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    United States PCE: sa: DG: Others: Books and Maps data was reported at 47.148 USD bn in May 2009. This records a decrease from the previous number of 47.560 USD bn for Apr 2009. United States PCE: sa: DG: Others: Books and Maps data is updated monthly, averaging 9.739 USD bn from Jan 1959 (Median) to May 2009, with 605 observations. The data reached an all-time high of 48.547 USD bn in Aug 2008 and a record low of 1.055 USD bn in Feb 1959. United States PCE: sa: DG: Others: Books and Maps data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A183: NIPA 2003: Personal Consumption Expenditure.

  18. Justice40 Tracts November 2022 Version 1.0 (Archive)

    • resilience.climate.gov
    • mpo-portal-lacrossecounty.hub.arcgis.com
    Updated Nov 22, 2022
    + more versions
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    Esri (2022). Justice40 Tracts November 2022 Version 1.0 (Archive) [Dataset]. https://resilience.climate.gov/datasets/f95344889cab44bd84207052f44cb940
    Explore at:
    Dataset updated
    Nov 22, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer is an archive of Version 1.0 of the CEJST data as a fully functional GIS layer. See an archive of the latest version of the CEJST tool using Version 2.0 of the data released in December 2024 here.This layer assesses and identifies communities that are disadvantaged according to updated Justice40 Initiative criteria. Census tracts in the U.S. and its territories that meet the Version 1.0 criteria are shaded in semi-transparent blue colors to work with a variety of basemaps. See this web map for use in your dashboards, story maps, and apps.Details of the assessment are provided in the popup for every census tract in the United States and its territories American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. This map uses 2010 census tracts from Version 1.0 of the source data downloaded November 22, 2022.If you have been using a previous version of the Justice40 data, please know that this Version 1.0 differs in many ways. See the updated Justice40 Initiative criteria for current specifics. Use this layer to help plan for grant applications, to perform spatial analysis, and to create informative dashboards and web applications. See this blog post for more information.From the source:This data "highlights disadvantaged census tracts across all 50 states, the District of Columbia, and the U.S. territories. Communities are considered disadvantaged:If they are in census tracts that meet the thresholds for at least one of the tool’s categories of burden, orIf they are on land within the boundaries of Federally Recognized TribesCategories of BurdensThe tool uses datasets as indicators of burdens. The burdens are organized into categories. A community is highlighted as disadvantaged on the CEJST map if it is in a census tract that is (1) at or above the threshold for one or more environmental, climate, or other burdens, and (2) at or above the threshold for an associated socioeconomic burden.In addition, a census tract that is completely surrounded by disadvantaged communities and is at or above the 50% percentile for low income is also considered disadvantaged.Census tracts are small units of geography. Census tract boundaries for statistical areas are determined by the U.S. Census Bureau once every ten years. The tool utilizes the census tract boundaries from 2010. This was chosen because many of the data sources in the tool currently use the 2010 census boundaries."PurposeThe goal of the Justice40 Initiative is to provide 40 percent of the overall benefits of certain Federal investments in [eight] key areas to disadvantaged communities. These [eight] key areas are: climate change, clean energy and energy efficiency, clean transit, affordable and sustainable housing, training and workforce development, the remediation and reduction of legacy pollution, [health burdens] and the development of critical clean water infrastructure." Source: Climate and Economic Justice Screening tool"Sec. 219. Policy. To secure an equitable economic future, the United States must ensure that environmental and economic justice are key considerations in how we govern. That means investing and building a clean energy economy that creates well‑paying union jobs, turning disadvantaged communities — historically marginalized and overburdened — into healthy, thriving communities, and undertaking robust actions to mitigate climate change while preparing for the impacts of climate change across rural, urban, and Tribal areas. Agencies shall make achieving environmental justice part of their missions by developing programs, policies, and activities to address the disproportionately high and adverse human health, environmental, climate-related and other cumulative impacts on disadvantaged communities, as well as the accompanying economic challenges of such impacts. It is therefore the policy of my Administration to secure environmental justice and spur economic opportunity for disadvantaged communities that have been historically marginalized and overburdened by pollution and underinvestment in housing, transportation, water and wastewater infrastructure, and health care." Source: Executive Order on Tackling the Climate Crisis at Home and AbroadUse of this Data"The pilot identifies 21 priority programs to immediately begin enhancing benefits for disadvantaged communities. These priority programs will provide a blueprint for other agencies to help inform their work to implement the Justice40 Initiative across government." Source: The Path to Achieving Justice 40The layer has some transparency applied to allow it to work sufficiently well on top of many basemaps. For optimum map display where streets and labels are clearly shown on top of this layer, try one of the Human Geography basemaps and set transparency to 0%, as is done in this example web map.Browse the DataView the Data tab in the top right of this page to browse the data in a table and view the metadata available for each field, including field name, field alias, and a field description explaining what the field represents.Symbology updated 2/19/2023 to show additional tracts whose overlap with tribal lands is greater than 0% but less than 1%, to be designated as "Partially Disadvantaged" alongside tracts whose overlap with tribal lands is 1% or more.

  19. T

    United States Inflation Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 12, 2025
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    TRADING ECONOMICS (2025). United States Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/inflation-cpi
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Aug 12, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1914 - Jul 31, 2025
    Area covered
    United States
    Description

    Inflation Rate in the United States remained unchanged at 2.70 percent in July. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  20. d

    CGS Map Sheet 48: National Loss from Earthquake Damage, Conterminous United...

    • catalog.data.gov
    • gis.data.cnra.ca.gov
    • +5more
    Updated Jul 24, 2025
    + more versions
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    California Department of Conservation (2025). CGS Map Sheet 48: National Loss from Earthquake Damage, Conterminous United States (2014 Estimate) [Dataset]. https://catalog.data.gov/dataset/cgs-map-sheet-48-national-loss-from-earthquake-damage-conterminous-united-states-2014-esti-79157
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    California Department of Conservation
    Area covered
    Contiguous United States, United States
    Description

    "Annualized Earthquake Losses (AEL) are economic losses from earthquake shaking-related building damage. These data use the most recent National Seismic Hazard Maps (the years 2008 and 2014 cycles), updated census data on population, and economic exposure estimates of general building stock to quantify annualized earthquake loss (AEL) for the conterminous United States. The AEL analyses were performed using the Federal Emergency Management Agency's (FEMA) Hazus software, which facilitated a systematic comparison of the influence of the 2014 National Seismic Hazard Maps in terms of annualized loss estimates in different parts of the country. These data do not include losses from ground-failure effects such as landslide, liquefaction, surface fault rupture, or losses due to other secondary effects such as fires following earthquakes. Building economic losses are direct economic losses including structural damage, non-structural damage, and content damage; as well as building damage-related economic losses, such as inventory loss, relocation cost, loss of proprietors’ income, and rental income loss. These do not include losses associated with business interruption. Replacement costs and loss valuations are based on 2014 dollars."

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US National Oceanic and Atmospheric Administration (NOAA) (2018). US GDP Marine Construction [Dataset]. https://koordinates.com/layer/20927-us-gdp-marine-construction/
Organization logo

US GDP Marine Construction

Explore at:
mapinfo tab, mapinfo mif, geopackage / sqlite, geodatabase, csv, kml, dwg, pdf, shapefileAvailable download formats
Dataset updated
Aug 30, 2018
Dataset provided by
National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
Authors
US National Oceanic and Atmospheric Administration (NOAA)
Area covered
Description

This layer is a component of ENOW_Counties.

This map service presents spatial information about the Economics: National Ocean Watch (ENOW) data in the Web Mercator projection. The ENOW data provides time-series data on the ocean and Great Lakes economy, which includes six economic sectors dependent on the oceans and Great Lakes, and measures four economic indicators: Establishments, Employment, Wages, and Gross Domestic Product (GDP). The annual time-series data are available for about 400 coastal counties, 30 coastal states, 8 regions, and the nation. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

© NOAA Office for Coastal Management

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