23 datasets found
  1. n

    ArcGIS for Coders: Learn the Javascript API

    • library.ncge.org
    • library-ncge.hub.arcgis.com
    Updated Jun 8, 2020
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    NCGE (2020). ArcGIS for Coders: Learn the Javascript API [Dataset]. https://library.ncge.org/documents/672aee2ab8954e218ce07cb53c88e65f
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    Dataset updated
    Jun 8, 2020
    Dataset authored and provided by
    NCGE
    Description

    The ArcGIS Javascript API lets developers build GIS web applications. The Javascript API is one of many that could be used but it's a great starting place. Students may also be interested in the Python API or others!

  2. Demo: Exercise F6: Create a JS API 4.x WebMap App or Create a JS API 4.x...

    • se-national-government-developer-esrifederal.hub.arcgis.com
    Updated Mar 13, 2025
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    Esri National Government (2025). Demo: Exercise F6: Create a JS API 4.x WebMap App or Create a JS API 4.x WebScene App [Dataset]. https://se-national-government-developer-esrifederal.hub.arcgis.com/datasets/demo-exercise-f6-create-a-js-api-4-x-webmap-app-or-create-a-js-api-4-x-webscene-app
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    Dataset updated
    Mar 13, 2025
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri National Government
    License

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

    Description

    Author: Megan Banaski (mbanaski@esri.com) and Max Ozenberger (mozenberger@esri.com)Last Updated: 1/1/2024Intended Environment: WebPurpose:Exercise F6: Create a JS API 4.x WebMap App or Create a JS API 4.x WebScene App This lab is part of GitHub repository that contains short labs that step you through the process of developing a web application with ArcGIS API for JavaScript.The labs start from ground-zero and work through the accessing different aspects of the API and how to begin to build an application and add functionality.Requirements: Here are the resources you will use for the labs.ArcGIS for Developers - Account, Documentation, Samples, Apps, DownloadsEsri Open Source Projects - More source codeA simple guide for setting up a local web server (optional)Help with HTML, CSS, and JavaScript

  3. National Tunnel Inventory Element Data

    • catalog.data.gov
    • datasets.ai
    • +4more
    Updated Sep 5, 2025
    + more versions
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    Federal Highway Administration (FHWA) (Point of Contact) (2025). National Tunnel Inventory Element Data [Dataset]. https://catalog.data.gov/dataset/national-tunnel-inventory-element-data1
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    Dataset updated
    Sep 5, 2025
    Dataset provided by
    Federal Highway Administrationhttps://highways.dot.gov/
    Description

    The National Tunnel Inventory Elements dataset was compiled on September 02, 2025 and published on August 26, 2025 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The National Tunnel Inventory (NTI) is a collection of information (database) describing the more than 500 of the Nation's tunnels located on public roads, including Interstate Highways, U.S. highways, State and county roads, as well as publicly-accessible tunnels on Federal lands. The element data present a breakdown of the condition of each structural and civil element for each tunnel on the National Highway System (NHS). A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529051

  4. a

    Data from: Google Earth Engine (GEE)

    • hub.arcgis.com
    • amerigeo.org
    • +6more
    Updated Nov 29, 2018
    + more versions
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    AmeriGEOSS (2018). Google Earth Engine (GEE) [Dataset]. https://hub.arcgis.com/items/bb1b131beda24006881d1ab019205277
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    Dataset updated
    Nov 29, 2018
    Dataset authored and provided by
    AmeriGEOSS
    Description

    Meet Earth EngineGoogle Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities and makes it available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface.SATELLITE IMAGERY+YOUR ALGORITHMS+REAL WORLD APPLICATIONSLEARN MOREGLOBAL-SCALE INSIGHTExplore our interactive timelapse viewer to travel back in time and see how the world has changed over the past twenty-nine years. Timelapse is one example of how Earth Engine can help gain insight into petabyte-scale datasets.EXPLORE TIMELAPSEREADY-TO-USE DATASETSThe public data archive includes more than thirty years of historical imagery and scientific datasets, updated and expanded daily. It contains over twenty petabytes of geospatial data instantly available for analysis.EXPLORE DATASETSSIMPLE, YET POWERFUL APIThe Earth Engine API is available in Python and JavaScript, making it easy to harness the power of Google’s cloud for your own geospatial analysis.EXPLORE THE APIGoogle Earth Engine has made it possible for the first time in history to rapidly and accurately process vast amounts of satellite imagery, identifying where and when tree cover change has occurred at high resolution. Global Forest Watch would not exist without it. For those who care about the future of the planet Google Earth Engine is a great blessing!-Dr. Andrew Steer, President and CEO of the World Resources Institute.CONVENIENT TOOLSUse our web-based code editor for fast, interactive algorithm development with instant access to petabytes of data.LEARN ABOUT THE CODE EDITORSCIENTIFIC AND HUMANITARIAN IMPACTScientists and non-profits use Earth Engine for remote sensing research, predicting disease outbreaks, natural resource management, and more.SEE CASE STUDIESREADY TO BE PART OF THE SOLUTION?SIGN UP NOWTERMS OF SERVICE PRIVACY ABOUT GOOGLE

  5. b

    National Bridge Inventory Element Data

    • geodata.bts.gov
    • s.cnmilf.com
    • +3more
    Updated Jul 1, 2020
    + more versions
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    U.S. Department of Transportation: ArcGIS Online (2020). National Bridge Inventory Element Data [Dataset]. https://geodata.bts.gov/datasets/usdot::national-bridge-inventory-element-data/about
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    Dataset updated
    Jul 1, 2020
    Dataset authored and provided by
    U.S. Department of Transportation: ArcGIS Online
    Description

    The National Bridge Inventory Elements dataset is as of June 20, 2025 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The data describes more than 620,000 of the Nation's bridges located on public roads, including Interstate Highways, U.S. highways, State and county roads, as well as publicly-accessible bridges on Federal and Tribal lands. The element data present a breakdown of the condition of each structural and bridge management element for each bridge on the National Highway System (NHS). The Specification for the National Bridge Inventory Bridge Elements contains a detailed description of each data element including coding instructions and attribute definitions. The Coding Guide is available at: https://doi.org/10.21949/1519106. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1519106

  6. Sentinel Explorer Classic

    • caribbeangeoportal.com
    • cacgeoportal.com
    • +15more
    Updated May 23, 2018
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    Esri (2018). Sentinel Explorer Classic [Dataset]. https://www.caribbeangeoportal.com/datasets/esri::sentinel-explorer-classic
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    Dataset updated
    May 23, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Description

    Mature Support Notice: This item is in mature support as of February 2025. A new version of this item is available for your use. This web application highlights some of the capabilities for accessing Sentinel-2 imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Sentinel-2 images on a daily basis.Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Sentinel-2 Explorer app provides the power of Sentinel-2 satellites, which gather data beyond what the eye can see. Use this app to draw on Sentinel's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the Sentinel-2 archive to visualize how the Earth's surface has changed over the last fourteen monthsQuick access to the following band combinations and indices is provided: BandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020 Agriculture : Highlights vigorous vegetation in bright green, stressed vegetation dull green and bare areas brown; Bands 11, 8, 2Natural Color : Bands 4, 3, 2Color Infrared : Healthy vegetation is bright red while stressed vegetation is dull red; Bands 8, 4 ,3 SWIR (Short-wave Infrared) : Highlights rock formations; Bands 12, 11, 4Geology : Highlights geologic features; Bands 12, 11, 2Bathymetric : Highlights underwater features; Bands 4, 3, 1Vegetation Index : Normalized Difference Vegetation Index(NDVI) with Colormap ; (Band 8 - Band 4)/(Band 8 + Band 4)Moisture Index : Normalized Difference Moisture Index (NDMI); (Band 8 - Band 11)/(Band 8 + Band 11)Normalized Burn Ratio : (Band 8 - Band 12)/(Band 8 + Band 12)Built-Up Index : (Band 11 - Band 8)/(Band 11 + Band 8)NDVI Raw : Normalized Difference Vegetation Index(NDVI); (Band 8 - Band 4)/(Band 8 + Band 4)NDVI - VRE only Raw : NDVI with VRE bands only; (Band 6 - Band 5)/(Band 6 + Band 5)NDVI - VRE only Colorized : NDVI with VRE bands only with Colormap; (Band 6 - Band 5)/(Band 6 + Band 5)NDVI - with VRE Raw : Also known as NDRE. NDVI with VRE band 5 and NIR band 8; (Band 8 - Band 5)/(Band 8 + Band 5)NDVI - with VRE Colorized : Also known as NDRE with Colormap; (Band 8 - Band 5)/(Band 8 + Band 5)NDWI Raw : Normalized Difference Water index with Green band and NIR band; (Band 3 - Band 8)/(Band 3 + Band 8)NDWI - with VRE Raw : Normalized Difference Water index with VRE band 5 and Green band 3; (Band 3 - Band 5)/(Band 3 + Band 5)NDWI - with VRE Colorized : NDWI index with VRE band 5 and Green band 3 with Colormap; (Band 3 - Band 5)/(Band 3 + Band 5)Custom SAVI : (Soil Adjusted Veg. Index); Offset + Scale*(1.5*(Band 8 - Band 4)/(Band 8 + Band 4 + 0.5))Custom Water Index : Offset + Scale*(Band 3 - Band 12)/(Band 3 + Band 12) Custom Burn Index : Offset + Scale*(Band 8 - Band 13)/(Band 8 + Band 13)Urban Index : Offset + Scale*(Band 8 - Band 12)/(Band 8 + Band 12)Optionally, you can also choose the "Custom Bands" or "Custom Index" option to create your own band combinations The Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for indices like NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Bookmark tool will direct you to pre-selected interesting locations.NOTE: Using the Time tool to access imagery in the Sentinel-2 archive requires an ArcGIS account. The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript. The following Imagery Layer are being accessed : Sentinel-2 - Provides access to 10, 20, and 60m 13-band multispectral imagery and a range of functions that provide different band combinations and indices.

  7. d

    i08 C2VSimFG Element Centroids

    • catalog.data.gov
    • data.ca.gov
    • +6more
    Updated Jul 24, 2025
    + more versions
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    California Department of Water Resources (2025). i08 C2VSimFG Element Centroids [Dataset]. https://catalog.data.gov/dataset/i08-c2vsimfg-element-centroids-c6bd3
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    California Department of Water Resources
    Description

    There is a total of 32, 537 elements (centroids) within the C2VSimFG model, which make up the finite element mesh of the model. The elements are subdivided into 21 subregions. Each element is composed of corresponding groundwater nodes within the model domain. The model domain area is 20, 742 square miles, and the average element size is roughly 407 acres. The boundaries of the model grid were developed using a set of control points at important locations of the model area. The finite grid mesh was created using GIS and several Excel and FORTRAN utilities. The grid size was refined in areas of higher groundwater gradient and/or areas that are more critical from hydrogeological viewpoints. The grid lines are designed parallel to the streamflow direction, when possible, as well as the groundwater streamlines, to capture the surface and subsurface drainage patterns. Nine major faults in the Central Valley are represented by thin strip of elements of around 500 feet. The dataset excludes three geologic outcrops: Sutter Buttes, Kettleman Hills and Capay Valley Hills, which are areas not included in the Bulletin 118. The dataset is maintained by the Sustainable Groundwater Management Office, Modeling and Tools Support Section.

  8. H

    Data from: RTB Maps Version 1.0

    • datasetcatalog.nlm.nih.gov
    • dataverse.harvard.edu
    • +1more
    Updated Aug 18, 2021
    + more versions
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    Giron, Ernesto; Rivera, Ovidio; Castano, Silvia-Elena; Barona, Elizabeth; Hyman, Glenn Graham (2021). RTB Maps Version 1.0 [Dataset]. http://doi.org/10.7910/DVN/P4BEJ7
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    Dataset updated
    Aug 18, 2021
    Authors
    Giron, Ernesto; Rivera, Ovidio; Castano, Silvia-Elena; Barona, Elizabeth; Hyman, Glenn Graham
    Description

    RTB Maps is a cloud-based electronic Atlas. We used ArGIS 10 for Desktop with Spatial Analysis Extension, ArcGIS 10 for Server on-premise, ArcGIS API for Javascript, IIS web services based on .NET, and ArcGIS Online combining data on the cloud with data and applications on our local server to develop an Atlas that brings together many of the map themes related to development of roots, tubers and banana crops. The Atlas is structured to allow our participating scientists to understand the distribution of the crops and observe the spatial distribution of many of the obstacles to production of these crops. The Atlas also includes an application to allow our partners to evaluate the importance of different factors when setting priorities for research and development. The application uses weighted overlay analysis within a multi-criteria decision analysis framework to rate the importance of factors when establishing geographic priorities for research and development. Datasets of crop distribution maps, agroecology maps, biotic and abiotic constraints to crop production, poverty maps and other demographic indicators are used as a key inputs to multi-objective criteria analysis www.rtb.cgiar.org/RTBMaps

  9. A Personalized Activity-based Spatiotemporal Risk Mapping Approach to...

    • figshare.com
    tiff
    Updated Mar 18, 2021
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    Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang (2021). A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic [Dataset]. http://doi.org/10.6084/m9.figshare.13517105.v1
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    tiffAvailable download formats
    Dataset updated
    Mar 18, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang
    License

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

    Description

    The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.

  10. a

    Light Rail Alignment

    • data-seattlecitygis.opendata.arcgis.com
    • hub.arcgis.com
    Updated May 23, 2024
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    City of Seattle ArcGIS Online (2024). Light Rail Alignment [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::light-rail-alignment-1
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    Dataset updated
    May 23, 2024
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Description

    See Sound Transit

  11. Landsat Explorer Classic

    • morocco.africageoportal.com
    • communities-amerigeoss.opendata.arcgis.com
    • +3more
    Updated Jan 10, 2018
    + more versions
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    Esri (2018). Landsat Explorer Classic [Dataset]. https://morocco.africageoportal.com/datasets/esri::landsat-explorer-classic
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    Dataset updated
    Jan 10, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Description

    Mature Support Notice: This item is in mature support as of February 2024. A new version of this item is available for your use. This web application highlights some of the capabilities for accessing Landsat imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Landsat images on a daily basis. Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Landsat Explorer app provides the power of Landsat satellites, which gather data beyond what the eye can see. Use this app to draw on Landsat's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the entire Landsat archive to visualize how the Earth's surface has changed over the last forty years.Quick access to the following band combinations and indices is provided: Agriculture : Highlights agriculture in bright green; Bands 6, 5, 2Natural Color : Sharpened with 15m panchromatic band; Bands 4, 3, 2 +8Color Infrared : Healthy vegetation is bright red; Bands 5, 4 ,3 SWIR (Short Wave Infrared) : Highlights rock formations; Bands 7, 6, 4Geology : Highlights geologic features; Bands 7, 6, 2Bathymetric : Highlights underwater features; Bands 4, 3, 1Panchromatic : Panchromatic images at 15m; Band 8Vegetation Index : Normalized Difference Vegetation Index(NDVI); (Band 5 - Band 4)/(Band 5 + Band 4)Moisture Index : Normalized Difference Moisture Index (NDMI); (Band 5 - Band 6)/(Band 5 + Band 6)SAVI : Soil Adjusted Veg. Index); Offset + Scale*(1.5*(Band 5 - Band 4)/(Band 5 + Band 4 + 0.5))Water Index : Offset + Scale*(Band 3 - Band 6)/(Band 3 + Band 6)Burn Index : Offset + Scale*(Band 5 - Band 7)/(Band 5 + Band 7)Urban Index : Offset + Scale*(Band 5 - Band 6)/(Band 5 + Band 6)Optionally, you can also choose the "Custom Bands" or "Custom Index" option to create your own band combinations The Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Stories tool will direct you to pre-selected interesting locations. The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript. The following Imagery Layers are being accessed : Multispectral Landsat - Provides access to 30m 8-band multispectral imagery and a range of functions that provide different band combinations and indices.Pansharpened Landsat - Provides access to 15m 4-band (Red, Green, Blue and NIR) panchromatic-sharpened imagery.Panchromatic Landsat - Provides access to 15m panchromatic imagery. These imagery layers can be accessed through the public group Landsat Community on ArcGIS Online.

  12. d

    Seattle Transportation Plan Bicycle Element

    • catalog.data.gov
    • data.seattle.gov
    • +2more
    Updated Feb 28, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). Seattle Transportation Plan Bicycle Element [Dataset]. https://catalog.data.gov/dataset/seattle-transportation-plan-bicycle-element
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    Dataset updated
    Feb 28, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    The Bicycle and E-Mobility Element of the STP will help create a safer, more bikeable Seattle. It provides a foundation for the City of Seattle to grow our investment in bicycling and e-mobility to achieve STP goals. The STP and the Bicycle and E-Mobility Element build on and supersede the 2014 Bicycle Master Plan (BMP). The bicycle and e-mobility network serves not only people riding traditional bicycles, but also people using adaptive bikes, cargo bicycles for both personal use and deliveries, trikes, scooters, skateboards, roller skates, wheelchairs or other wheeled mobility devices, and “e-mobility” devices, which refers to personal and shared electric-powered bicycles, scooters, and other electric-powered devices. It serves people bicycling and taking e-mobility to serve a variety of trip purposes, such as getting to work, school, transit, the gym or doctor's office, recreating, making urban goods deliveries, and more.The Bike+ network consists of bikeways suitable for people of all ages and abilities (AAA), including protected bike lanes, Neighborhood Greenways, Healthy Streets, and bike lanes where vehicle speeds and volumes are sufficiently low. The Bike+ network is envisioned to seamlessly integrate with the multi-use trail network, which provides connections through or on the edges of parks and opens spaces, where an off-street connection is preferred, or is more feasible than an on-street connection. Diagram of an umbrella titled "What is Bike+?" Underneath the umbrella, the following are bulleted - protected bike lane, bike lane (if vehicle speed and volumes low. See Table 4), neighborhood greenway, and healthy street. Many planned projects from the 2014 BMP have been implemented and are shown on the existing bicycle and e-mobility network map. The Bike+ network shows existing and proposed AAA bikeways on Seattle’s arterial and non-arterial (i.e., neighborhood streets) networks.Refresh Cycle: None, Static. Manually as required.Original Publish: 5/23/2024Update Publish: 7/11/2024 per Policy and Planning teamContact: Policy and Planning team

  13. l

    Los Angeles County Housing Element (2021-2029) - County-Owned Projects in...

    • data.lacounty.gov
    • geohub.lacity.org
    • +2more
    Updated Aug 15, 2023
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    County of Los Angeles (2023). Los Angeles County Housing Element (2021-2029) - County-Owned Projects in Cities [Dataset]. https://data.lacounty.gov/datasets/los-angeles-county-housing-element-2021-2029-county-owned-projects-in-cities
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    Dataset updated
    Aug 15, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    These are county-owned projects that lie within incorporated cities. They help count towards the RHNA for the latest Housing Element. This layer was generated from parcels and aggregated to form one project boundary. Below is a description of this data from the Housing Element (specifically, page 207): While the County has land use jurisdiction in unincorporated Los Angeles County, it also owns land in cities within Los Angeles County. Through interjurisdictional partnerships, the County has used these sites to increase opportunities for interim and permanent housing. As a strategy to accommodate the RHNA, the County includes the capacity or planned development on County-owned sites in cities, where the County is the authority to approve planning entitlements and issue building permits pursuant to the County’s sovereign immunity, as established by California Government Code §53090 and 53091. Zoning and land use regulations for cities do not apply to these sites.

  14. Arctic DEM Explorer (Mature Support)

    • seakfhpdatahub-psmfc.hub.arcgis.com
    • communities-amerigeoss.opendata.arcgis.com
    Updated Aug 30, 2016
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    Esri (2016). Arctic DEM Explorer (Mature Support) [Dataset]. https://seakfhpdatahub-psmfc.hub.arcgis.com/datasets/esri::arctic-dem-explorer-mature-support
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    Dataset updated
    Aug 30, 2016
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Arctic
    Description

    Retirement Notice: This item is in mature support as of July 2024 and will retire in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This web application enables the exploration of Arctic elevation based on the 2m resolution Arctic Digital Elevation Models (DEM) created by the Polar Geospatial Center. The app displays multiple different renderings as well as profiles of the data. In many areas the coverage is available from multiple dates and the app displays temporal profiles as well as computing the differences. The current datasets consisting of 2m DEMs, cover the Arctic from 60*N to the Pole and will gradually, and incrementally be replaced with better 2m versions as they are produced during 2018. The elevations are digital surface models photogrammetrically generated from stereo satellite imagery and have not been edited to create terrain heights. The current datasets are preliminary and are known to contain some errors and artifacts. As more control becomes available, the elevation values will be refined and adjusted. The original PGC datasets have been adjusted according to the PGC proposed correction parameters, to give WGS84 ellipsoidal heights, but available in this service also as orthometric heights computed using the EGM2008 geoid separation. Details on how the DEMs are generated and their use can be found in ArcticDEM datasets. The DEMs were created from DigitalGlobe, Inc., imagery and funded under National Science Foundation awards 1043681, 1559691, and 1542736.The app also provides access to the Arctic Landsat imagery that is updated daily and also served through ArcGIS Online.Quick access to server functions defined for the following elevation derivatives are provided:Hillshade – Hillshaded surface generated dynamically on elevation layer, with a solar azimuth of 315 degrees and solar altitude of 45 degreesMulti-Directional Hillshade – Multi-directional hillshaded surface generated dynamically on elevation layer, computing hillshade from 6 different directionsElevation Tinted Hillshade – Elevation tinted hillshade surface generated dynamically on elevation layerSlopeMap – A color visualization of Slope surface generated dynamically on elevation layer, where flat surfaces is gray, shallow slopes are yellow and steep slopes are orangeAspectMap - A color visualization of aspect generated dynamically on elevation layerContour – Dynamically generated contours with specified contour intervals and options for smoothing to create more cartographically pleasing contours.The Time tool enables access to a temporal time slider and temporal profile for a selected point. The Time tool is only accessible at larger zoom scales. The Identify tool enables access to elevation, slope and aspect values for the specified point as well as information on the source image and links to download the source data. From the app it is also possible to export defined areas of the DEMs. These can be exported in user defined projections and resolutions. The Bookmark tool link to pre-selected interesting locations.For more information on the underlying services see Arctic DEM layer.The application is written using Web AppBuilder for ArcGIS accessing imagery layers using the ArcGIS API for JavaScript.

  15. a

    Urban Observatory Compare App

    • fesec-cesj.opendata.arcgis.com
    • gis-for-secondary-schools-schools-be.hub.arcgis.com
    Updated Aug 16, 2013
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    ArcGIS Maps for the Nation (2013). Urban Observatory Compare App [Dataset]. https://fesec-cesj.opendata.arcgis.com/datasets/nation::urban-observatory-compare-app
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    Dataset updated
    Aug 16, 2013
    Dataset authored and provided by
    ArcGIS Maps for the Nation
    Description

    The Urban Observatory Compare app shows maps of the same subject for three cities, in a side by side comparison view. The app allows quick visual comparisons of the patterns at work in cities around the world.The app allows people to interact with rich datasets for each city. People can use the Urban Observatory web application to easily compare cities by using a simple web browser. As a user zooms in to one digital city map, other city maps will zoom in parallel, revealing similarities and differences in density and distribution. For instance, a person can simultaneously view traffic density for Abu Dhabi and Paris or simultaneously view vegetation in London and Tokyo.The Urban Observatory is brought to you by Richard Saul Wurman, creator of Technology/Entertainment/Design (TED) and 19.20.21; Jon Kamen of the Academy Award-, Emmy Award-, and Golden Globe Award-winning film company @radical.media; and Esri president Jack Dangermond. "A map is a pattern made understandable, and patterns must be compared to understand successes, failures, and opportunities of our global cities," says Wurman. "The Urban Observatory demonstrates this new paradigm, using cartographic language and constructive data display. People and cities can use maps as a common language," said Wurman. The application utilizes Esri's ArcGIS API for JavaScript. Once a web map is created, it is added to a group and tagged to indicated its city and subject information. Those tags are read by the application as it starts up in the browser.

  16. Visualize 2045: Constrained Element, 2022 update (Data Download)

    • hub.arcgis.com
    • rtdc-mwcog.opendata.arcgis.com
    Updated Feb 14, 2023
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    Metropolitan Washington Council of Governments (2023). Visualize 2045: Constrained Element, 2022 update (Data Download) [Dataset]. https://hub.arcgis.com/datasets/e4787295a965416ab9c2cef43441a0fc
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    Dataset updated
    Feb 14, 2023
    Dataset authored and provided by
    Metropolitan Washington Council of Governmentshttp://www.mwcog.org/
    Description

    The financially constrained element of Visualize 2045 identifies all the regionally significant capital improvements to the region’s highway and transit systems that transportation agencies expect to make and to be able to afford through 2045.For more information on Visualize 2045, visit https://www.mwcog.org/visualize2045/.To view the web map, visit https://www.mwcog.org/maps/map-listing/visualize-2045-project-map/.Download the ZIP file that contains a File Geodatabase

  17. a

    Ontario Road Network (ORN) Road Net Element

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +2more
    Updated Jan 1, 2001
    + more versions
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    Ontario Ministry of Natural Resources and Forestry (2001). Ontario Road Network (ORN) Road Net Element [Dataset]. https://hub.arcgis.com/datasets/2fd52bccdb77479da0133c86545503f8
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    Dataset updated
    Jan 1, 2001
    Dataset authored and provided by
    Ontario Ministry of Natural Resources and Forestry
    Area covered
    Description

    The ORN is a provincewide geographic database of over 250,000 kilometres of municipal roads, provincial highways, and resource and recreational roads. The ORN is the source of roads data for the Government of Ontario. Road names in the ORN are the official names provided by the authoritative jurisdiction for each road segment, such as a municipality or the Ontario Government. You can also find the authoritative jurisdiction for a specific road feature in the Jurisdiction table in ORN Road Net Element. ORN Road Net Element requires an advanced knowledge of GIS including LRS and complex table relationships. This dataset contains the following related tables:official street namealternate street nameaddress informationroad classificationnumber of lanesroad surfacespeed limitstructuretoll pointblocked passageroute nameroute numberjurisdictionsourceunderpassjunction The ORN contains information licensed from the parties listed in in the “Ontario Road Network – Licenced Sources” document in the Additional Documentation section below. Additional Documentation Ontario Road Network - Road Net Element - User Guide (Word)Data Capture Specifications for Road Net Elements - Guide to Best Practices for Acquisition (Word)GO-ITS 29 - Ontario Road Network StandardOntario Road Network - Licensed Sources (Word) Status On going: data is being continually updated Maintenance and Update Frequency Weekly: data is updated on a weekly basis Contact Ontario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

  18. VT Rare, Threatened and Endangered Species (Public)

    • hub.arcgis.com
    • anrgeodata.vermont.gov
    • +2more
    Updated Sep 23, 2022
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    Vermont Agency of Natural Resources (2022). VT Rare, Threatened and Endangered Species (Public) [Dataset]. https://hub.arcgis.com/datasets/1d7ed0d93a05473d8a34c831200f378c
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    Dataset updated
    Sep 23, 2022
    Dataset provided by
    Vermont Agency Of Natural Resourceshttp://www.anr.state.vt.us/
    Authors
    Vermont Agency of Natural Resources
    Area covered
    Description

    The Vermont Fish and Wildlife Department's Natural Heritage Inventory (NHI) maintains a database of rare, threatened and endangered species and natural (plant) communities in Vermont. The Department is a member of the network of Natural Heritage Programs and Conservation Data Centres network that collaborates with NatureServe, which is the umbrella organization. The Element Occurrence (EO) records that form the core of the Natural Heritage Inventory database include information on the location, status, characteristics, numbers, condition, and distribution of elements of biological diversity using established Natural Heritage Methodology developed by NatureServe and The Nature Conservancy. An Element Occurrence (EO) is an area of land and/or water in which a species or natural community is, or was, present. An EO should have practical conservation value for the Element as evidenced by potential continued (or historical) presence and/or regular recurrence at a given location. For species Elements, the EO often corresponds with the local population, but when appropriate may be a portion of a population or a group of nearby populations (e.g., metapopulation). For community Elements, the EO may represent a stand or patch of a natural community, or a cluster of stands or patches of a natural community. Because they are defined on the basis of biological information, EOs may cross jurisdictional boundaries. An Element Occurrence record is a data management tool that has both spatial and tabular components including a mappable feature and its supporting database. EOs are typically represented by bounded, mapped areas of land and/or water or, at small scales, the centroid point of this area. EO records are most commonly created for current or historically known occurrences of natural communities or native species of conservation interest.

  19. a

    Housing Element Open Data Project and SB 35 Determination

    • hub.arcgis.com
    • data.ca.gov
    • +1more
    Updated Apr 27, 2018
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    Housing and Community Development (2018). Housing Element Open Data Project and SB 35 Determination [Dataset]. https://hub.arcgis.com/maps/64a819d37c414e78bd4ca31d762eb88c
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    Dataset updated
    Apr 27, 2018
    Dataset authored and provided by
    Housing and Community Development
    Area covered
    Description

    Shows SB 35 determination status for cities and counties throughout the state, based on data reported on the annual progress report (APR).SB 35 (Wiener) Streamline Approval Process Opt-in program for developersFinal Streamlined Ministerial Approval Process Guidelines (PDF)Creates a streamlined approval process for developments in localities that have not yet met their housing targets, provided that the development is on an infill site and complies with existing residential and mixed use zoning. Participating developments must provide at least 10 percent of units for lower-income families. All projects over 10 units must be prevailing wage and larger projects must provide skilled and trained labor.For more information, visit the Annual Progress Reports on HCD's website.

  20. a

    i08 C2VSimFG Elements

    • hub.arcgis.com
    • data.cnra.ca.gov
    • +7more
    Updated Feb 7, 2023
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    Carlos.Lewis@water.ca.gov_DWR (2023). i08 C2VSimFG Elements [Dataset]. https://hub.arcgis.com/datasets/92cbcc969da942cd98c9be40221c08da
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    Dataset updated
    Feb 7, 2023
    Dataset authored and provided by
    Carlos.Lewis@water.ca.gov_DWR
    Area covered
    Description

    There is a total of 32, 537 elements within the C2VSimFG model, which make-up the finite grid mesh of the model. The elements are subdivided into 21 subregions. Each element is composed of corresponding groundwater nodes within the model domain. The model domain area is 20, 742 square miles, and each element is roughly 407 acres. The boundaries of the model grid were developed using a set of control points at important locations of the model area. The finite element mesh was created using GIS and several Excel and FORTRAN utilities. The grid size was refined in areas of higher groundwater gradient and/or areas that are more critical from hydrogeological viewpoints. The grid lines are designed parallel to the streamflow direction, when possible, as well as the groundwater streamlines, to capture the surface and subsurface drainage patterns. Nine major faults in the Central Valley are represented by thin strip of elements of around 500 feet. The dataset excludes three geologic outcrops: Sutter Buttes, Kettleman Hills and Capay Valley Hills, which are areas not included in the Bulletin 118. The dataset is maintained by the Sustainable Groundwater Management Office, Modeling and Tools Support Section. The areas calculated for this data using the WGS 1984 Web Mercator projection may not reflect the actual areas used in the C2VSimFG model.

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NCGE (2020). ArcGIS for Coders: Learn the Javascript API [Dataset]. https://library.ncge.org/documents/672aee2ab8954e218ce07cb53c88e65f

ArcGIS for Coders: Learn the Javascript API

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Dataset updated
Jun 8, 2020
Dataset authored and provided by
NCGE
Description

The ArcGIS Javascript API lets developers build GIS web applications. The Javascript API is one of many that could be used but it's a great starting place. Students may also be interested in the Python API or others!

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