Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
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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 Spatiotemporal Big Data Store Tutorial introduces you the the capabilities of the spatiotemporal big data store in ArcGIS Data Store, available with ArcGIS Enterprise. Observation data can be moving objects, changing attributes of stationary sensors, or both. The spatiotemporal big data store enables archival of high volume observation data, sustains high velocity write throughput, and can run across multiple machines (nodes). Adding additional machines adds capacity, enabling you to store more data, implement longer retention policies of your data, and support higher data write throughput.
After completing this tutorial you will:
Understand the concepts and best practices for working with the spatiotemporal big data store available with ArcGIS Data Store. Have configured the appropriate security settings and certificates on a enterprise server, real-time server, and a data server which are necessary for working with the spatiotemporal big data store. Have learned how to process and archive large amounts of observational data in the spatiotemporal big data store. Have learned how to visualize the observational data that is stored in the spatiotemporal big data store.
Releases
Each release contains a tutorial compatible with the version of GeoEvent Server listed. The release of the component you deploy does not have to match your version of ArcGIS GeoEvent Server, so long as the release of the component is compatible with the version of GeoEvent Server you are using. For example, if the release contains a tutorial for version 10.6; this tutorial is compatible with ArcGIS GeoEvent Server 10.6 and later. Each release contains a Release History document with a compatibility table that illustrates which versions of ArcGIS GeoEvent Server the component is compatible with.
NOTE: The release strategy for ArcGIS GeoEvent Server components delivered in the ArcGIS GeoEvent Server Gallery has been updated. Going forward, a new release will only be created when
a component has an issue,
is being enhanced with new capabilities,
or is not compatible with newer versions of ArcGIS GeoEvent Server.
This strategy makes upgrades of these custom
components easier since you will not have to
upgrade them for every version of ArcGIS GeoEvent Server
unless there is a new release of
the component. The documentation for the
latest release has been
updated and includes instructions for updating
your configuration to align with this strategy.
Latest
Release 4 - February 2, 2017 - Compatible with ArcGIS GeoEvent Server 10.5 and later.
Previous
Release 3 - July 7, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 2 - May 17, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 1 - March 18, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Points to ArcGIS Server Map Service, which is updated weekly from the Enterprise geodatabase.
Geoportal Server is a standards-based, open source product that enables discovery and use of geospatial resources including data and services.
With the Geoportal Server you can:
Time Aware is a configurable app template that enables you visualize time enabled layers in a web map using a time slider. This is useful for displaying changes in data over time. Use CasesBuild a stand alone app that presents data changing through time.Build a time aware app and embed it within a story map journal or story map series to include time animation within your story.Configurable OptionsChoose a title, logo, and color scheme.Configure the ability for feature and location search.Customize the color and date time format of the time slider.Enable a legend, scalebar, share dialog, or about window.Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis requires time aware data, to learn more see the configure time help topic. An existing time aware feature service can be consumed from this application, however in order to create your own time aware feature service you will either need ArcGIS Enterprise or an ArcGIS Online subscription.Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the digital vector boundaries for Local Enterprise Partnerships, in England, as at December 2022.The boundaries available are: (BUC) Ultra generalised (500m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.
REST URL of Feature Server – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Local_Enterprise_Partnerships_December_2022_EN_BUC/FeatureServerREST URL of WFS Server –https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Local_Enterprise_Partnerships_December_2022_EN_BUC/WFSServer?service=wfs&request=getcapabilitiesREST URL of Map Server –https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Local_Enterprise_Partnerships_December_2022_EN_BUC/MapServer
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the digital vector boundaries for Local Enterprise Partnerships, in England, as at December 2022.The boundaries available are: (BFC) Full resolution - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights. Version 2 - To account for name changes. E37000011 Gloucestershire changed its name to GFirst on the 31st December 2022E37000045 Derby, Derbyshire, Nottingham and Nottinghamshire has changed its name to D2N2 on the 31st December 2022E37000051 London has changed it’s name to The London Economic Action Partnership on the 31st December 2022E37000053 Oxfordshire has changed it’s name to OxLEP on the 31st December 2022E37000054 Sheffield City Region has changed it’s name to South Yorkshire on the 1st December 2022E37000059 Greater Cambridge and Greater Peterborough has changed it’s name to The Business Board on the 31st December 2022REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BFC_V2/FeatureServer
REST URL of WFS Server – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Local_Enterprise_Partnerships_December_2022_EN_BFC/WFSServer?service=wfs&request=getcapabilities REST URL of Map Server – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Local_Enterprise_Partnerships_December_2022_EN_BFC_Tile/MapServer
An address point represents a geographic location that has been assigned an address by the local address authority (i.e., county or municipality) but does not necessarily receive mail from the US Postal Service (USPS). Address points may include several pieces of information about the structure or location that’s being mapped, such as:[WHOLE_ADDRESS] the full address (i.e., the USPS mailing address, if the address is for a physical location [rather than a PO box]);the type of unit [UNIT_TYPE] and unit [UNIT];the city or zip community [POST_COMM] and ZIP code POST_CODE;the vacancy status (occupied, vacant, meter) [OccupiedUseStatus]; andthe date that the address point was created [DATE_CREATED] and last edited [DATE_MODIFIED].These data were originally created for Public Safety e911 response in 2001 through field survey by county staff and is mapping grade. Today it is used throughout the County and by the public to conduct business and assist in decision making. This feature service is updated daily from its source ArcGIS Enterprise feature class. Source data within an Enterprise Geodatabase is accessed by County and City of Rock Hill staff through ArcGIS Server and Portal. When edited, business rules are enforced by BCS theAddresser software. York County has an Address Manual used by staff and stakeholders to ensure quality and standards are adhered to during maintenance and use.These data are shared through open data and available for download. York County addresses are included in the National Address Database (USDOT NAD). The NAD is consumed by Google as highlighted in their Maps Content Partners 2022 November Newsletter. York County is one of 13 counties added in 2022. Access the NAD through the ArcGIS Online Living Atlas.As of October 2022, the schema of these data are compatible with NG911. Previous schema remains as of January 2023 with intent to remove fields tentatively planned for 2024. Review the schema field mapping document (PDF) to gain a better understanding of field mapping used to transition these data to NG911 standards.
https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy
The Italian geospatial analytics market, valued at €260 million in 2025, is poised for robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 8.17% from 2025 to 2033. This expansion is driven by increasing adoption of precision agriculture techniques, the burgeoning need for efficient infrastructure management within utilities and communication sectors, and rising demand for advanced analytics in defense and intelligence applications. Furthermore, the Italian government's focus on smart city initiatives and the expanding digitalization across various sectors, including healthcare and real estate, significantly contribute to market growth. The market segmentation reveals a strong demand across diverse verticals, with agriculture, utilities, and defense exhibiting substantial growth potential. The prevalent use of surface analysis techniques reflects a focus on immediate application needs, while the growing adoption of network and geo-visualization analytics indicates a shift toward more sophisticated and insightful data interpretation. Leading players such as ESRI, Hexagon AB, and Trimble Geospatial are actively contributing to market development by providing cutting-edge software and services. Competition is likely to intensify as smaller, specialized companies emerge, offering niche solutions and catering to the evolving demands of different market segments. The forecast period (2025-2033) anticipates substantial market expansion, largely attributed to continued technological advancements, particularly in AI and machine learning, enhancing the analytical capabilities of geospatial data. However, challenges exist, potentially including data security concerns, the need for skilled professionals to interpret complex analytical results, and the high initial investment required for advanced geospatial technology implementation. Nevertheless, the long-term outlook for the Italian geospatial analytics market remains positive, driven by sustained government investment in digital infrastructure and the increasing awareness of the value proposition offered by sophisticated geospatial analysis across various sectors. The market's trajectory suggests a significant opportunity for both established and emerging players in the years to come. Recent developments include: March 2023: The Italian space agency and NASA have collaborated to build and launch the Multi-Angle Imager for Aerosols mission, an effort to investigate the health impacts of tiny airborne particles polluting the cities through analyzing data by collecting data from the satellite-based observatories, which would fuel the demand for geospatial analytics market in the country., January 2023: EDB, an open-source database service provider in Italy, announced its partnership with Esri to certify EDB Postgres Advanced Server with Esri ArcGIS Pro and Esri ArcGIS Enterprise, which work together to form Esri's Geospatial analytic solutions, operating in many countries, including Italy. After this partnership, users can connect their EDB Postgres Advanced Server to explore, visualize and analyze their geospatial data and share their work with an Esri ArcGIS Enterprise portal. In addition, EDB customers, especially those in the public sector, can use their database with Esri ArcGIS software to transform their data into something that improves workflows and processes and shapes policies and engagement within their communities.. Key drivers for this market are: Increase in the number of Smart Cities in The Country, The Implementation of analytics Software in the Country's Public Transportation. Potential restraints include: Increase in the number of Smart Cities in The Country, The Implementation of analytics Software in the Country's Public Transportation. Notable trends are: The Increase in the Number of Smart Cities in The Country Fuels the Market Growth.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The boundaries available are: (BGC) Generalised (20m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights. Version 2 - To account for name changes. E37000011 Gloucestershire changed its name to GFirst on the 31st December 2022E37000045 Derby, Derbyshire, Nottingham and Nottinghamshire has changed its name to D2N2 on the 31st December 2022E37000051 London has changed it’s name to The London Economic Action Partnership on the 31st December 2022E37000053 Oxfordshire has changed it’s name to OxLEP on the 31st December 2022E37000054 Sheffield City Region has changed it’s name to South Yorkshire on the 1st December 2022E37000059 Greater Cambridge and Greater Peterborough has changed it’s name to The Business Board on the 31st December 2022 REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BGC_V2/FeatureServer REST URL of WFS Server – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/LEP_DEC_2022_EN_BGC_V2/WFSServer?service=wfs&request=getcapabilities REST URL of Map Server – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BGC_V2/MapServer
NIWA's bathymetry model of New Zealand at a 250m resolution. The 2016 model is a compilation of data digitised from published coastal charts, digital soundings archive, navy collector sheets and digital multibeam data sourced from surveys by NIWA, LINZ, as well as international surveys by vessels from United States of America, France, Germany, Australia, and Japan. All data used is held at NIWA.Image service can be used for analysis in ArcGIS Desktop or ArcGIS Online - no need to download the data, just stream using this service and classify, symbolise, mask, extract or apply map algebra - just like you would with local raster files. https://enterprise.arcgis.com/en/server/latest/publish-services/windows/key-concepts-for-image-services.htmMap information and metadata Offshore representation was generated from digital bathymetry at a grid resolution of 250m. Sun illumination is from an azimuth of 315° and 45° above the horizon.Projection Mercator 41 (WGS84 datum). EPSG: 3994Scale 1:5,000,000 at 41°S. Not to be used for navigational purposes Bibliographic reference Mitchell, J.S., Mackay, K.A., Neil, H.L., Mackay, E.J., Pallentin, A., Notman P., 2012. Undersea New Zealand, 1:5,000,000. NIWA Chart, Miscellaneous Series No. 92Further Information: https://www.niwa.co.nz/our-science/oceans/bathymetry/further-informationLicence: https://www.niwa.co.nz/environmental-information/licences/niwa-open-data-licence-by-nn-nc-sa-version-1_Item Page Created: 2017-11-01 00:55 Item Page Last Modified: 2025-04-05 18:48Owner: NIWA_OpenData
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the digital vector boundaries for Local Enterprise Partnerships, in England, as at December 2022.The boundaries available are: (BGC) Generalised (20m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights. Version 2 - To account for name changes. E37000011 Gloucestershire changed its name to GFirst on the 31st December 2022E37000045 Derby, Derbyshire, Nottingham and Nottinghamshire has changed its name to D2N2 on the 31st December 2022E37000051 London has changed it’s name to The London Economic Action Partnership on the 31st December 2022E37000053 Oxfordshire has changed it’s name to OxLEP on the 31st December 2022E37000054 Sheffield City Region has changed it’s name to South Yorkshire on the 1st December 2022E37000059 Greater Cambridge and Greater Peterborough has changed it’s name to The Business Board on the 31st December 2022
REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BGC_V2/FeatureServer
REST URL of WFS Server – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/LEP_DEC_2022_EN_BGC_V2/WFSServer?service=wfs&request=getcapabilities
REST URL of Map Server – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BGC_V2/MapServer
Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
License information was derived automatically
Learn state-of-the-art skills to build compelling, useful, and fun Web GIS apps easily, with no programming experience required.Building on the foundation of the previous three editions, Getting to Know Web GIS, fourth edition,features the latest advances in Esri’s entire Web GIS platform, from the cloud server side to the client side.Discover and apply what’s new in ArcGIS Online, ArcGIS Enterprise, Map Viewer, Esri StoryMaps, Web AppBuilder, ArcGIS Survey123, and more.Learn about recent Web GIS products such as ArcGIS Experience Builder, ArcGIS Indoors, and ArcGIS QuickCapture. Understand updates in mobile GIS such as ArcGIS Collector and AuGeo, and then build your own web apps.Further your knowledge and skills with detailed sections and chapters on ArcGIS Dashboards, ArcGIS Analytics for the Internet of Things, online spatial analysis, image services, 3D web scenes, ArcGIS API for JavaScript, and best practices in Web GIS.Each chapter is written for immediate productivity with a good balance of principles and hands-on exercises and includes:A conceptual discussion section to give you the big picture and principles,A detailed tutorial section with step-by-step instructions,A Q/A section to answer common questions,An assignment section to reinforce your comprehension, andA list of resources with more information.Ideal for classroom lab work and on-the-job training for GIS students, instructors, GIS analysts, managers, web developers, and other professionals, Getting to Know Web GIS, fourth edition, uses a holistic approach to systematically teach the breadth of the Esri Geospatial Cloud.AUDIENCEProfessional and scholarly. College/higher education. General/trade.AUTHOR BIOPinde Fu leads the ArcGIS Platform Engineering team at Esri Professional Services and teaches at universities including Harvard University Extension School. His specialties include web and mobile GIS technologies and applications in various industries. Several of his projects have won specialachievement awards. Fu is the lead author of Web GIS: Principles and Applications (Esri Press, 2010).Pub Date: Print: 7/21/2020 Digital: 6/16/2020 Format: Trade paperISBN: Print: 9781589485921 Digital: 9781589485938 Trim: 7.5 x 9 in.Price: Print: $94.99 USD Digital: $94.99 USD Pages: 490TABLE OF CONTENTSPrefaceForeword1 Get started with Web GIS2 Hosted feature layers and storytelling with GIS3 Web AppBuilder for ArcGIS and ArcGIS Experience Builder4 Mobile GIS5 Tile layers and on-premises Web GIS6 Spatial temporal data and real-time GIS7 3D web scenes8 Spatial analysis and geoprocessing9 Image service and online raster analysis10 Web GIS programming with ArcGIS API for JavaScriptPinde Fu | Interview with Esri Press | 2020-07-10 | 15:56 | Link.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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The boundaries available are: (BFE) Full resolution - extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands).Contains both Ordnance Survey and ONS Intellectual Property Rights. Version 2 - To account for name changes. E37000011 Gloucestershire changed its name to GFirst on the 31st December 2022E37000045 Derby, Derbyshire, Nottingham and Nottinghamshire has changed its name to D2N2 on the 31st December 2022E37000051 London has changed it’s name to The London Economic Action Partnership on the 31st December 2022E37000053 Oxfordshire has changed it’s name to OxLEP on the 31st December 2022E37000054 Sheffield City Region has changed it’s name to South Yorkshire on the 1st December 2022E37000059 Greater Cambridge and Greater Peterborough has changed it’s name to The Business Board on the 31st December 2022 REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BFE_V2/FeatureServer REST URL of WFS Server – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/LEP_DEC_2022_EN_BFE_V2/WFSServer?service=wfs&request=getcapabilities REST URL of Map Server – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BFE_V2/MapServer
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the digital vector boundaries for Local Enterprise Partnerships, in England, as at December 2022.The boundaries available are: (BFE) Full resolution - extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands).Contains both Ordnance Survey and ONS Intellectual Property Rights. Version 2 - To account for name changes. E37000011 Gloucestershire changed its name to GFirst on the 31st December 2022E37000045 Derby, Derbyshire, Nottingham and Nottinghamshire has changed its name to D2N2 on the 31st December 2022E37000051 London has changed it’s name to The London Economic Action Partnership on the 31st December 2022E37000053 Oxfordshire has changed it’s name to OxLEP on the 31st December 2022E37000054 Sheffield City Region has changed it’s name to South Yorkshire on the 1st December 2022E37000059 Greater Cambridge and Greater Peterborough has changed it’s name to The Business Board on the 31st December 2022
REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BFE_V2/FeatureServer
REST URL of WFS Server – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/LEP_DEC_2022_EN_BFE_V2/WFSServer?service=wfs&request=getcapabilities
REST URL of Map Server – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LEP_DEC_2022_EN_BFE_V2/MapServer
The Public Works Department operates a robust graffiti abatement program. Its strategic approach includes proactive abatement through directed patrols across the City. This “enterprise” approach strengthens the City’s commitment to prevention by aggressively removing graffiti in order to communicate that a clean city is valued.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Swimming pools are important for property tax assessment because they impact the value of the property. Tax assessors at local government agencies often rely on expensive and infrequent surveys, leading to assessment inaccuracies. Finding pools that are not on the assessment roll (such as those recently constructed) is valuable to assessors and will ultimately mean additional revenue for the community.This deep learning model helps automate the task of finding pools from high resolution satellite imagery. This model can also benefit swimming pool maintenance companies and help redirect their marketing efforts. Public health and mosquito control agencies can also use this model to detect pools and drive field activity and mitigation efforts.Licensing requirementsArcGIS Desktop – ArcGIS Image Analyst extension for ArcGIS ProArcGIS Enterprise – ArcGIS Image Server with raster analytics configuredArcGIS Online – ArcGIS Image for ArcGIS OnlineUsing the modelFollow the guide to use the model. Before using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.Note: Deep learning is computationally intensive, and a powerful GPU is recommended to process large datasets.Input8-bit, 3-band high resolution (5-7.5 centimeters) imageryOutputFeature class containing bounding boxes depicting pool locations with class BuiltinPool | PopupPoolApplicable geographiesThe model is expected to work well in the New Zealand.Model architectureThe model uses the MMDetection model architecture implemented using ArcGIS Pro Arcpy.Accuracy metricsThe model has an average precision score of 0.95.1 BuiltInPool2PopupPoolSample resultsHere are a few results from the model.(Post processing are recommended to filter out False Positive Object. If the confidence are below certain threshold e.g 5%)To learn how to use this model, see this story
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Public Works Department operates a robust graffiti abatement program. Its strategic approach includes proactive abatement through directed patrols across the City. This “enterprise” approach strengthens the City’s commitment to prevention by aggressively removing graffiti in order to communicate that a clean city is valued.
Diese Datei enthält Namen und Codes für die Local Enterprise Partnerships (LEP) (nicht überlappende Teile) in England zum 1. April 2021. (Dateigröße - 16 KB).
Feldnamen – LEPNOP21CD, LEPNOP21NM, FID
Feldtypen – Text, Text
Feldlängen – 9, 41
FID = Die FID oder Feature-ID wird durch den Publikationsprozess erstellt, wenn die Namen und Codes / Lookup-Produkte im Open Geography-Portal veröffentlicht werden.
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