100+ datasets found
  1. a

    Designing User Interfaces for Esri's Experience Builder – 2023 Workshop...

    • edu.hub.arcgis.com
    Updated Mar 1, 2023
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    Education and Research (2023). Designing User Interfaces for Esri's Experience Builder – 2023 Workshop Materials [Dataset]. https://edu.hub.arcgis.com/content/d16a2adb0c454dd8b8801c013637e58e
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    Dataset updated
    Mar 1, 2023
    Dataset authored and provided by
    Education and Research
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Providing user-friendly interfaces in your applications is crucial for increasing task completion and user satisfaction. This can be particularly important for geospatial applications, as these may include a high degree of complexity or may be used by the public or non-GIS professionals. This workshop will introduce you to ArcGIS Experience Builder, a new development platform from Esri that allows you to build custom Web apps for desktop and mobile devices using a drag-and-drop interface. You will learn how to develop an app using Experience Builder’s layout and widget options, as well as some best practices for integrating Experience Builder into a larger user-interface design process and optimizing your app’s interface for greater usability.

  2. Teaching and Learning With ArcGIS Online

    • teachwithgis.co.uk
    • lecture-with-gis-esriukeducation.hub.arcgis.com
    Updated Jan 28, 2023
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    Esri UK Education (2023). Teaching and Learning With ArcGIS Online [Dataset]. https://teachwithgis.co.uk/datasets/teaching-and-learning-with-arcgis-online-1
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    Dataset updated
    Jan 28, 2023
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri UK Education
    Description

    Prior experience of GIS is variable, but a number of PGCE students and in-service teachers reported negative prior experiences with geospatial technology. Common complaints include a course focussed on data students found irrelevant, with learning exercises in the form of list-like instructions. The complexity of desktop GIS software is also often mentioned as off-putting.

  3. Open-Source GIScience Online Course

    • ckan.americaview.org
    Updated Nov 2, 2021
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    ckan.americaview.org (2021). Open-Source GIScience Online Course [Dataset]. https://ckan.americaview.org/dataset/open-source-giscience-online-course
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    Dataset updated
    Nov 2, 2021
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Description

    In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

  4. Data from: Improving public safety through spatial synthesis, mapping,...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Dec 25, 2024
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    Miguel Jaller; James Thorne; Jason Whitney; Daniel Rivera-Royero (2024). Improving public safety through spatial synthesis, mapping, modeling, and performance analysis of emergency evacuation routes in California localities [Dataset]. http://doi.org/10.5061/dryad.w9ghx3g0j
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    zipAvailable download formats
    Dataset updated
    Dec 25, 2024
    Dataset provided by
    University of California, Davis
    Authors
    Miguel Jaller; James Thorne; Jason Whitney; Daniel Rivera-Royero
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    California
    Description

    The risk of natural disasters, many of which are amplified by climate change, requires the protection of emergency evacuation routes to permit evacuees safe passage. California has recognized the need through the AB 747 Planning and Zoning Law, which requires each county and city in California to update their - general plans to include safety elements from unreasonable risks associated with various hazards, specifically evacuation routes and their capacity, safety, and viability under a range of emergency scenarios. These routes must be identified in advance and maintained so they can support evacuations. Today, there is a lack of a centralized database of the identified routes or their general assessment. Consequently, this proposal responds to Caltrans’ research priority for “GIS Mapping of Emergency Evacuation Routes.” Specifically, the project objectives are: 1) create a centralized GIS database, by collecting and compiling available evacuation route GIS layers, and the safety element of the evacuation routes from different jurisdictions as well as their use in various types of evacuation scenarios such as wildfire, flooding, or landslides. 2) Perform network analyses and modeling based on the team’s experience with road network performance, access restoration, and critical infrastructure modeling, for a set of case studies, as well as, assessing their performance considering the latest evacuation research. 3) Analyze how well current bus and rail routes align with evacuation routes; and for a series of case studies, using data from previous evacuations, evaluate how well aligned the safety elements of the emerging plans are, relative to previous evacuation routes. And 4) analyze different metrics about the performance of the evacuation routes for different segments of the population (e.g., elderly, mobility constrained, non-vehicle households, and disadvantaged communities). The database and assessments will help inform infrastructure investment decisions and to develop recommendations on how best to maintain State transportation assets and secure safe evacuation routes, as they will identify the road segments with the largest impact on the evacuation route/network performance. The project will deliver a GIS of the compiled plans, a report summarizing the creation of the database and the analyses and will make a final presentation of the study results. Methods The project used the following public datasets: • Open Street Map. The team collected the road network arcs and nodes of the selected localities and the team will make public the graph used for each locality. • National Risk Index (NRI): The team used the NRI obtained publicly from FEMA at the census tract level. • American Community Survey (ACS): The team used ACS data to estimate the Social Vulnerability Index at the census block level. Then the author developed a measurement to estimate the road network performance risk at the node level, by estimating the Hansen accessibility index, betweenness centrality and the NRI. Create a set of CSV files with the risk for more than 450 localities in California, on around 18 natural hazards. I also have graphs of the RNP risk at the regional level showing the directionality of the risk.

  5. GIS Data USA | Mapping Data | 43M+ Places in the United States

    • datarade.ai
    Updated Mar 3, 2025
    + more versions
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    InfobelPRO (2025). GIS Data USA | Mapping Data | 43M+ Places in the United States [Dataset]. https://datarade.ai/data-products/gis-data-usa-mapping-data-43m-places-in-the-united-states-infobelpro
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset provided by
    Infobelhttp://www.infobel.com/
    Authors
    InfobelPRO
    Area covered
    United States
    Description

    Unlock precise, high-quality GIS data covering 43M+ verified locations across the USA. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.

    Key use cases of GIS Data helping our customers :

    1. Optimize Mapping & Spatial Analysis : Use GIS data to analyse landscapes, urban infrastructure, and competitor locations, ensuring data-driven planning and decision-making.
    2. Enhance Navigation & Location-Based Services : Improve real-time route planning, asset tracking, and EV charging station discovery for seamless location-based experiences.
    3. Identify Strategic Sites for Business Expansion : Leverage GIS intelligence to select optimal retail sites, franchise locations, and warehouses with precision.
    4. Improve Logistics & Address Accuracy : Streamline delivery networks, validate addresses, and optimize courier routes to boost efficiency and customer satisfaction.
    5. Support Environmental & Urban Development Initiatives : Utilize GIS insights for disaster preparedness, sustainable city planning, and land-use management.
  6. Geographic Information System Analytics Market Analysis, Size, and Forecast...

    • technavio.com
    pdf
    Updated Jul 22, 2024
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    Technavio (2024). Geographic Information System Analytics Market Analysis, Size, and Forecast 2024-2028: North America (US and Canada), Europe (France, Germany, UK), APAC (China, India, South Korea), Middle East and Africa , and South America [Dataset]. https://www.technavio.com/report/geographic-information-system-analytics-market-industry-analysis
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    pdfAvailable download formats
    Dataset updated
    Jul 22, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    License

    https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice

    Time period covered
    2024 - 2028
    Area covered
    Canada, United States
    Description

    Snapshot img

    Geographic Information System Analytics Market Size 2024-2028

    The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

    The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
    Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.
    

    What will be the Size of the GIS Analytics Market during the forecast period?

    Request Free Sample

    The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
    GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.
    

    How is this Geographic Information System Analytics Industry segmented?

    The geographic information system analytics 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.

    End-user
    
      Retail and Real Estate
      Government
      Utilities
      Telecom
      Manufacturing and Automotive
      Agriculture
      Construction
      Mining
      Transportation
      Healthcare
      Defense and Intelligence
      Energy
      Education and Research
      BFSI
    
    
    Components
    
      Software
      Services
    
    
    Deployment Modes
    
      On-Premises
      Cloud-Based
    
    
    Applications
    
      Urban and Regional Planning
      Disaster Management
      Environmental Monitoring Asset Management
      Surveying and Mapping
      Location-Based Services
      Geospatial Business Intelligence
      Natural Resource Management
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        China
        India
        South Korea
    
    
      Middle East and Africa
    
        UAE
    
    
      South America
    
        Brazil
    
    
      Rest of World
    

    By End-user Insights

    The retail and real estate segment is estimated to witness significant growth during the forecast period.

    The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

    The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

  7. GIS Data Italy | Mapping Data | 4.5M+ Places in Italy

    • datarade.ai
    Updated Mar 6, 2025
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    InfobelPRO (2025). GIS Data Italy | Mapping Data | 4.5M+ Places in Italy [Dataset]. https://datarade.ai/data-products/gis-data-italy-mapping-data-4-5m-places-in-italy-infobelpro
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Mar 6, 2025
    Dataset provided by
    Infobelhttp://www.infobel.com/
    Authors
    InfobelPRO
    Area covered
    Italy
    Description

    Unlock precise, high-quality GIS data covering 4.5M+ verified locations across Italy. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.

    Key use cases of GIS Data helping our customers :

    1. Optimize Mapping & Spatial Analysis : Use GIS data to analyse landscapes, urban infrastructure, and competitor locations, ensuring data-driven planning and decision-making.
    2. Enhance Navigation & Location-Based Services : Improve real-time route planning, asset tracking, and EV charging station discovery for seamless location-based experiences.
    3. Identify Strategic Sites for Business Expansion : Leverage GIS intelligence to select optimal retail sites, franchise locations, and warehouses with precision.
    4. Improve Logistics & Address Accuracy : Streamline delivery networks, validate addresses, and optimize courier routes to boost efficiency and customer satisfaction.
    5. Support Environmental & Urban Development Initiatives : Utilize GIS insights for disaster preparedness, sustainable city planning, and land-use management.
  8. m

    MA Trail Surface Condition - User Experience

    • gis.data.mass.gov
    • geodot.mass.gov
    • +4more
    Updated Mar 2, 2023
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    Massachusetts geoDOT (2023). MA Trail Surface Condition - User Experience [Dataset]. https://gis.data.mass.gov/maps/MassDOT::ma-trail-surface-condition-user-experience/about
    Explore at:
    Dataset updated
    Mar 2, 2023
    Dataset authored and provided by
    Massachusetts geoDOT
    Area covered
    Description

    This layer represents the surface condition rating per trail system collected while riding the data bike along trails for the Massachusetts Trail Surface Condition Study in 2022. The surface condition rating is calculated by a weighted average of the 10-meter interval ratings along a trail's length with rougher sections weighted more. This layer provides both a raw average and a weighted average. Surface condition data was collected via the rRuf application, which was running on an iPhone mounted on the bike's handlebars.

  9. V

    Pet-Friendly Loudoun

    • data.virginia.gov
    • s.cnmilf.com
    • +1more
    Updated Aug 23, 2024
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    Loudoun County (2024). Pet-Friendly Loudoun [Dataset]. https://data.virginia.gov/dataset/pet-friendly-loudoun
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    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Aug 23, 2024
    Dataset provided by
    Loudoun County GIS
    Authors
    Loudoun County
    Area covered
    Loudoun County
    Description

    To use browser translation, open each application in a new window here: All Pet-Friendly Resources; Veterinary Clinics; Pet-Friendly Parks; Pet-Friendly Dining

  10. a

    A call to action- doing critical GIS in a community-engaged introductory GIS...

    • usc-geohealth-hub-uscssi.hub.arcgis.com
    Updated Nov 14, 2025
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    Spatial Sciences Institute (2025). A call to action- doing critical GIS in a community-engaged introductory GIS course [Dataset]. https://usc-geohealth-hub-uscssi.hub.arcgis.com/datasets/a-call-to-action-doing-critical-gis-in-a-community-engaged-introductory-gis-course
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    Dataset updated
    Nov 14, 2025
    Dataset authored and provided by
    Spatial Sciences Institute
    Description

    Abstract: Community Engaged Learning (CEL) is a pedagogical approach that involves students, community partners, and instructors working together to analyze and address community-identified concerns through experiential learning. Implementing community-engagement in geography courses and, specifically, in GIS courses is not new. However, while students enrolled in CEL GIS courses critically reflect on social and spatial inequalities, GIS tools themselves are mostly applied in uncritical ways. Yet, CEL GIS courses can specifically help students understand GIS as a socially constructed technology which can not only empower but also disempower the community. This contribution presents the experiences from a community-engaged introductory GIS course, taught at a Predominantly White Institution (PWI) in Virginia (USA) in Spring ’24. It shows how the course helped students gain a conceptual understanding of what is GIS, how to use it, and valuable software skills, while also reflecting about their own privileges, how GIS can (dis)empower the community, and their own role as a GIS analyst. Ultimately, the paper shows how the course supported positive changes in the community, equity in education, reciprocity in university/community relationships, and student civic-mindedness.

  11. D

    Disability and Health Insurance - Seattle Neighborhoods

    • data.seattle.gov
    • catalog.data.gov
    • +1more
    csv, xlsx, xml
    Updated Oct 22, 2024
    + more versions
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    (2024). Disability and Health Insurance - Seattle Neighborhoods [Dataset]. https://data.seattle.gov/dataset/Disability-and-Health-Insurance-Seattle-Neighborho/nxn5-xp4j
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Oct 22, 2024
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on disabilities and health insurance related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes C21007 Age by Veteran Status by Poverty Status in the Past 12 Months by Disability Status, B27010 Types of Health Insurance Coverage by Age, B22010 Receipt of Food Stamps/SNAP by Disability Status for Households. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.


    Table created for and used in the Neighborhood Profiles application.

    Vintages: 2023
    ACS Table(s): C21007, B27010, B22010


    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb(year)a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data

  12. l

    Workers' Rights Income and Employment Index (census tract)

    • geohub.lacity.org
    • data.lacounty.gov
    • +1more
    Updated Oct 13, 2023
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    County of Los Angeles (2023). Workers' Rights Income and Employment Index (census tract) [Dataset]. https://geohub.lacity.org/datasets/lacounty::workers-rights-income-and-employment-index-census-tract/explore
    Explore at:
    Dataset updated
    Oct 13, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Created for CEO-ARDI and DCBA in response to a Board of Supervisors motion on workers' rights to develop a targeted outreach plan for "high need"/impacted communities.Data (mostly) from US Census ACS 5-year estimates 2023. See the Equity Explorer layer descriptions for detailed source information: https://experience.arcgis.com/experience/9d7a43397ea84ab98a534be5b5376fba/page/Layer-Details/ Data featured on the Workers' Rights Income and Employment Index Dashboard.For questions or more information please contact egis@isd.lacounty.gov.

  13. u

    NEWT: National Extension Web-mapping Tool

    • agdatacommons.nal.usda.gov
    bin
    Updated Nov 21, 2025
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    Cooperative Extension System; Virginia Tech Center for Geospatial Information Technology (2025). NEWT: National Extension Web-mapping Tool [Dataset]. https://agdatacommons.nal.usda.gov/articles/dataset/NEWT_National_Extension_Web-mapping_Tool/24852795
    Explore at:
    binAvailable download formats
    Dataset updated
    Nov 21, 2025
    Dataset provided by
    Cooperative Extension System
    Authors
    Cooperative Extension System; Virginia Tech Center for Geospatial Information Technology
    License

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

    Description

    eXtension Foundation, the University of New Hampshire, and Virginia Tech have developed a mapping and data exploration tool to assist Cooperative Extension staff and administrators in making strategic planning and programming decisions. The tool, called the National Extension Web-mapping Tool (or NEWT), is the key in efforts to make spatial data available within cooperative extension system. NEWT requires no GIS experience to use. NEWT provides access for CES staff and administrators to relevant spatial data at a variety of scales (national, state, county) in useful formats (maps, tables, graphs), all without the need for any experience or technical skills in Geographic Information System (GIS) software. By providing consistent access to relevant spatial data throughout the country in a format useful to CES staff and administrators, NEWT represents a significant advancement for the use of spatial technology in CES. Users of the site will be able to discover the data layers which are of most interest to them by making simple, guided choices about topics related to their work. Once the relevant data layers have been chosen, a mapping interface will allow the exploration of spatial relationships and the creation and export of maps. Extension areas to filter searches include 4-H Youth & Family, Agriculture, Business, Community, Food & Health, and Natural Resources. Users will also be able to explore data by viewing data tables and graphs. This Beta release is open for public use and feedback. Resources in this dataset:Resource Title: Website Pointer to NEWT National Extension Web-mapping Tool Beta. File Name: Web Page, url: https://www.mapasyst.org/newt/ The site leads the user through the process of selecting the data in which they would be most interested, then provides a variety of ways for the user to explore the data (maps, graphs, tables).

  14. GIS Data | 164M+ Global Places

    • datarade.ai
    Updated Mar 6, 2025
    + more versions
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    InfobelPRO (2025). GIS Data | 164M+ Global Places [Dataset]. https://datarade.ai/data-products/gis-data-164m-global-places-infobelpro
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Mar 6, 2025
    Dataset provided by
    Infobelhttp://www.infobel.com/
    Authors
    InfobelPRO
    Area covered
    United Kingdom, France, United States
    Description

    Unlock precise, high-quality GIS data covering 164M+ verified locations across 220+ countries. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.

    Key use cases of GIS Data helping our customers :

    1. Optimize Mapping & Spatial Analysis : Use GIS data to analyse landscapes, urban infrastructure, and competitor locations, ensuring data-driven planning and decision-making.
    2. Enhance Navigation & Location-Based Services : Improve real-time route planning, asset tracking, and EV charging station discovery for seamless location-based experiences.
    3. Identify Strategic Sites for Business Expansion : Leverage GIS intelligence to select optimal retail sites, franchise locations, and warehouses with precision.
    4. Improve Logistics & Address Accuracy : Streamline delivery networks, validate addresses, and optimize courier routes to boost efficiency and customer satisfaction.
    5. Support Environmental & Urban Development Initiatives : Utilize GIS insights for disaster preparedness, sustainable city planning, and land-use management.
  15. Asynchronous ArcGIS for Schools Materials

    • teachwithgis.co.uk
    • lecture-with-gis-esriukeducation.hub.arcgis.com
    Updated Mar 8, 2024
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    Esri UK Education (2024). Asynchronous ArcGIS for Schools Materials [Dataset]. https://teachwithgis.co.uk/datasets/asynchronous-arcgis-for-schools-materials
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    Dataset updated
    Mar 8, 2024
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri UK Education
    Description

    In this asynchronous session, you will use some of the free GIS tools from the Teach With GIS website, created and maintained by the Esri UK education team. All of these tools are free to use and accessible as websites from laptops, tablets and mobile devices. We recommend that you view them on a laptop or tablet if possible, to give you plenty of screen space to see every detail. They do not require any logins or subscriptions. We want you to experience using modern, online GIS tools from the perspective of a student before you begin to create your own tools, maps, and lessons. We have chosen a range of tools that let you experience GIS as a tool to examine physical and human geography, and to compare and contrast over space and time.

  16. a

    Getting Started with GIS

    • hub.arcgis.com
    Updated Jan 30, 2019
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    State of Delaware (2019). Getting Started with GIS [Dataset]. https://hub.arcgis.com/documents/52a04f17dfa845d79036ea5f341be606
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    Dataset updated
    Jan 30, 2019
    Dataset authored and provided by
    State of Delaware
    Description

    Get an introduction to the basic components of a GIS. Learn fundamental concepts that underlie the use of a GIS with hands-on experience with maps and geographic data.

  17. d

    Mapping the Census using Open-Source GIS

    • dataone.org
    Updated Dec 28, 2023
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    Elizabeth Sutherland (2023). Mapping the Census using Open-Source GIS [Dataset]. http://doi.org/10.5683/SP3/SFCC3J
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Elizabeth Sutherland
    Description

    Maps have always been a powerful tool for visualizing data. Participants will learn how to link the static data of census tables to census geographies by using open-source GIS software. Participants will learn how to join data, calculate new attributes, symbolize geography and create maps. No prior GIS experience is necessary. QGIS will be required to be downloaded prior to the workshop, and laptops will be required. Download instructions https://qgis.org/en/site/forusers/download.html. Download data files https://drive.google.com/drive/folders/1xrAj_BrPtMDBgdi9MXWGcrcuVGfTsGgi?usp=sharing

  18. c

    SB 535 Disadvantaged Communities (Additional Tribal Areas 2023 & 2024)

    • gis.data.ca.gov
    • data.ca.gov
    • +3more
    Updated Jul 11, 2024
    + more versions
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    OEHHA ArcGIS Online (2024). SB 535 Disadvantaged Communities (Additional Tribal Areas 2023 & 2024) [Dataset]. https://gis.data.ca.gov/datasets/OEHHA::sb-535-disadvantaged-communities-additional-tribal-areas-2023-2024
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    Dataset updated
    Jul 11, 2024
    Dataset authored and provided by
    OEHHA ArcGIS Online
    Area covered
    Description

    This map shows the 2022 disadvantaged communities designated by CalEPA for the purpose of SB 535. These areas represent:

    • Highest scoring 25% of census tracts from CalEnviroScreen 4.0, along with census tracts scoring in the top 5% of the Pollution Burden indicator but without an overall CalEnviroScreen score due to due to unavailable or unreliable Population Characteristics indicator data and score.
    • All census tracts currently identified as disadvantaged but not in the highest scoring 25% census tracts in version 4.0 (i.e., the highest scoring 25% of census tracts in CalEnviroScreen 3.0 along with the census tracts with the highest 5% Pollution Burden scores, but without an overall CalEnviroScreen score). See the Disadvantaged Communities 2017 map here.
    • Federally recognized tribal areas as identified by the Census in the 2021 American Indian Areas Related National Geodatabase. A Tribe may establish that a particular area of land is under its control, for purposes of this designation, by requesting a consultation with the CalEPA Deputy Secretary for Environmental Justice, Tribal Affairs and Border Relations at TribalAffairs@calepa.ca.gov
    Please see CalEPA's Draft Designation of Disadvantaged Communities Pursuant to Senate Bill 535 document as well as CalEPA's California Climate Investments to Benefit Disadvantaged Communities page.

  19. n

    GIS for Coronavirus Planning and Response Whitepaper

    • prep-response-portal.napsgfoundation.org
    • prep-response-portal-napsg.hub.arcgis.com
    Updated Apr 1, 2020
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    Esri’s Disaster Response Program (2020). GIS for Coronavirus Planning and Response Whitepaper [Dataset]. https://prep-response-portal.napsgfoundation.org/documents/939886dd26614a2b9d72b3eef46b4f02
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    Dataset updated
    Apr 1, 2020
    Dataset authored and provided by
    Esri’s Disaster Response Program
    Description

    Infectious disease experts have predicted a pandemic, saying it was not a question of if but when. Drawing on experiences with severe acute respiratory syndrome (SARS), avian influenza (H5N1), and novel influenza A (H1N1), the World Health Organization (WHO) and other health authorities, such as the Centers for Disease Control and Prevention (CDC), urged nations and local governments to prepare pandemic response plans. Many ministries of health and subnational departments of health around the world have activated those plans in response to coronavirus and are sharing data as required by the updated International Health Regulations.Esri's work with health organizations and government leaders has proven location intelligence from geographic information system (GIS) technology and data to be critical for the following:Assessing risk and evaluating threatsMonitoring and tracking outbreaksMaintaining situational awarenessEnsuring resource allocationNotifying agencies and communitiesThe current coronavirus disease pandemic presents an opportunity to build on the experience and readiness of Esri's existing global user community in health and human services. Through real-time maps, apps, and dashboards, GIS will also facilitate a seamless flow of relevant data as a component of the response from local to global levels. A compelling case exists for building on top of the public health GIS foundation that is already in place both in the United States and around the world.After reading this paper, leadership and senior staff should understand the following:The necessity to apply location intelligence to public health processes in coronavirus responseHow GIS can support immediate and long-term actionWhat resources Esri provides its customers

  20. d

    Data from: Experiences with Data Dissemination

    • search.dataone.org
    Updated Dec 28, 2023
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    Bo Wandschneider (2023). Experiences with Data Dissemination [Dataset]. http://doi.org/10.5683/SP3/HHGNXL
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Bo Wandschneider
    Description

    This presentation covers: the history of the Data Resource Centre (DRC); why it is successful; the hardware; what you need; recent developments; and what is going on with GIS.

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Education and Research (2023). Designing User Interfaces for Esri's Experience Builder – 2023 Workshop Materials [Dataset]. https://edu.hub.arcgis.com/content/d16a2adb0c454dd8b8801c013637e58e

Designing User Interfaces for Esri's Experience Builder – 2023 Workshop Materials

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Dataset updated
Mar 1, 2023
Dataset authored and provided by
Education and Research
License

Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically

Description

Providing user-friendly interfaces in your applications is crucial for increasing task completion and user satisfaction. This can be particularly important for geospatial applications, as these may include a high degree of complexity or may be used by the public or non-GIS professionals. This workshop will introduce you to ArcGIS Experience Builder, a new development platform from Esri that allows you to build custom Web apps for desktop and mobile devices using a drag-and-drop interface. You will learn how to develop an app using Experience Builder’s layout and widget options, as well as some best practices for integrating Experience Builder into a larger user-interface design process and optimizing your app’s interface for greater usability.

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