57 datasets found
  1. Sector Map - Manufacturing

    • noaa.hub.arcgis.com
    Updated Jun 9, 2021
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    NOAA GeoPlatform (2021). Sector Map - Manufacturing [Dataset]. https://noaa.hub.arcgis.com/maps/5cef2e53a2c44811930b5306b2ab6b9e
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    Dataset updated
    Jun 9, 2021
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    License

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

    Area covered
    Description

    This map displays drought, climate and manufacturing-related agriculture data for the United States. The map was created by the National Integrated Drought Information System (NIDIS) and is a component of the Manufacturing Sector web mapping application, a tool for exploring the relationship between drought, climate and the manufacturing sector in the United States.Data Sources for each layer are identified in the Layer section below as well as in the Layer and Legend sections of the web map. Additional information about the impact of drought on manufacturing can be found on the NIDIS Manufacturing Sector page.

  2. EnviroAtlas - Industrial Water Demand (2010) by 12-Digit HUC for the...

    • catalog.data.gov
    • datadiscoverystudio.org
    • +2more
    Updated Apr 22, 2025
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    U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas (Point of Contact) (2025). EnviroAtlas - Industrial Water Demand (2010) by 12-Digit HUC for the Conterminous United States [Dataset]. https://catalog.data.gov/dataset/enviroatlas-industrial-water-demand-2010-by-12-digit-huc-for-the-conterminous-united-states4
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    Dataset updated
    Apr 22, 2025
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Area covered
    Contiguous United States, United States
    Description

    This EnviroAtlas dataset includes industrial water demand attributes which provide insight into the amount of water currently used for manufacturing and production of commodities in the contiguous United States. The values are based on 2010 water demand and Dun and Bradstreet's 2009/2010 source data, and have been summarized by watershed or 12-digit hydrologic unit code (HUC). For the purposes of this metric, industrial water use includes chemical, food, paper, wood, and metal production. The industrial water is for self-supplied only such as by private wells or reservoirs. Sources include either surface water or groundwater. This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  3. Dataset of 'Mapping 10-m Industrial Lands across 1000+ Global Large Cities,...

    • zenodo.org
    bin, zip
    Updated Feb 18, 2025
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    Cheolhee Yoo; Cheolhee Yoo; Yuhan Zhou; Yuhan Zhou; Qihao Weng; Qihao Weng (2025). Dataset of 'Mapping 10-m Industrial Lands across 1000+ Global Large Cities, 2017-2023' [Dataset]. http://doi.org/10.5281/zenodo.14832219
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    zip, binAvailable download formats
    Dataset updated
    Feb 18, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Cheolhee Yoo; Cheolhee Yoo; Yuhan Zhou; Yuhan Zhou; Qihao Weng; Qihao Weng
    License

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

    Description

    This dataset provides high-resolution (10 m) industrial land maps for 1,093 global cities from 2017 to 2023.

    The dataset includes:

    • 10 m resolution industrial land maps for each year (GeoTIFF, Zip)
    • Detailed information for each city, including industrial land area per capita indicators (1093_city_information.xlsx)
    • Validation Package (Validation_Package.zip)

    File Naming Convention

    • GeoTIFF files: Industrial_land_XXX_YYY_YEAR.tif
      • XXX: Country code
      • YYY: City ID
      • YEAR: Year of data
      • Example: Industrial_land_USA_634_2017.tif represents the industrial land map for Chicago, USA, in 2017.

    Each TIF file has a 10 m spatial resolution with the GCS_WGS_1984 spatial projection. The maps include three classes:

    • Class 1: Industrial land in built-up areas
    • Class 2: Non-industrial land in built-up areas
    • Class 0: Non-built-up areas

    City Information

    A detailed summary of city-specific information, including the annual total industrial land area, is provided in 1093_city_information.xlsx. This file includes:

    • ID_HDC_G0: Unique city ID (Urban Centre)
    • CTR_MN_NM: Main country name
    • CTR_MN_ISO: ISO-3 country codes
    • UC_NM_MN: Main city (Urban Centre) name
    • UC_NM_LST: Full list of assigned city (Urban Centre) names
    • CLUSTER: Assigned cluster number in industrial land modeling
    • URB_ECOREGION: Assigned urban ecoregion
    • CLUSTER: Assigned cluster number in industrial land modeling
    • IND_YEAR: Total industrial land area for each year (in m²).

    Validation Package

    • This package includes validation samples used for industrial land mapping validation.
    • Validation_shapefile/: Contains the validation shapefiles used for assessing the accuracy of industrial land maps.
    • Validation of Industrial Land Map Using CO₂ Emissions Data.xlsx: Includes validation results comparing industrial land maps with CO₂ emissions data.
    • Association between Proposed Industrial Land and the Official Data.xlsx: Contains data assessing the relationship between the proposed industrial land and official datasets.
  4. 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).

  5. a

    Miscellaneous Industrial Mineral Operations

    • disasters-geoplatform.hub.arcgis.com
    • azgeo-data-hub-agic.hub.arcgis.com
    • +5more
    Updated Dec 1, 2005
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    GeoPlatform ArcGIS Online (2005). Miscellaneous Industrial Mineral Operations [Dataset]. https://disasters-geoplatform.hub.arcgis.com/datasets/miscellaneous-industrial-mineral-operations
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    Dataset updated
    Dec 1, 2005
    Dataset authored and provided by
    GeoPlatform ArcGIS Online
    Area covered
    Description

    This data set includes miscellaneous industrial minerals operations in the United States. The data represent commodities covered by the Minerals Information Team (MIT) of the U.S. Geological Survey. The mineral operations are plants and (or) mines surveyed by the MIT and considered currently active in 2003. This is a replacement for the July 2004 map layer.The data is legacy and not expected to be updated. It is being provided as the best available until Mineral Resources identifies an alternative data source.

  6. Digital Map Market Analysis APAC, North America, Europe, South America,...

    • technavio.com
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    Technavio, Digital Map Market Analysis APAC, North America, Europe, South America, Middle East and Africa - US, China, Germany, Japan, India - Size and Forecast 2024-2028 [Dataset]. https://www.technavio.com/report/digital-map-market-industry-analysis
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    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global, United States
    Description

    Snapshot img

    Digital Map Market Size 2024-2028

    The digital map market size is forecast to increase by USD 19.75 billion at a CAGR of 26.06% between 2023 and 2028.

    What will be the Size of the Digital Map Market During the Forecast Period?

    Request Free Sample

    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. The proliferation of connected devices, including PDAs, Cortana, Siri, Amazon Echo, and Google Now, has increased the demand for digital maps in real-time mapping applications and map analytics. Real-time tracking systems are gaining popularity in sectors such as energy & power, automobile, telecommunication, and transportation, providing valuable spatial data on terrain, roads, buildings, rivers, and other features. APIs enable seamless integration of digital maps into various applications, enhancing user experience and ROI.
    The internet has made digital maps accessible from anywhere, further fueling market growth. Overall, the market is poised for significant expansion, offering numerous opportunities for businesses and innovators alike.
    

    How is this Digital Map Industry segmented and which is the largest segment?

    The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

    Application
    
      Navigation
      Geocoders
      Others
    
    
    Type
    
      Outdoor
      Indoor
    
    
    Geography
    
      APAC
    
        China
        India
        Japan
    
    
      North America
    
        US
    
    
      Europe
    
        Germany
    
    
      South America
    
    
    
      Middle East and Africa
    

    By Application Insights

    The navigation segment is estimated to witness significant growth during the forecast period.
    

    Digital maps play a crucial role in various industries, particularly in automotive applications for driver assistance systems. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. The increasing use of connected cars and the development of Long-Term Evolution (LTE) technologies are driving the demand for digital maps. These maps provide real-time traffic information, helping drivers navigate urban areas with high population density and traffic congestion more efficiently. Additionally, digital maps are essential for transportation route planning, public services, agriculture, and conservation efforts. In agriculture, digital maps help determine soil types, nutrient levels, and crop yields.

    Waste reduction and the protection of sensitive ecosystems and habitats are also facilitated by digital maps. Overall, digital maps offer valuable insights for urban planning, emergency situations, and various industries, making them an indispensable tool for businesses and individuals alike.

    Get a glance at the Digital Map Industry report of share of various segments. Request Free Sample

    The navigation segment was valued at USD 4.58 billion in 2018 and showed a gradual increase during the forecast period.

    Regional Analysis

    APAC is estimated to contribute 43% to the growth of the global market during the forecast period.
    

    Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

    For more insights on the market share of various regions, Request Free Sample

    In the Asia-Pacific (APAC) region, the market for digital maps is experiencing growth due to the increasing use of Internet of Things (IoT) devices and real-time mapping technologies. Countries such as Japan, China, and South Korea, along with a few Southeast Asian nations, are key contributors to this market expansion. IoT devices, including GPS-enabled PDAs, professional assistants, and smart home devices, are being integrated into digital maps to provide real-time data. This data can be used to develop real-time dashboards, enabling organizations and local governments to effectively manage traffic, monitor oil field equipment, and more.

    The growing digital connectivity landscape in APAC is fueling the demand for digital maps and related technologies, including APIs, SDKs, and mapping solutions from providers such as Nearmap, ESRI, and INRIX.

    Digital Map Market Dynamics

    Our digital map market researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

    What are the key market drivers leading to the rise In the adoption of Digital Map Industry?

    Adoption of intelligent PDAs is the key driver of the market.

    The markets encompass a range of advanced technologies and applications that leverage Geographic Information Systems (
    
  7. Three-dimensional building and mobility infrastructure of the CONUS

    • zenodo.org
    • data.niaid.nih.gov
    zip
    Updated Dec 5, 2023
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    David Frantz; David Frantz; Franz Schug; Franz Schug; Sam Cooper; Sam Cooper; Camila Gomez-Medina; Camila Gomez-Medina; Patrick Hostert; Patrick Hostert (2023). Three-dimensional building and mobility infrastructure of the CONUS [Dataset]. http://doi.org/10.5281/zenodo.7043159
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    zipAvailable download formats
    Dataset updated
    Dec 5, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    David Frantz; David Frantz; Franz Schug; Franz Schug; Sam Cooper; Sam Cooper; Camila Gomez-Medina; Camila Gomez-Medina; Patrick Hostert; Patrick Hostert
    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 intermediate mapping results for estimating material stocks in the CONUS (see related identifiers) on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), Microsoft building footprints, NLCD Impervious data, and crowd-sourced geodata (OSM). These data may also be useful on their own.

    Provided layers @10m resolution
    - Building height
    - Building type
    - Building area
    - Impervious fraction
    - street, and rail area
    - Building and street climate zones
    - County zones
    - State masks
    - EQUI7 correction factors

    Spatial extent
    This dataset covers the whole CONUS.

    Temporal extent
    The maps are representative for ca. 2018.

    Data format
    The data are organized in 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

    Further information
    For further information, please see the main publication.
    A web-visualization of the resulting 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).

    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, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.

  8. Digital Map Market - Size, Share & Industry Analysis

    • mordorintelligence.com
    pdf,excel,csv,ppt
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    Mordor Intelligence, Digital Map Market - Size, Share & Industry Analysis [Dataset]. https://www.mordorintelligence.com/industry-reports/digital-map-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2021 - 2030
    Area covered
    Global
    Description

    The Global Digital Map Market is segmented by Solution (Software, Services), Deployment (On-Premise, Cloud), Industry (Automotive, Engineering & Construction, Logistics & Transportation, Energy & Utilities, Telecommunication), and Geography (North America, Europe, Asia-Pacific, Rest of the world). The market sizes and forecasts are provided in terms of value (USD million) for all the above segments.

  9. Americas Modified Atmosphere Packaging Market Size & Share Analysis -...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    + more versions
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    Mordor Intelligence, Americas Modified Atmosphere Packaging Market Size & Share Analysis - Industry Research Report - Growth Trends [Dataset]. https://www.mordorintelligence.com/industry-reports/americas-modified-atmosphere-packaging-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    Americas
    Description

    The Americas Modified Atmosphere Packaging (MAP) Market is Segmented by Material (Polyethylene, Polypropylene, Polyvinylchloride), Application (Fruits, Vegetables, Poultry, Seafood, and Meat Products, Bakery and Confectioners), and Geography.

  10. k

    USA Digital Map Market Outlook to 2028

    • kenresearch.com
    pdf
    Updated Dec 18, 2024
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    Ken Research (2024). USA Digital Map Market Outlook to 2028 [Dataset]. https://www.kenresearch.com/industry-reports/usa-digital-map-market
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Ken Research
    License

    https://www.kenresearch.com/terms-and-conditionshttps://www.kenresearch.com/terms-and-conditions

    Area covered
    United States
    Description

    Unlock data-backed intelligence on USA Digita Map Industry Insights and Future Growth, size at USD 4.9 billion in 2023, showcasing industry trends and opportunities.

  11. n

    American FactFinder

    • neuinfo.org
    • dknet.org
    • +1more
    Updated Jun 4, 2025
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    (2025). American FactFinder [Dataset]. http://identifiers.org/RRID:SCR_002932
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    Dataset updated
    Jun 4, 2025
    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

  12. H

    High Definition Maps Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 7, 2025
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    Archive Market Research (2025). High Definition Maps Report [Dataset]. https://www.archivemarketresearch.com/reports/high-definition-maps-52988
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Mar 7, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The High Definition (HD) Maps market is experiencing robust growth, driven by the escalating demand for autonomous vehicles and Advanced Driver-Assistance Systems (ADAS). The market size in 2025 is estimated at $15.49 billion, projecting a significant expansion over the forecast period (2025-2033). While the provided CAGR (Compound Annual Growth Rate) is missing, considering the rapid technological advancements and increasing adoption of autonomous driving technologies, a conservative estimate would place the CAGR between 15% and 20% for the forecast period. This growth is fueled by several key factors, including the increasing accuracy and detail offered by HD maps compared to traditional maps, enabling safer and more efficient navigation for autonomous vehicles. The market is segmented by type (centralized vs. crowdsourced mapping) and application (autonomous vehicles, ADAS, others), with autonomous vehicles currently dominating the market share due to their critical reliance on precise and up-to-date map data. Major players like TomTom, Google, HERE Technologies, and Baidu Apollo are heavily investing in research and development, fostering innovation and competition within the market. Regional growth is expected to be geographically diverse, with North America and Europe leading the initial adoption, followed by a rapid expansion in the Asia-Pacific region driven by significant investments in autonomous vehicle infrastructure and technological advancements. The competitive landscape is characterized by both established map providers and technology giants entering the market. This intense competition is pushing innovation forward, leading to more accurate, detailed, and frequently updated HD maps. Challenges include the high cost of creating and maintaining HD maps, the need for continuous data updates to reflect dynamic road conditions, and data privacy concerns surrounding the collection and use of location data. Despite these challenges, the long-term outlook for the HD Maps market remains incredibly positive, fueled by the continuous advancement of autonomous driving technology and the increasing demand for improved road safety and traffic management solutions. The market's growth trajectory suggests significant opportunities for both established players and emerging companies in the years to come. We project a substantial increase in market size by 2033, exceeding the 2025 figures by a considerable margin, based on the estimated CAGR.

  13. f

    Number of odor detections by type and location.

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Ted C. Eckmann; Samantha G. Wright; Logan K. Simpson; Joe L. Walker; Steven A. Kolmes; James E. Houck; Sandra C. Velasquez (2023). Number of odor detections by type and location. [Dataset]. http://doi.org/10.1371/journal.pone.0189175.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ted C. Eckmann; Samantha G. Wright; Logan K. Simpson; Joe L. Walker; Steven A. Kolmes; James E. Houck; Sandra C. Velasquez
    License

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

    Description

    This shows the total number of odor detections this study recorded from December 2014 through November 2015, by type of odor, separating the industrial and non-industrial categories into subcategories. The table also compares the total from all 19 stations to just those from stations 13 and 14 (see map in Fig 1).

  14. Material stock map of CONUS - South West

    • zenodo.org
    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 - South West [Dataset]. http://doi.org/10.5281/zenodo.6873600
    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 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. 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.

  15. Material stock map of CONUS - North East

    • zenodo.org
    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 - North East [Dataset]. http://doi.org/10.5281/zenodo.6869330
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    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 North East CONUS, i.e.

    • CT
    • DC
    • DE
    • MA
    • MD
    • ME
    • NH
    • NJ
    • NY
    • PA
    • RI
    • VA

    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.

  16. p

    Map Stores in Michigan, United States - 9 Available (Free Sample)

    • poidata.io
    csv
    Updated May 5, 2025
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    Poidata.io (2025). Map Stores in Michigan, United States - 9 Available (Free Sample) [Dataset]. https://www.poidata.io/report/map-store/united-states/michigan
    Explore at:
    csvAvailable download formats
    Dataset updated
    May 5, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Michigan, United States
    Description

    This dataset provides information on 9 in Michigan, United States as of May, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

  17. p

    Map Stores in Iowa, United States - 2 Available (Free Sample)

    • poidata.io
    csv
    Updated Jun 9, 2025
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    Poidata.io (2025). Map Stores in Iowa, United States - 2 Available (Free Sample) [Dataset]. https://www.poidata.io/report/map-store/united-states/iowa
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 9, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Iowa, United States
    Description

    This dataset provides information on 2 in Iowa, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

  18. N

    Navigation Map Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 6, 2025
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    Archive Market Research (2025). Navigation Map Report [Dataset]. https://www.archivemarketresearch.com/reports/navigation-map-48824
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global navigation map market is experiencing robust growth, driven by increasing adoption of location-based services across various sectors. Our analysis projects a market size of $15 billion in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This significant expansion is fueled by several key factors. The automotive industry's reliance on advanced driver-assistance systems (ADAS) and autonomous vehicles is a primary driver, demanding high-precision and regularly updated map data. Furthermore, the proliferation of mobile devices with integrated GPS and mapping applications continues to stimulate market growth. The burgeoning enterprise solutions segment, utilizing navigation maps for logistics, fleet management, and delivery optimization, contributes significantly to overall market value. Government and public sector initiatives promoting smart cities and infrastructure development further fuel demand. Technological advancements, such as the integration of LiDAR and improved GIS data, enhance map accuracy and functionality, attracting more users and driving market expansion. The market segmentation reveals substantial contributions from various application areas. The automotive segment is projected to maintain its dominance throughout the forecast period, followed closely by the mobile devices and enterprise solutions segments. Within the type segment, GIS data holds a significant market share due to its versatility and application across various sectors. However, LiDAR data is experiencing rapid growth, driven by its high precision and suitability for autonomous driving applications. Geographic regional analysis indicates strong market presence in North America and Europe, primarily driven by advanced technological infrastructure and high adoption rates. However, the Asia-Pacific region is poised for substantial growth, fueled by rapid urbanization, increasing smartphone penetration, and government investments in infrastructure development. Competitive landscape analysis reveals a blend of established players and emerging technology companies, signifying an increasingly dynamic and innovative market environment.

  19. p

    Map Stores in South Carolina, United States - 6 Available (Free Sample)

    • poidata.io
    csv
    Updated Jun 9, 2025
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    Poidata.io (2025). Map Stores in South Carolina, United States - 6 Available (Free Sample) [Dataset]. https://www.poidata.io/report/map-store/united-states/south-carolina
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 9, 2025
    Dataset provided by
    Poidata.io
    Area covered
    South Carolina, United States
    Description

    This dataset provides information on 6 in South Carolina, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

  20. National Mine Map Repository Mine Locations

    • catalog.data.gov
    • gimi9.com
    Updated Nov 28, 2023
    + more versions
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    Office of Surface Mining, Reclamation and Enforcement (2023). National Mine Map Repository Mine Locations [Dataset]. https://catalog.data.gov/dataset/national-mine-map-repository-mine-locations
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    Dataset updated
    Nov 28, 2023
    Dataset provided by
    Office of Surface Mining Reclamation and Enforcementhttp://www.osmre.gov/
    Description

    The National Mine Map Repository (NMMR) maintains point locations for mines appearing on maps within its archive. This dataset is intended to help connect the Office of Surface Mining Reclamation and Enforcement, other federal, state, and local government agencies, private industry, and the general public with archived mine maps in the NMMR's collection. The coordinates for mine point locations represent the best information the NMMR has for the location of the mine. As much as possible, the NMMR strives to find precise locations for all historic mines appearing on mine maps. When this is not possible, another feature as close to the mine as is known is used. This information is reflected in the mine point symbols. However, the NMMR cannot guarantee the accuracy of mine point locations or any other information on or derived from mine maps. The NMMR is part of the United States Department of the Interior, Office of Surface Mining Reclamation and Enforcement (OSMRE). The mission of the NMMR is to preserve abandoned mine maps, to correlate those maps to the surface topography, and to provide the public with quality map products and services. It serves as a point of reference for maps and other information on surface and underground coal, metal, and non-metal mines from throughout the United States. It also serves as a location to retrieve mine maps in an emergency. Some of the information that can be found in the repository includes: Mine and company names, Mine plans including mains, rooms, and pillars, Man-ways, shafts, and mine surface openings. Geological information such as coal bed names, bed thicknesses, bed depths and elevations, bed outcrops, drill-hole data, cross-sections, stratigraphic columns, and mineral assays. Geographical information including historic railroad lines, roads, coal towns, surface facilities and structures, ponds, streams, and property survey lines, gas well and drill-hole locations. Please note: Map images are not available for download from this dataset. They can be requested by contacting NMMR staff and providing them with the desired Document Numbers. NMMR staff also have additional search capabilities and can fulfill more complex requests if necessary. See the NMMR website homepage for contact information: https://www.osmre.gov/programs/national-mine-map-repository. There is no charge for noncommercial use of the maps. Commercial uses will incur a $46/hour research fee for fulfilling requests.

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NOAA GeoPlatform (2021). Sector Map - Manufacturing [Dataset]. https://noaa.hub.arcgis.com/maps/5cef2e53a2c44811930b5306b2ab6b9e
Organization logo

Sector Map - Manufacturing

Explore at:
Dataset updated
Jun 9, 2021
Dataset provided by
National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
Authors
NOAA GeoPlatform
License

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

Area covered
Description

This map displays drought, climate and manufacturing-related agriculture data for the United States. The map was created by the National Integrated Drought Information System (NIDIS) and is a component of the Manufacturing Sector web mapping application, a tool for exploring the relationship between drought, climate and the manufacturing sector in the United States.Data Sources for each layer are identified in the Layer section below as well as in the Layer and Legend sections of the web map. Additional information about the impact of drought on manufacturing can be found on the NIDIS Manufacturing Sector page.

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