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
This resource was created by Esri Canada Education and Research. To browse our full collection of higher-education learning resources, please visit https://hed.esri.ca/resourcefinder/.This tutorial introduces you to using Python code in a Jupyter Notebook, an open source web application that enables you to create and share documents that contain rich text, equations and multimedia, alongside executable code and visualization of analysis outputs. The tutorial begins by stepping through the basics of setting up and being productive with Python notebooks. You will be introduced to ArcGIS Notebooks, which are Python Notebooks that are well-integrated within the ArcGIS platform. Finally, you will be guided through a series of ArcGIS Notebooks that illustrate how to create compelling notebooks for data science that integrate your own Python scripts using the ArcGIS API for Python and ArcPy in combination with thousands of open source Python libraries to enhance your analysis and visualization.To download the dataset Labs, click the Open button to the top right. This will automatically download a ZIP file containing all files and data required.You can also clone the tutorial documents and datasets for this GitHub repo: https://github.com/highered-esricanada/arcgis-notebooks-tutorial.git.Software & Solutions Used: Required: This tutorial was last tested on August 27th, 2024, using ArcGIS Pro 3.3. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.Recommended: ArcGIS Online subscription account with permissions to use advanced Notebooks and GeoEnrichmentOptional: Notebook Server for ArcGIS Enterprise 11.3+Time to Complete: 2 h (excludes processing time)File Size: 196 MBDate Created: January 2022Last Updated: August 27, 2024
The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making.
BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions.
Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself.
For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise.
Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer.
This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery.
See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt
See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt
Detroit Street View (DSV) is an urban remote sensing program run by the Enterprise Geographic Information Systems (EGIS) Team within the Department of Innovation and Technology at the City of Detroit. The mission of Detroit Street View is ‘To continuously observe and document Detroit’s changing physical environment through remote sensing, resulting in freely available foundational data that empowers effective city operations, informed decision making, awareness, and innovation.’ LiDAR (as well as panoramic imagery) is collected using a vehicle-mounted mobile mapping system.
Due to variations in processing, index lines are not currently available for all existing LiDAR datasets, including all data collected before September 2020. Index lines represent the approximate path of the vehicle within the time extent of the given LiDAR file. The actual geographic extent of the LiDAR point cloud varies dependent on line-of-sight.
Compressed (LAZ format) point cloud files may be requested by emailing gis@detroitmi.gov with a description of the desired geographic area, any specific dates/file names, and an explanation of interest and/or intended use. Requests will be filled at the discretion and availability of the Enterprise GIS Team. Deliverable file size limitations may apply and requestors may be asked to provide their own online location or physical media for transfer.
LiDAR was collected using an uncalibrated Trimble MX2 mobile mapping system. The data is not quality controlled, and no accuracy assessment is provided or implied. Results are known to vary significantly. Users should exercise caution and conduct their own comprehensive suitability assessments before requesting and applying this data.
Sample Dataset: https://detroitmi.maps.arcgis.com/home/item.html?id=69853441d944442f9e79199b57f26fe3
Location of underground storm drains in the City of Tucson. The data provided here was pulled from drawings and plans submitted to the Tucson Department of Transportation.PurposeThis layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Dataset ClassificationLevel 0 - OpenKnown UsesLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Update FrequencyLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Stormwater models consist of a set of nodes that are combined to simulate the behavior of the entire system. Each node represents a hydrograph operation, such as generating runoff from a subcatchment or routing the hydrograph through a reach or pond. The individual nodes are interconnected, specifying how the hydrographs are routed from one node to another.PurposeThis layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Dataset ClassificationLevel 0 - OpenKnown UsesLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Update FrequencyNot updated since 2009
Roads that are a part of the Major Streets and Routes layer designated as scenic.PurposeThis layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Dataset ClassificationLevel 0 - OpenKnown UsesLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Update FrequencyLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
ArcGIS Enterprise puts collaboration and flexibility at the center of your organization's GIS. It pairs industry-leading mapping and analytics capabilities with a dedicated Web GIS infrastructure to organize and share your work on any device, anywhere, at any time.
The dataset includes approximate flood-hazard boundary areas prepared by both detailed and approximate methods. Study limits were defined using the highlighted drainage-problem areas shown on the city's zoning base maps as a guide. Floodplain studies completed and sealed in 2007 and 2008 . Shape files created April 2011. Shape files exported from Autodesk Map 3D 2006 and projected using ArcMap 10.Maintenance and frequency to be determined by City of Tucson, Planning and Development Services.Usage: This layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.
The dataset includes approximate flood-hazard boundary areas prepared by both detailed and approximate methods. Study limits were defined using the highlighted drainage-problem areas shown on the city's zoning base maps as a guide. Floodplain studies completed and sealed in 2007 and 2008. The highlighted drainage problem areas shown on the city's zoning base maps did not distinguish between FEMA flood plains and problem areas approximated either from drainage complaints or from information included in subdivision/development drainage studies.PurposeLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Dataset ClassificationLevel 0 - OpenKnown UsesThis layer is intended to be used in the City of Tucson's Open Data portal and not for regular use in ArcGIS Online, ArcGIS Enterprise or other web applications.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Update FrequencyLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!
COMPLETED 2010. The data was converted from the most recent (2010) versions of the adopted plans, which can be found at https://cms3.tucsonaz.gov/planning/plans/ Supplemental Information: In March 2010, Pima Association of Governments (PAG), in cooperation with the City of Tucson (City), initiated the Planned Land Use Data Conversion Project. This 9-month effort involved evaluating mapped land use designations and selected spatially explicit policies for nearly 50 of the City's adopted neighborhood, area, and subregional plans and converting the information into a Geographic Information System (GIS) format. Further documentation for this file can be obtained from the City of Tucson Planning and Development Services Department or Pima Association of Governments Technical Services. A brief summary report was provided, as requested, to the City of Tucson which highlights some of the key issues found during the conversion process (e.g., lack of mapping and terminology consistency among plans). The feature class "Plan_boundaries" represents the boundaries of the adopted plans. The feature class "Plan_mapped_land_use" represents the land use designations as they are mapped in the adopted plans. Some information was gathered that is implicit based on the land use designation or zones (see field descriptions below). Since this information is not explicitly stated in the plans, it should only be viewed by City staff for general planning purposes. The feature class "Plan_selected_policies" represents the spatially explicit policies that were fairly straightforward to map. Since these policies are not represented in adopted maps, this feature class should only be viewed by City staff for general planning purposes only. 2010 - created by Jamison Brown, working as an independent contractor for Pima Association of Governments, created this file in 2010 by digitizing boundaries as depicted (i.e. for the mapped land use) or described in the plans (i.e. for the narrative policies). In most cases, this involved tracing based on parcel (paregion) or street center line (stnetall) feature classes. Snapping was used to provide line coincidence. For some map conversions, freehand sketches were drawn to mimick the freehand sketches in the adopted plan. Field descriptions Field descriptions for the "Plan_boundaries" feature class: Plan_Name: Plan name Plan_Type: Plan type (e.g., Neighborhood Plan) Plan_Num: Plan number ADOPT_DATE: Date of Plan adoption IMPORTANT: A disclaimer about the data as it is unofficial. URL: Uniform Resource Locator Field descriptions for the "Plan_mapped_land_use" feature class: Plan_Name: Plan name Plan_Type: Plan type (e.g., Neighborhood Plan) Plan_Num: Plan number LU_DES: Land use designation (e.g., Low density residential) LISTED_ALLOWABLE_ZONES: Allowable zones as listed in the Plan LISTED_RAC_MIN: Minimum residences per acre (if applicable), as listed in the Plan LISTED_RAC_TARGET: Target residences per acre (if applicable), as listed in the Plan LISTED_RAC_MAX: Maximum residences per acre (if applicable), as listed in the Plan LISTED_FAR_MIN: Minimum Floor Area Ratio (if applicable), as listed in the Plan LISTED_FAR_TARGET: Target Floor Area Ratio (if applicable), as listed in the Plan LISTED_FAR_MAX: Maximum Floor Area Ratio (if applicable), as listed in the Plan BUILDING_HEIGHT_MAX Building height maximum (ft.) if determined by Plan policy IMPORTANT: A disclaimer about the data as it is unofficial. URL: Uniform Resource Locator IMPLIED_ALLOWABLE_ZONES: Implied (not listed in the Plan) allowable zones IMPLIED_RAC_MIN: Implied (not listed in the Plan) minimum residences per acre (if applicable) IMPLIED_RAC_TARGET: Implied (not listed in the Plan) target residences per acre (if applicable) IMPLIED_RAC_MAX: Implied (not listed in the Plan) maximum residences per acre (if applicable) IMPLIED_FAR_MIN: Implied (not listed in the Plan) minimum Floor Area Ratio (if applicable) IMPLIED_FAR_TARGET: Implied (not listed in the Plan) target Floor Area Ratio (if applicable) IMPLIED_FAR_MAX: Implied (not listed in the Plan) maximum Floor Area Ratio (if applicable) IMPLIED_LU_CATEGORY: Implied (not listed in the Plan) general land use category. General categories used include residential, office, commercial, industrial, and other.PurposeLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Dataset ClassificationLevel 0 - OpenKnown UsesThis layer is intended to be used in the City of Tucson's Open Data portal and not for regular use in ArcGIS Online, ArcGIS Enterprise or other web applications.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactJohn BeallCity of Tucson Development Services520-791-5550John.Beall@tucsonaz.govUpdate FrequencyLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Civic Events affecting traffic in the City of Tucson.Usage: This layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Link to Open Data item: https://gisdata.tucsonaz.gov/datasets/civic-events-open-data
WebLogis, Loudoun County's Online Mapping System. Provides access to the County’s Enterprise Geographic Information System data layers.
Combination of 2 layers which were all made by Frank Sousa (WASHERZ which showed the existing alignments that are both WASH and ERZ became unnecessary)WASH_ORD shows the existing WASH alignmentsWASH_ERZ shows the existing ERZ alignments Dan Bursuck combined data in May 2015 and added fields: wash_type, status and visible (segments outside of City Limits don't show - visible=no - but are retained because they are part of Frank's original dataPurposeThis layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Dataset ClassificationLevel 0 - OpenKnown UsesLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Update FrequencyNot Maintained
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Lorem ipsum dolor sit amet consectetur adipiscing elit. Massa enim nec dui nunc. Quis commodo odio aenean sed adipiscing diam donec adipiscing. Nulla pellentesque dignissim enim sit amet venenatis urna. Sit amet volutpat consequat mauris nunc congue nisi vitae. Fames ac turpis egestas maecenas pharetra convallis posuere morbi leo. Morbi tristique senectus et netus et malesuada fames ac turpis. Eget lorem dolor sed viverra ipsum nunc. Id ornare arcu odio ut sem. Morbi leo urna molestie at elementum eu. In metus vulputate eu scelerisque. Lobortis mattis aliquam faucibus purus in massa tempor nec feugiat. Ut sem viverra aliquet eget sit amet tellus cras adipiscing. Lobortis mattis aliquam faucibus purus in massa tempor. Donec massa sapien faucibus et molestie ac feugiat. Et odio pellentesque diam volutpat commodo sed egestas egestas. Pharetra magna ac placerat vestibulum lectus. Fermentum leo vel orci porta non pulvinar neque laoreet suspendisse.PurposeThis layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Dataset ClassificationLevel 0 - OpenKnown UsesLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactJohn ZukasDept of Transportation and Mobility520-837-6762john.zukas@tucsonaz.govUpdate FrequencyUpdates only required when Service Area expands or contracts.
CHANGE NOTICE: Effective June 3, 2021 DataBC has updated the service urls for all public BC Geographic Warehouse (BCGW) feature layer items in ArcGIS Online (INCLUDING THIS ITEM!). This will require ACTION on the part of all ArcGIS Online web map authors to update any references to this layer's service url in their ArcGIS Online web maps or web applications. To avoid errors, updates must be done prior to November 30, 2021. For more information please visit: https://www2.gov.bc.ca/gov/content/data/geographic-data-services/web-based-mapping/agolPurpose: The primary use of this data is to provide information about Indigenous Owned Businesses identified at specific civic address locations in B.C. Notes: The BC Indigenous Business Listings dataset offers a brief summary of Indigenous businesses operating in the province. For each business listed in the dataset, information including the Indigenous owner(s) of the company, location, links to websites as well as primary contact information including email addresses and phone numbers is provided where available. This information is intended to facilitate connections between business owners and consumers, investors, and industry. It is also meant to support an understanding of ownership trends among Indigenous businesses.
To add or update your Indigenous-owned business, please visit the BC Indigenous Business & Investment Council. Table Comments: GSR_INDIGENOUS_BUSINESSES_SV is a spatially enabled layer comprising a brief summary of INDIGENOUS Businesses operating in the province. For each business listed in the dataset, information including the INDIGENOUS owner(s) of the company, location, links to websites as well as primary contact information including email addresses and phone numbers is provided where available. This information is intended to facilitate connections between business owners and consumers, investors, and industry. It is also meant to support an understanding of ownership trends among INDIGENOUS businesses.WMS GetCapabilities URL: DataBC also offers access to this data in OGC WMS format. WMS is useful when the map author does not require custom popups, styling, or analytic capabilities for the layer. ArcGIS Online authors may want to use WMS, instead of this ArcGIS Server layer, in the following scenarios: Where they want to use existing Data Custodian approved styling, and/or They only need simple identify and map rendering functionality.Copy the: WMS GetCapabilities URL to add this web item to an ArcGIS Online Map or Scene Viewer. In some cases, multiple Styles are listed in the GetCapabilities and can be added as WMS Custom parameters. For more information on how to use a WMS layer see - ESRI's OGC ArcGIS Online HelpBC Data Catalogue Metadata URL: https://catalogue.data.gov.bc.ca/dataset/bdc81d33-1ab5-4882-9764-8701e8971bb7
This map displays projected visible surface smoke across the contiguous United States for the next 48 hours in 1 hour increments. It is updated every 24 hours by NWS. Concentrations are reported in micrograms per cubic meter.Where is the data coming from?The National Digital Guidance Database (NDGD) is a sister to the National Digital Forecast Database (NDFD). Information in NDGD may be used by NWS forecasters as guidance in preparing official NWS forecasts in NDFD. The experimental/guidance NDGD data is not an official NWS forecast product.Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndgd/GT.aq/AR.conus/ds.smokes01.binSource data archive can be found here: https://www.ncei.noaa.gov/products/weather-climate-models/national-digital-guidance-database look for 'LXQ...' files by date. These are the Binary GRIB2 files that can be decoded via DeGRIB tool.Where can I find other NDGD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.RevisionsJuly 11, 2022: Feed updated to leverage forecast model change by NOAA, whereby the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) forecast model system was replaced with the Rapid Refresh (RAP) forecast model system. Key differences: higher accuracy with RAP now concentrated at 0-8 meter detail vs HYSPLIT at 0-100 meter; earlier data delivery by 6 hrs; forecast output extended to 51 hrs.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!
This map displays the predicted ice accumulation for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database (NDFD) produced by the National Weather Service. The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.iceaccum.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
A listing of current business licenses in the City of Alpharetta. Most items in this dataset are associated with a spatial location and can be plotted in GIS software, however some features may not be tied to a location, and therefore may appear to plot outside of the Alpharetta city limits.Important: If you are downloading a dataset from https://open-alpharetta.opendata.arcgis.com, please disregard the Updated, Created, and Published dates on the web page. Most datasets are refreshed nightly. At times, however, the website may provide you with an older cached copy of the data. To ensure you are downloading the most current dataset, we recommend using the "Request new file" option that may appear after you have downloaded a stale dataset.
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
The USGS National Hydrography Dataset (NHD) downloadable data collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. For additional information on NHD, go to https://www.usgs.gov/core-science-systems/ngp/national-hydrography.
DWR was the steward for NHD and Watershed Boundary Dataset (WBD) in California. We worked with other organizations to edit and improve NHD and WBD, using the business rules for California. California's NHD improvements were sent to USGS for incorporation into the national database. The most up-to-date products are accessible from the USGS website. Please note that the California portion of the National Hydrography Dataset is appropriate for use at the 1:24,000 scale.
For additional derivative products and resources, including the major features in geopackage format, please go to this page: https://data.cnra.ca.gov/dataset/nhd-major-features Archives of previous statewide extracts of the NHD going back to 2018 may be found at https://data.cnra.ca.gov/dataset/nhd-archive.
In September 2022, USGS officially notified DWR that the NHD would become static as USGS resources will be devoted to the transition to the new 3D Hydrography Program (3DHP). 3DHP will consist of LiDAR-derived hydrography at a higher resolution than NHD. Upon completion, 3DHP data will be easier to maintain, based on a modern data model and architecture, and better meet the requirements of users that were documented in the Hydrography Requirements and Benefits Study (2016). The initial releases of 3DHP include NHD data cross-walked into the 3DHP data model. It will take several years for the 3DHP to be built out for California. Please refer to the resources on this page for more information.
The FINAL,STATIC version of the National Hydrography Dataset for California was published for download by USGS on December 27, 2023. This dataset can no longer be edited by the state stewards. The next generation of national hydrography data is the USGS 3D Hydrography Program (3DHP).
Questions about the California stewardship of these datasets may be directed to nhd_stewardship@water.ca.gov.
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
This resource was created by Esri Canada Education and Research. To browse our full collection of higher-education learning resources, please visit https://hed.esri.ca/resourcefinder/.This tutorial introduces you to using Python code in a Jupyter Notebook, an open source web application that enables you to create and share documents that contain rich text, equations and multimedia, alongside executable code and visualization of analysis outputs. The tutorial begins by stepping through the basics of setting up and being productive with Python notebooks. You will be introduced to ArcGIS Notebooks, which are Python Notebooks that are well-integrated within the ArcGIS platform. Finally, you will be guided through a series of ArcGIS Notebooks that illustrate how to create compelling notebooks for data science that integrate your own Python scripts using the ArcGIS API for Python and ArcPy in combination with thousands of open source Python libraries to enhance your analysis and visualization.To download the dataset Labs, click the Open button to the top right. This will automatically download a ZIP file containing all files and data required.You can also clone the tutorial documents and datasets for this GitHub repo: https://github.com/highered-esricanada/arcgis-notebooks-tutorial.git.Software & Solutions Used: Required: This tutorial was last tested on August 27th, 2024, using ArcGIS Pro 3.3. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.Recommended: ArcGIS Online subscription account with permissions to use advanced Notebooks and GeoEnrichmentOptional: Notebook Server for ArcGIS Enterprise 11.3+Time to Complete: 2 h (excludes processing time)File Size: 196 MBDate Created: January 2022Last Updated: August 27, 2024