ArcGIS tool and tutorial to convert the shapefiles into network format. The latest version of the tool is available at http://csun.uic.edu/codes/GISF2E.htmlUpdate: we now have added QGIS and python tools. To download them and learn more, visit http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

Contents: This is an ArcGIS Pro zip file that you can download and use for creating map books based on United States National Grid (USNG). It contains a geodatabase, layouts, and tasks designed to teach you how to create a basic map book.Version 1.0.0 Uploaded on May 24th and created with ArcGIS Pro 2.1.3 - Please see the README below before getting started!Updated to 1.1.0 on August 20thUpdated to 1.2.0 on September 7thUpdated to 2.0.0 on October 12thUpdate to 2.1.0 on December 29thBack to 1.2.0 due to breaking changes in the templateBack to 1.0.0 due to breaking changes in the template as of June 11th 2019Updated to 2.1.1 on October 8th 2019Audience: GIS Professionals and new users of ArcGIS Pro who support Public Safety agencies with map books. If you are looking for apps that can be used by any public safety professional, see the USNG Lookup Viewer.Purpose: To teach you how to make a map book with critical infrastructure and a basemap, based on USNG. You NEED to follow the steps in the task and not try to take shortcuts the first time you use this task in order to receive the full benefits. Background: This ArcGIS Pro template is meant to be a starting point for your map book projects and is based on best practices by the USNG National Implementation Center (TUNIC) at Delta State University and is hosted by the NAPSG Foundation. This does not replace previous templates created in ArcMap, but is a new experimental approach to making map books. We will continue to refine this template and work with other organizations to make improvements over time. So please send us your feedback admin@publicsafetygis.org and comments below. Instructions: Download the zip file by clicking on the thumbnail or the Download button.Unzip the file to an appropriate location on your computer (C:\Users\YourUsername\Documents\ArcGIS\Projects is a common location for ArcGIS Pro Projects).Open the USNG Map book Project File (APRX).If the Task is not already open by default, navigate to Catalog > Tasks > and open 'Create a US National Grid Map Book' Follow the instructions! This task will have some automated processes and models that run in the background but you should pay close attention to the instructions so you also learn all of the steps. This will allow you to innovate and customize the template for your own use.FAQsWhat is US National Grid? The US National Grid (USNG) is a point and area reference system that provides for actionable location information in a uniform format. Its use helps achieve consistent situational awareness across all levels of government, disciplines, and threats & hazards – regardless of your role in an incident.One of the key resources NAPSG makes available to support emergency responders is a basic USNG situational awareness application. See the NAPSG Foundation and USNG Center websites for more information.What is an ArcGIS Pro Task? A task is a set of preconfigured steps that guide you and others through a workflow or business process. A task can be used to implement a best-practice workflow, improve the efficiency of a workflow, or create a series of interactive tutorial steps. See "What is a Task?" for more information.Do I need to be proficient in ArcGIS Pro to use this template? We feel that this is a good starting point if you have already taken the ArcGIS Pro QuickStart Tutorials. While the task will automate many steps, you will want to get comfortable with the map layouts and other new features in ArcGIS Pro.Is this template free? This resources is provided at no-cost, but also with no guarantees of quality assurance or support at this time. Can't I just use ArcMap? Ok - here you go. USNG 1:24K Map Template for ArcMapKnown Limitations and BugsZoom To: It appears there may be a bug or limitation with automatically zooming the map to the proper extent, so get comfortable with navigation or zoom to feature via the attribute table.FGDC Compliance: We are seeking feedback from experts in the field to make sure that this meets minimum requirements. At this point in time we do not claim to have any official endorsement of standardization. File Size: Highly detailed basemaps can really add up and contribute to your overall file size, especially over a large area / many pages. Consider making a simple "Basemap" of street centerlines and building footprints.We will do the best we can to address limitations and are very open to feedback!

This resources contains PDF files and Python notebook files that demonstrate how to create geospatial resources in HydroShare and how to use these resources through web services provided by the built-in HydroShare GeoServer instance. Geospatial resources can be consumed directly into ArcMap, ArcGIS, Story Maps, Quantum GIS (QGIS), Leaflet, and many other mapping environments. This provides HydroShare users with the ability to store data and retrieve it via services without needing to set up new data services. All tutorials cover how to add WMS and WFS connections. WCS connections are available for QGIS and are covered in the QGIS tutorial. The tutorials and examples provided here are intended to get the novice user up-to-speed with WMS and GeoServer, though we encourage users to read further on these topic using internet searches and other resources. Also included in this resource is a tutorial designed to that walk users through the process of creating a GeoServer connected resource.

The current list of available tutorials: - Creating a Resource - ArcGIS Pro - ArcMap - ArcGIS Story Maps - QGIS - IpyLeaflet - Folium

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/.In this tutorial, you are a GIS analyst for the City of Lethbridge in Alberta who has been tasked with generating building footprint layers for various neighbourhoods to support city planning activities. You want to use deep learning to extract building footprints from aerial imagery in ArcGIS Pro. You’ll choose a pretrained model provided by ArcGIS Living Atlas and use the transfer learning approach to fine-tune the model’s performance in the City of Lethbridge. To download the PDF tutorial, click the Download button to the top right on this page.To download the data required, visit this link and click Download: https://www.arcgis.com/home/item.html?id=29d38e9248b34ba096fb4df7b1aed24e.Software & Solutions Used: ArcGIS Pro 2.5+Time to Complete: 120 minutesDate Created: February, 2024Last Updated: April, 2025

This User Guide contains information about the ONSUD including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 356 KB)

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

Example citations:

Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

11.1 Refugial potential for vascular plants and mammals (1990-2050)

11.1 Refugial potential for reptiles and amphibians (1990-2050)

12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

PDF Document guide to use of the web application of the same name.Updated on 12/18/2024 to include section on data download feature. Removes section regarding outdated equity index nomenclature. For information on the Equity Index, please see information found within the Equity and Displacement Risk application.

This dataset was updated April, 2024.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes: Clipping input datasets to the California boundary Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc) Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California. Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only. Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs) In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset.Data Sources: GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.htmlData Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.

The Ontario Imagery Web Map Service (OIWMS) is an open data service available to everyone free of charge. It provides instant online access to the most recent, highest quality, province wide imagery. GEOspatial Ontario (GEO) makes this data available as an Open Geospatial Consortium (OGC) compliant web map service or as an ArcGIS map service. Imagery was compiled from many different acquisitions which are detailed in the Ontario Imagery Web Map Service Metadata Guide linked below. Instructions on how to use the service can also be found in the Imagery User Guide linked below.Note: This map displays the Ontario Imagery Web Map Service Source, a companion ArcGIS web map service to the Ontario Imagery Web Map Service. It provides an overlay that can be used to identify acquisition relevant information such as sensor source and acquisition date. OIWMS contains several hierarchical layers of imagery, with coarser less detailed imagery that draws at broad scales, such as a province wide zooms, and finer more detailed imagery that draws when zoomed in, such as city-wide zooms. The attributes associated with this data describes at what scales (based on a computer screen) the specific imagery datasets are visible.Available ProductsOntario Imagery OCG Web Map Service – public linkOntario Imagery ArcGIS Map Service – public linkOntario Imagery Web Map Service Source – public linkOntario Imagery ArcGIS Map Service – OPS internal linkOntario Imagery Web Map Service Source – OPS internal linkAdditional DocumentationOntario Imagery Web Map Service Metadata Guide (PDF)Imagery User Guide (Word)StatusCompleted: Production of the data has been completedMaintenance and Update FrequencyAnnually: Data is updated every yearContactOntario Ministry of Natural Resources, Geospatial Ontario, imagery@ontario.ca

Geodatabase: N/A

Geodatabase Filename: N/A

Creation Date: May 2024

Update Date: Currently Up-To-Date

Data Location: AGOL

Data Type: PDFData Subtype: N/A

Hub Site List: CSA DCR (Community Resilience) Mental Health

Data Description:

Conversation guide developed for Mental Health Month 2024 to provide education and prompts about eight key dimensions of wellness and local mental health supports and resources.

Data Update Log: None

Data Error Log: none

This User Guide contains information about the ONSUD including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 353 KB)

This User Guide contains information about the ONSUD including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 356 KB)

Explore the Great Outdoors - Trail Maps and Guide (PDF)

SarTopo CalTopo How To Guide for the WEB APP

PROTOTYPE - Under Development - Not to be relied upon for Operational Use. Visit weather.gov for operational information.The National Weather Service (NWS) is evolving to build a Weather-Ready Nation, where communities are ready, responsive, and resilient to increasing vulnerabilities from extreme weather, water, and climate events and environmental hazards. To build a Weather-Ready Nation, the NWS is committed to providing science-based analysis, forecasts and partnership interactions in a consistent way across the agency to effectively deliver accurate and timely weather, water and climate information to decision makers at the federal, state, local and tribal nation levels. NWS service evolution in the area of Impact-based Decision Support Services (IDSS) is based on the recognition of the expanding demands of our core partners to prepare and respond to extreme events.This National Weather Service Impact-Based Decision Support Services (IDSS) Dashboard user guide in PDF format assists users in navigating the functionality of the dashboard. For more information about National Weather Service Impact-Based Decision Support Services, visit https://www.weather.gov/about/idss. In addition, please view the NWS IDSS Service Description Document.

Please note: this data differs in some of its columns from the Jan 2013 - Sep 2020 set. This data is a singular snapshot of a dataset published to promote innovation and research. It is not updated or expanded from the date range described.TMS traffic quarter-hourly (2013-2020)

Data reuse caveats: as per license.Data quality statement: please read the accompanying user manual, explaining:how this data is collectedidentification of count stationstraffic monitoring technologymonitoring hierarchy and conventionstypical survey specificationdata calculationTMS operation.Traffic monitoring for state highways: user manual [PDF 465 KB]Data quality caveats: you must use this data in conjunction with the user manual, and the following caveats.Much of this data is sourced from road sensors and may be subject to technical or environmental factors.Data is compiled from a variety of sources. Accuracy may vary and the data should only be used as a guide.Data is representative of the change of traffic volume not of total traffic volume for each region.Data is sourced from Waka Kotahi New Zealand Transport Agency TMS data.Light and heavy traffic volumes have been split using TMS data where vehicles with a length of less than 5.5m are classed as light vehicles. Heavy vehicles are over 11m long. Those between 5.5 and 11m are split 50:50 into light and heavy vehicles.Please be aware that when unzipped these are very large files and some systems may have difficulty opening it. Each file contains more than 10 million rows, and therefore won't work in Excel. However, each file is in CSV format, and will work in:programming languages such as Python or Rdatabases with SQL.State highway traffic monitoring (map)State highway traffic monitoring sitesState highway daily-updated traffic count (API and CSV)

Photo by Joseph Chan on Unsplash

This User Guide contains information about the ONSUD including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 356 KB)

Biking in Rwanda is a Mountain Bike Guide for Rwanda with - in its current version - 59 well document tracks and countless alternatives covering more than 8500 kilometersAll the tracks are also available in GPX-Format. The respective Zipped File is available on ArcGIS Online in the form of "attached code" with the "Find a Bike Route in Rwanda Web Application"08.11.2020: Replaced with one page PDF, with the links to the updated, 7th Edition, 102 views in the year up to 08.11.2020High Resolution Version uploaded: 24.4.2017 (Original V636), to date: 74 Views, 0 ratingsHigh Resolution Version uploaded: 3.2.2016 (Original V405)High Resolution Version uploaded: 24.7.2015 (Original V255)High Resolution Version uploaded: 16.7.2015 (Original V244)The Filename for replacing the guide with a newer version must be '20150117_BikingInRwanda_244_highres.pdf' (regardless of the actual version, Kaspar should have chosen a more update-neutral name from the beginning - but did not).

This User Guide contains information about the ONSUD including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 350 KB)

This User Guide contains information about the NSUL including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 386 KB)