94 datasets found
  1. US Ocean Employment Ship Build

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Aug 30, 2018
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    US National Oceanic and Atmospheric Administration (NOAA) (2018). US Ocean Employment Ship Build [Dataset]. https://koordinates.com/layer/20916-us-ocean-employment-ship-build/
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    geopackage / sqlite, csv, dwg, geodatabase, mapinfo mif, shapefile, pdf, mapinfo tab, kmlAvailable 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. Redevelopment Economics at Superfund Sites Web Map

    • hub.arcgis.com
    Updated Feb 9, 2021
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    U.S. EPA (2021). Redevelopment Economics at Superfund Sites Web Map [Dataset]. https://hub.arcgis.com/maps/ce6e1daf40f84950b592107f660ecd58
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    Dataset updated
    Feb 9, 2021
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Authors
    U.S. EPA
    Area covered
    Description

    This web map presents 2024 economic data for redevelopment at Superfund sites at a national level. EPA's Superfund Redevelopment Program, (SRP) tracks this information over time to give a general overview of the national beneficial effects associated with Superfund redevelopment. To date, SRP has tracked these benefits from 2011 through 2024. This web map was built to be used in the Redevelopment Economics at Superfund Sites dashboard for the Redevelopment Economics at Superfund Sites StoryMap. Contact bqboggs@skeo.com with any questions.

  3. 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
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    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).

  4. 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/
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    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.

  5. a

    Economic Conditions

    • hub.arcgis.com
    Updated Jun 27, 2017
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    Florida Department of Agriculture and Consumer Services (2017). Economic Conditions [Dataset]. https://hub.arcgis.com/maps/4e71093872fd465ab2a4f203f7e3aa29
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    Dataset updated
    Jun 27, 2017
    Dataset authored and provided by
    Florida Department of Agriculture and Consumer Services
    Area covered
    Description

    The data displayed in this theme of the Florida’s Roadmap to Living Healthy are quantitative measures that present the economic condition of Florida’s communities. The data sets contained in this themed map provide the business community and policymakers with relevant and useful statistics needed to make informed decisions to positively affect Florida’s economy. The Florida Department of Agriculture and Consumer Services has used the most current economic statistics from trusted sources such as the United States Census Bureau, U.S. Department of Labor Bureau of Labor Statistics, Consumer Financial Protection Bureau, U.S. Department of the Treasury Community Development Financial Institutions Fund, Social Security Administration, Florida Department of Children and Families, CareerSource Florida, and Esri to build this custom visualization. The economic data used for this themed map includes topics, such as unemployment rates, rural and underserved communities, New Market Tax Credits (NMTC), poverty indicators, career centers, and other related topics. The economic data shown in this themed map is useful for data-driven planning and decision making at the local and state level that could influence growth in various economic sectors.For technical assistance, contact Ronnie Blanco at ronaldo.blanco@freshfromflorida.com

  6. 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.

  7. Wind Techno-economic Exclusion

    • catalog.data.gov
    • s.cnmilf.com
    • +5more
    Updated Nov 27, 2024
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    California Energy Commission (2024). Wind Techno-economic Exclusion [Dataset]. https://catalog.data.gov/dataset/wind-techno-economic-exclusion-29d91
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Energy Commissionhttp://www.energy.ca.gov/
    Description

    The site suitability criteria included in the techno-economic land use screens are listed below. As this list is an update to previous cycles, tribal lands, prime farmland, and flood zones are not included as they are not technically infeasible for development. The techno-economic site suitability exclusion thresholds are presented in table 1. Distances indicate the minimum distance from each feature for commercial scale wind developmentAttributes: Steeply sloped areas: change in vertical elevation compared to horizontal distancePopulation density: the number of people living in a 1 km2 area Urban areas: defined by the U.S. Census. Water bodies: defined by the U.S. National Atlas Water Feature Areas, available from Argonne National Lab Energy Zone Mapping Tool Railways: a comprehensive database of North America's railway system from the Federal Railroad Administration (FRA), available from Argonne National Lab Energy Zone Mapping Tool Major highways: available from ESRI Living Atlas Airports: The Airports dataset including other aviation facilities as of July 13, 2018 is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). The Airports database is a geographic point database of aircraft landing facilities in the United States and U.S. Territories. Attribute data is provided on the physical and operational characteristics of the landing facility, current usage including enplanements and aircraft operations, congestion levels and usage categories. This geospatial data is derived from the FAA's National Airspace System Resource Aeronautical Data Product. Available from Argonne National Lab Energy Zone Mapping Tool Active mines: Active Mines and Mineral Processing Plants in the United States in 2003Military Lands: Land owned by the federal government that is part of a US military base, camp, post, station, yard, center, or installation. Table 1 Wind Steeply sloped areas >10o Population density >100/km2 Capacity factor <20% Urban areas <1000 m Water bodies <250 m Railways <250 m Major highways <125 m Airports <5000 m Active mines <1000 m Military Lands <3000m For more information about the processes and sources used to develop the screening criteria see sources 1-7 in the footnotes. Data updates occur as needed, corresponding to typical 3-year CPUC IRP planning cyclesFootnotes:[1] Lopez, A. et. al. “U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis,” 2012. https://www.nrel.gov/docs/fy12osti/51946.pdf[2] https://greeningthegrid.org/Renewable-Energy-Zones-Toolkit/topics/social-environmental-and-other-impacts#ReadingListAndCaseStudies[3] Multi-Criteria Analysis for Renewable Energy (MapRE), University of California Santa Barbara. https://mapre.es.ucsb.edu/[4] Larson, E. et. al. “Net-Zero America: Potential Pathways, Infrastructure, and Impacts, Interim Report.” Princeton University, 2020. https://environmenthalfcentury.princeton.edu/sites/g/files/toruqf331/files/2020-12/Princeton_NZA_Interim_Report_15_Dec_2020_FINAL.pdf.[5] Wu, G. et. al. “Low-Impact Land Use Pathways to Deep Decarbonization of Electricity.” Environmental Research Letters 15, no. 7 (July 10, 2020). https://doi.org/10.1088/1748-9326/ab87d1.[6] RETI Coordinating Committee, RETI Stakeholder Steering Committee. “Renewable Energy Transmission Initiative Phase 1B Final Report.” California Energy Commission, January 2009.[7] Pletka, Ryan, and Joshua Finn. “Western Renewable Energy Zones, Phase 1: QRA Identification Technical Report.” Black & Veatch and National Renewable Energy Laboratory, 2009. https://www.nrel.gov/docs/fy10osti/46877.pdf.[8]https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Urban+Areas[9]https://ezmt.anl.gov/[10]https://www.arcgis.com/home/item.html?id=fc870766a3994111bce4a083413988e4[11]https://mrdata.usgs.gov/mineplant/Credits Title: Techno-economic screening criteria for utility-scale wind energy installations for Integrated Resource Planning Purpose for creation: These site suitability criteria are for use in electric system planning, capacity expansion modeling, and integrated resource planning. Keywords: wind energy, resource potential, techno-economic, IRP Extent: western states of the contiguous U.S. Use Limitations The geospatial data created by the use of these techno-economic screens inform high-level estimates of technical renewable resource potential for electric system planning and should not be used, on their own, to guide siting of generation projects nor assess project-level impacts.Confidentiality: Public ContactEmily Leslie Emily@MontaraMtEnergy.comSam Schreiber sam.schreiber@ethree.com Jared Ferguson Jared.Ferguson@cpuc.ca.govOluwafemi Sawyerr femi@ethree.com

  8. Justice40 Tracts May 2022 (Archive)

    • resilience.climate.gov
    • gis-for-racialequity.hub.arcgis.com
    • +1more
    Updated Aug 16, 2022
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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.

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

    • data.cnra.ca.gov
    • data.ca.gov
    • +6more
    Updated May 24, 2017
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    California Department of Conservation (2017). CGS Map Sheet 48: National Loss from Earthquake Damage, Conterminous United States (2014 Estimate) [Dataset]. https://data.cnra.ca.gov/dataset/cgs-map-sheet-48-national-loss-from-earthquake-damage-conterminous-united-states-2014-estimate
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    geojson, zip, arcgis geoservices rest api, csv, html, kmlAvailable download formats
    Dataset updated
    May 24, 2017
    Dataset authored and provided by
    California Department of Conservationhttp://www.conservation.ca.gov/
    License

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

    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."
  10. Low-Income Community Bonus Credit Program

    • zenodo.org
    bin, gif, html, txt +1
    Updated Mar 21, 2025
    + more versions
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    Zenodo (2025). Low-Income Community Bonus Credit Program [Dataset]. http://doi.org/10.5281/zenodo.15061838
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    zip, bin, gif, txt, htmlAvailable download formats
    Dataset updated
    Mar 21, 2025
    Dataset 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

    IRA Low-Income Community Bonus Credit Program Layers

    These geospatial data resources and the linked mapping tool below reflect currently available data on three categories of potentially qualifying Low-Income communities:

    1. Census tracts that meet the CDFI's New Market Tax Credit Program's threshold for Low Income, thereby are able to apply to Category 1.
    2. Census tracts that meet the White House's Climate and Economic Justice Screening Tool's threshold for disadvantage in the 'Energy' category, thereby are able to apply for Additional Selection Criteria Geography.
    3. Counties that meet the USDA's threshold for Persistent Poverty, thereby are able to apply for Additional Selection Criteria Geography.

    Note that Category 2 - Indian Lands are not shown on this map. Note that Persistent Poverty is not calculated for US Territories. Note that CEJST Energy disadvantage is not calculated for US Territories besides Puerto Rico.

    The excel tool provides the land area percentage of each 2023 census tract meeting each of the above categories. To examine geographic eligibility for a specific address or latitude and longitude, visit the program's mapping tool.

    Additional information on this tax credit program can be found on the DOE Landing Page for the 48e program at https://www.energy.gov/diversity/low-income-communities-bonus-credit-program or the IRS Landing Page at https://www.irs.gov/credits-deductions/low-income-communities-bonus-credit.

    Maps last updated: September 1st, 2024
    Next map update expected: December 7th, 2024

    Disclaimer: The spatial data and mapping tool is intended for geolocation purposes. It should not be relied upon by taxpayers to determine eligibility for the Low-Income Communities Bonus Credit Program.

    Source Acknowledgements:

    1. The New Market Tax Credit (NMTC) Tract layer using data from the 2016-2020 ACS is from the CDFI Information Mapping System (CIMS) and is created by the U.S. Department of Treasury Community Development Financial Institutions Fund. To learn more, visit CDFI Information Mapping System (CIMS) | Community Development Financial Institutions Fund (cdfifund.gov). https://www.cdfifund.gov/mapping-system. Tracts are displayed that meet the threshold for the New Market Tax Credit Program.
    2. The 'Energy' Category Tract layer from the Climate and Economic Justice Screening Tool (CEJST) is created by the Council on Environmental Quality (CEQ) within the Executive Office of the President. To learn more, visit https://screeningtool.geoplatform.gov/en/. Tracts are displayed that meet the threshold for the 'Energy' Category of burden. I.e., census tracts that are at or above the 90th percentile for (energy burden OR PM2.5 in the air) AND are at or above the 65th percentile for low income.
    3. The Persistent Poverty County layer is created by joining the U.S. Department of Agriculture, Economic Research Service's Poverty Area Official Measures dataset, with relevant county TIGER/Line Shapefiles from the US Census Bureau. To learn more, visit https://www.ers.usda.gov/data-products/poverty-area-measures/. Counties are displayed that meet the thresholds for Persistent Poverty according to 'Official' USDA updates. i.e. areas with a poverty rate of 20.0 percent or more for 4 consecutive time periods, about 10 years apart, spanning approximately 30 years (baseline time period plus 3 evaluation time periods). Until Dec 7th, 2024 both the USDA estimates using 2007-2011 and 2017-2021 ACS 5-year data. On Dec 8th, 2024, only the USDA estimates using 2017-2021 data will be accepted for program eligibility.

  11. Material stock map of CONUS - South West

    • zenodo.org
    • data.niaid.nih.gov
    zip
    Updated Jul 25, 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 - South West [Dataset]. http://doi.org/10.5281/zenodo.8176659
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    zipAvailable download formats
    Dataset updated
    Jul 25, 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 West CONUS, i.e.

    • AZ
    • NM
    • NV
    • TX

    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.

  12. Material stock map of CONUS - Great Plains

    • zenodo.org
    • data.niaid.nih.gov
    zip
    Updated Jul 20, 2023
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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 - Great Plains [Dataset]. http://doi.org/10.5281/zenodo.8167633
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jul 20, 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 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.

  13. Justice40 Tracts November 2022 Version 1.0 (Archive)

    • resilience.climate.gov
    Updated Nov 22, 2022
    + more versions
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    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.

  14. a

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

    • regionaldatahub-brag.hub.arcgis.com
    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://regionaldatahub-brag.hub.arcgis.com/items/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

  15. Justice40 Tracts Map April 2022 (Archive)

    • gis-for-racialequity.hub.arcgis.com
    Updated Apr 25, 2022
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    Justice40 Tracts Map April 2022 (Archive) [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/0687efe42c7c44eb803c23a47ed374fa
    Explore at:
    Dataset updated
    Apr 25, 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 map was released November 22, 2022 and is available here. There are significant changes, see the Justice40 Initiative criteria for details.This map assesses and identifies communities that are disadvantaged according to Justice40 Initiative criteria. Census tracts in the U.S. and its territories that meet the criteria are shaded in dark blue. Suitable for dashboards, apps, stories, and grant applications.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 April 15, 2022.Use the accompanying 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 40Browse the DataView the Data tab in the top right of the layer's item 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. 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."

  17. 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.

  18. County Business Patterns (CBP) from Economic Census 2017

    • hub.arcgis.com
    Updated Apr 1, 2020
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    Esri (2020). County Business Patterns (CBP) from Economic Census 2017 [Dataset]. https://hub.arcgis.com/maps/1f90850b9fd84b219917a8b278ea626c
    Explore at:
    Dataset updated
    Apr 1, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer contains data on the number of establishments, total employment, and total annual payroll for for 20 selected 4- and 5-digit North American Industry Classification System (NAICS) codes. This is shown by county and state boundaries. The full CBP data set (available at census.gov) is updated annually to contain the most currently released CBP data. This layer is symbolized to show the total number of establishments depicted by size, and the average annual pay per employee, depicted by color.

    Current Vintage: 2017

    CBP Table: CB1700CBP

    Data downloaded from: Census Bureau's API for County Business Patterns

    Date of API call: June 1, 2019

    The United States Census Bureau's County Business Patterns Program (CBP):

    About this Program Data Technical Documentation News & Updates

    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. Please cite the Census Bureau and CBP when using this data.

    Data Processing Notes: Boundaries come from the US Census Bureau TIGER geodatabases. 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 Bureau. These are Census Bureau boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 56 records - all US states, Washington D.C., Puerto Rico, and U.S. Island Areas Blank values represent industries where there either were no businesses in that industry and that geography OR industries where the data had to be withheld to avoid disclosing data for individual companies. Users should visit data.census.gov or Census Business Builder for more details on these withheld records.

  19. Digital Map Market Analysis, Size, and Forecast 2025-2029: North America (US...

    • technavio.com
    Updated Jun 18, 2025
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    Technavio (2025). Digital Map Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, and UK), APAC (China, India, Indonesia, Japan, and South Korea), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/digital-map-market-industry-analysis
    Explore at:
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Canada, United States, Global
    Description

    Snapshot img

    Digital Map Market Size 2025-2029

    The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.

    The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
    Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.
    

    What will be the Size of the Digital Map Market during the forecast period?

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free Sample

    In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.

    Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.

    How is this Digital Map Industry segmented?

    The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Application
    
      Navigation
      Geocoders
      Others
    
    
    Type
    
      Outdoor
      Indoor
    
    
    Solution
    
      Software
      Services
    
    
    Deployment
    
      On-premises
      Cloud
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        China
        India
        Indonesia
        Japan
        South Korea
    
    
      Rest of World (ROW)
    

    By Application Insights

    The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.

    Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance app

  20. 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
    Puerto Rico, U.S. Virgin Islands
    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.

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US National Oceanic and Atmospheric Administration (NOAA) (2018). US Ocean Employment Ship Build [Dataset]. https://koordinates.com/layer/20916-us-ocean-employment-ship-build/
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US Ocean Employment Ship Build

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geopackage / sqlite, csv, dwg, geodatabase, mapinfo mif, shapefile, pdf, mapinfo tab, kmlAvailable 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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