This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

ArcGIS Pro is Esri's main desktop GIS software and it is easy to enable student to install and use it on their personal laptops. All you have to do is:set students up with an Esri Identity in ArcGIS Onlinepoint student at the video explaining how to download ArcGIS ProStudent logs into ArcGIS Pro using their identityLets go through those steps in a bit more detail.

City of New Orleans ownership parcels. ESRI shapefile may be downloaded by selecting 'Export', then 'Download as: Shapefile'. Free GIS software for viewing geometry may be downloaded from ESRI (http://www.esri.com/software/arcgis/arcreader/). For KMZ format, please download .kmz attached.

Mosaics are published as ArcGIS image serviceswhich circumvent the need to download or order data. GEO-IDS image services are different from standard web services as they provide access to the raw imagery data. This enhances user experiences by allowing for user driven dynamic area of interest image display enhancement, raw data querying through tools such as the ArcPro information tool, full geospatial analysis, and automation through scripting tools such as ArcPy. Image services are best accessed through the ArcGIS REST APIand REST endpoints (URL's). You can copy the OPS ArcGIS REST API link below into a web browser to gain access to a directory containing all OPS image services. Individual services can be added into ArcPro for display and analysis by using Add Data -> Add Data From Path and copying one of the image service ArcGIS REST endpoint below into the resultant text box. They can also be accessed by setting up an ArcGIS server connectionin ESRI software using the ArcGIS Image Server REST endpoint/URL. Services can also be accessed in open-source software. For example, in QGIS you can right click on the type of service you want to add in the browser pane (e.g., ArcGIS REST Server, WCS, WMS/WMTS) and copy and paste the appropriate URL below into the resultant popup window. All services are in Web Mercator projection. For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca Available Products: ArcGIS REST APIhttps://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/AerialImagery/ Image Service ArcGIS REST endpoint / URL'shttps://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/AerialImagery/GEO_Imagery_Data_Service_2013to2017/ImageServer https://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/AerialImagery/GEO_Imagery_Data_Service_2018to2022/ImageServer https://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/AerialImagery/GEO_Imagery_Data_Service_2023to2027/ImageServerWeb Coverage Services (WCS) URL'shttps://ws.geoservices.lrc.gov.on.ca/arcgis5/services/AerialImagery/GEO_Imagery_Data_Service_2013to2017/ImageServer/WCSServer/https://ws.geoservices.lrc.gov.on.ca/arcgis5/services/AerialImagery/GEO_Imagery_Data_Service_2018to2022/ImageServer/WCSServer/https://ws.geoservices.lrc.gov.on.ca/arcgis5/services/AerialImagery/GEO_Imagery_Data_Service_2023to2027/ImageServer/WCSServer/Web Mapping Service (WMS) URL'shttps://ws.geoservices.lrc.gov.on.ca/arcgis5/services/AerialImagery/GEO_Imagery_Data_Service_2013to2017/ImageServer/WMSServer/https://ws.geoservices.lrc.gov.on.ca/arcgis5/services/AerialImagery/GEO_Imagery_Data_Service_2018to2022/ImageServer/WMSServer/https://ws.geoservices.lrc.gov.on.ca/arcgis5/services/AerialImagery/GEO_Imagery_Data_Service_2023to2027/ImageServer/WMSServer/ Metadata for all imagery products available in GEO-IDS can be accessed at the links below:South Central Ontario Orthophotography Project (SCOOP) 2023North-Western Ontario Orthophotography Project (NWOOP) 2022 Central Ontario Orthophotography Project (COOP) 2021 South-Western Ontario Orthophotography Project (SWOOP) 2020 Digital Raster Acquisition Project Eastern Ontario (DRAPE) 2019-2020 South Central Ontario Orthophotography Project (SCOOP) 2018 North-Western Ontario Orthophotography Project (NWOOP) 2017 Central Ontario Orthophotography Project (COOP) 2016 South-Western Ontario Orthophotography Project (SWOOP) 2015 Algonquin Orthophotography Project (2015) Additional Documentation: Ontario Web Raster Services User Guide (Word) Status:Completed: Production of the data has been completed Maintenance and Update Frequency:Annually: Data is updated every year Contact:Geospatial Ontario (GEO), geospatial@ontario.ca

To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

The Pacific Southwest Region has geospatial datasets available for download from this website. These datasets are zipped personal or file geodatabases created using ESRI ArcGis 10.0 software. Additional descriptive information as well as data steward contact information, for each geodatabase, can be found under the metadata link. State Level Datasets Existing Vegetation, Fire History, Fire Return Interval Departure, Direct Protection Areas, and other California extent data sets. Region Level Datasets Forest Activities (FACTS), Vegetation Burn Severity, Allotments and other Regional extent datasets. Forest Planning & Monitoring Datasets Land Manangement Plans, including the Draft Early Adopters (Inyo, Sierra and Sequia National Forests) Forest Datasets Transportation and land suitability class data are available. Resources in this dataset:Resource Title: Pacific Southwest Region Geospatial Data. File Name: Web Page, url: https://www.fs.usda.gov/main/r5/landmanagement/gis The Pacific Southwest Region has geospatial datasets available for download from this website. They include State Level Datasets, Region Level Datasets, Forest Planning & Monitoring Datasets, and Forest Datasets. Freeware, like 7-Zip, for decompressing (unzipping) the geodatabases can be found by utilizing a search engine; as can freeware, like ArcGis Explorer Desktop, for viewing the geospatial dataResource Software Recommended: 7-Zip,url: http://www.7-zip.org/ Resource Title: Pacific Southwest Region Geospatial Data. File Name: Web Page, url: https://www.fs.usda.gov/main/r5/landmanagement/gis The Pacific Southwest Region has geospatial datasets available for download from this website. They include State Level Datasets, Region Level Datasets, Forest Planning & Monitoring Datasets, and Forest Datasets. Freeware, like 7-Zip, for decompressing (unzipping) the geodatabases can be found by utilizing a search engine; as can freeware, like ArcGis Explorer Desktop, for viewing the geospatial dataResource Software Recommended: ArcGIS Explorer Desktop,url: http://www.esri.com/software/arcgis/explorer/index.html

Virginia Department of Transportation Twenty Twenty Two Quarter One Linear Referencing SystemVDOT 22.1 LRS Release Map PackagePackage will be downloaded to your local 'Downloads' folder by default. Map package as downloaded is compressed. Depending on your ArcGIS software version, you may need to use the tool 'Extract Package' to unpack the package into a directory of your choosing prior to opening.LRS 22.1 Release Documents

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/.Lidar data have become an important source for detailed 3D information for cities as well as forestry, agriculture, archaeology, and many other applications. Topographic lidar surveys, which are conducted by airplane, helicopter or drone, produce data sets that contain millions or billions of points. This can create challenges for storing, visualizing and analyzing the data. In this tutorial you will learn how to create a LAS Dataset and explore the tools available in ArcGIS Pro for visualizing lidar data.To download the tutorial and data folder, click the Open button to the top right. This will download a ZIP file containing the tutorial documents and data files.Software & Solutions Used: ArcGIS Pro Advanced 3.x. Last tested with ArcGIS Pro version 3.3. Time to Complete: 30 - 60 minsFile Size: 337 MBDate Created: August 2020Last Updated: March 2024

To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.

Facilities and features in Chicago parks. For more information, visit http://www.chicagoparkdistrict.com/facilities/search/. To view or use these shapefiles, compression software and special GIS software, such as ESRI ArcGIS or QGIS, is required. To download this file, right-click the "Download" link above and choose "Save link as."

To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.

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

To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.

To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.

Users are encouraged to access the Maine ArcGIS REST Services Directory and connect to the 2-foot contour feature service layer URLs available under the "Hosted" folder instead of attempting to download the data. Many GIS software clients (including ArcGIS, QGIS, and Global Mapper) allow for exporting data directly in the software client as well, once the service connection is established. Please review your specific GIS client documentation for the workflow to add a new ArcGIS/feature service connection.AutoCAD users: There is a free plugin available (ArcGIS for AutoCAD) that allows direct editing of GIS data within AutoCAD. System requirements can be found here. The download page can be found here.

The ArcGIS system provides access to both imagery and tools for visualizing and analyzing imagery. Imagery collections from the ArcGIS Living Atlas of the World can be viewed through apps such as the Landsat Explorer app, ArcGIS Online Map Viewer, and ArcGIS Pro, while the Spatial Analyst extension and ArcGIS Image Analyst for ArcGIS Pro, more commonly know as the Image Analyst extension, provide raster functions, classification and change detection tools, and other advanced image interpretation and analysis tools. The tutorials in the Working with Imagery in ArcGIS learning path will introduce you to exploring and selecting imagery in ArcGIS web applications, applying indices and raster functions to imagery in ArcGIS Pro, and performing image classification and change detection in ArcGIS Pro.This ArcGIS Pro project package contains data for Tutorial 3, Performing Image Classification in ArcGIS Pro, and Tutorial 4, Performing Change Detection in ArcGIS Pro, of the learning path. Click Download to download the .ppkx file or click Open in ArcGIS Pro then open the pitemx file to download and open the package.Software Used: ArcGIS Pro 2.8. Project package may be opened in 3.x versions.File Size: 170mbDate Created: November 7, 2022Last Tested: December 5, 2024

This dataset is very large and detailed. As a result, there is no option to download a single dataset of the entire City as a shapefile (.shp) since it would exceed the 2 GB file size limit. If you intend to use this data in a CAD program, you should download the zone(s) in shapefile format and attach the data to your project.

 Download Shapefile by Zone(click on a zone to start the download)



  Zone A





  Zone C


  Zone B





  Zone D

EPA Intelligent Dasymetric Mapping (IDM) ToolboxThe Intelligent Dasymetric Mapping (IDM) Toolbox is available to download based on the version of ArcGIS software implemented.The IDM Toolbox uses ArcPy and arcpy.da functionality. This version requires ArcGIS 10.3 or higher. The ArcPy toolbox contains a number of scripts that assist preparing vector population and raster ancillary datasets for intelligent dasymetric mapping, performs the dasymetric calculations, and then generates a floating point output raster of revised population density. Please see the documentation in the zip file for more information on the individual tools.You may find more information by the EPA about this data and the toolbox here: https://www.epa.gov/enviroatlas/dasymetric-toolboxTO DOWNLOAD: simply click on the "Open" button at the top right to start the 2GB download of the zip file. Or, you may go directly to the EPA's FTP download site here: https://edg.epa.gov/data/public/ORD/EnviroAtlas/National/ConterminousUS/ and download the "dasymetric_us_20160208.zip" file.

On November 7, 2021, NV5 collected Quality Level 1 (QL1) lidar data across the preliminary CAL FIRE defined fire perimeter for the CZU lightning complex fire in San Mateo and Santa Cruz counties. The technical report for the lidar data collection is available here: https://fuelsmapping.com/czu_postfire_lidar_report From the QL1 postfire lidar, NV5 and Tukman Geospatial developed a set of derivatives. These derivatives are a Digital Terrain Model (DTM), a Digital Surface Model (DSM), a Hillshade derived from the DTM, a lidar intensity image, a Normalized Digital Surface Model (nDSM), a Canopy Cover raster, and a lidar intensity image. The derivatives will be used to study the effects of the CZU wildfire on the natural landscape, forests, and shrublands of Santa Cruz and San Mateo Counties. The lidar derivatives are provided as GeoTiffs available for download from ArcGIS Online and as dynamic image services. Table 1 provides more information (including download information) for the derivatives produced. The GeoTiffs can be used in desktop GIS software packages such as ArcGIS Pro and ERDAS Imagine; the image services can be used in web maps and web mapping applications by both GIS users and non-GIS users. Table 1. lidar derivatives for the CZU lightning fire footprint in San Mateo and Santa Cruz Counties

  Dataset


  Description


  Link to GeoTiff


  Link to Image Service






  Digital Terrain Model (DTM)


  Hydroflattened digital terrain model. Pixel values represent elevation above sea level of the ground.


  https://vegmap.press/czu_postfire_dtm_tif


  https://vegmap.press/czu_postfire_dtm




  Digital Surface Model (DSM)


  Pixel values in the DSM represent elevations above sea level of the ‘highest hit’ surface. The DSM provides elevation above sea level of the top of the tree canopy, the top of buildings, and the top of other features.


  https://vegmap.press/czu_postfire_dsm_tif


  https://vegmap.press/czu_postfire_dsm




  Hillshade


  The hillshade is derived from the DTM and provides a ‘shaded relief’ visualization of the earth’s surface.


  https://vegmap.press/czu_postfire_hillshade_tif


  https://vegmap.press/czu_postfire_hillshade




  Lidar Intensity


  Lidar intensity, scaled to 8-bit resolution.


  https://vegmap.press/czu_postfire_intensity_tif


  https://vegmap.press/czu_postfire_lidar_intensity




  Normalized Digital Surface Model (nDSM)


  In the nDSM, pixel values represent the maximum normalized height in feet of features such as vegetation and structures. For areas with aboveground features, pixel values represent the aboveground height of the tallest part of the feature in the 3x3 foot pixel. For areas with no aboveground features, the nDSM has pixel values of 0. 


  https://vegmap.press/czu_postfire_nDSM_tif


  https://vegmap.press/czu_postfire_nDSM




  Canopy Height Model


  The canopy height model is the normalized digital surface model, with building footprints and a small buffer surrounding them set to 0 normalized height. Building footprint data came from the prefire CHM. The datasheet for the prefire CHM is available here: https://vegmap.press/sc_chm As such, this raster mostly represents the aboveground height of the vegetation canopy.  Note that it also includes some noise (e.g., powerlines and other objects that are not vegetation), as well as some structures that weren't captured as building footprints.


  https://vegmap.press/czu_postfire_chm_tif


  https://vegmap.press/czu_postfire_chm




  Canopy Cover


  This is the Canopy Height Model, thresholded to show pixel values greater than or equal to 15 feet aboveground as 1, and all other areas as 0. As such, it is a proxy for tree canopy cover. 


  https://vegmap.press/czu_postfire_cc_tif


  https://vegmap.press/czu_postfire_cc

Related Datasets: The QL1 point cloud, from which these deliverables were acquired, is available as laz files. The laz files are downloadable by tile. See this datasheet for more information: CZU postfire QL1 point cloudCZU postfire 4-band imagery