It’s a complete training guide to help you get started with complex image processing workflows. It includes a checklist of tutorials, videos and lessons along with links to additional help topics.
This guide is useful to anyone interested in learning how to work with the powerful image processing and visualization capabilities available with the ArcGIS Image Analyst. Complete the checklist provided in the guide and you’ll get hands on experience with:
Setting up ArcGIS Image Analyst in ArcGIS Pro
Extracting features from imagery using machine learning image classification and deep learning methods
Do you have imagery from an aerial photography camera (whether a modern digital camera or scanned film) and the orientation data either by direct georeferencing or the results of aerial triangulation? If yes, you’ll want to work with a mosaic dataset, and load the imagery with the proper raster type.
The mosaic dataset provides the foundation for many different use cases, including:
On-the-fly orthorectification of images in a dynamic mosaic, for direct use in ArcGIS Pro or sharing through ArcGIS Image Server.
There are different raster types that support the photogrammetric model for frame imagery. If you have existing orientation data from ISAT or Match-AT, you can use the raster types with those names to directly load the data (see Help here).
For a general frame camera, you’ll want to know how to use the Frame Camera raster type and we have recently updated some helpful resources:
If you want to extract a digital terrain model (DTM) from the imagery, or improve the accuracy of the aerial triangulation, see the Ortho Mapping capabilities of ArcGIS Pro (advanced license). http://esriurl.com/OrthoMapping.
Any remote sensing image, whether it’s a drone image, aerial photograph, or data from a satellite sensor, will inherently be impacted by some form of geometric distortion. The shape of local terrain, the sensor angle and altitude, the motion of the sensor system, and the curvature of the Earth all make it difficult to represent three dimensional ground features accurately in a two dimensional map. Image orthorectification corrects for these types of distortion so you can have a measurable, map-accurate image.
Everyone working with GIS data to make well-informed decisions needs up-to-date information about the natural, man-made, and cultural features on the ground: roads, land cover types, buildings, water bodies, and other features that fill the landscape. Much of the vector data that describes these features was actually created from orthorectified imagery, and can be combined with new imagery to update your landbase.
Esri’s Ortho Mapping suite enables you to orthorectify your remote sensing imagery to make it map-accurate. It also makes it easy to create other products like orthomosaics (mosaicked images corrected for distortion) and digital elevation models (terrain or surface models) which can be used as basemaps, part of a landbase, or for further analysis in stereo models, 3D analysis and feature extraction.
The workflow to create ortho mapping products will be presented in a three-part blog series, each with a short video:
Creating a workspace
Performing a block adjustment
Creating ortho mapping products
Let's get started!
Creating an Ortho Mapping Workspace
The first step in any project is getting organized – and creating an Ortho Mapping Workspace in ArcGIS Pro makes this easy to do.
TheOrtho Mapping Workspaceis a sub-project in ArcGIS Pro; it’s the interface you work with when interacting with ortho mapping workflows. The workspace is defined by the type of imagery you are working with (drone, aerial or satellite). In turn, the workspace is integrated with the tools and wizards to properly guide you through each step in the workflow. When you create a new workspace, an Ortho Mapping folder appears in your project folder structure in Catalog, and a new table of contents list view allows you toList By Ortho Mapping Entities. Again, the types of feature classes and tables you see in the Contents pane depend on the type of imagery you are working with.
Similar to Maps or Scenes within a project, a workspace is an object stored in the folder structure of a project and it can be accessed by other projects. All the feature classes and tables needed to orthorectify your imagery are created and managed in the workspace.
5 Simple Steps
Step 1: Open theImagerytab in your ArcGIS Pro project. This is where you can analyze and manage any raster data you want to work with in Pro. In the Ortho Mapping group, you’ll see theNew Workspacemenu that allows you to create a New Ortho Mapping Workspace, add an existing Ortho Mapping Workspace with a reference to that workspace, or import an Ortho Mapping Workspace by creating a copy of an existing workspace and storing the new copy in your project. SelectNew Workspace.
Step 2: TheNew Ortho Mapping Workspacewizard appears. Here you’ll give your workspace a name (required) which identifies your project in the Contents and Catalog panes. You can also provide a description (optional) and you’ll select the type of imagery you want to import. In our workflow, we’re using aerial imagery acquired byVexcel Imaging covering an area over Hollywood, California, so we’ll selectAerial – Digitalas the type. Click Next.
Step 3:TheImage Collectionpage opens. Here you’ll enter specific information about the type of sensor used to collect your imagery. You can choose from MATCH-AT, ISAT, or Applanix, or you can select the Generic Frame Camera, which requires you to provide the exterior and interior orientation information with the Frames tables and Cameras tables, respectively. Entering the Frames and Cameras information will provide the information necessary to correct for sensor-related distortion.
TheFrames tablehas aspecific schemathat is required in the ortho mapping workspace for aerial imagery. It contains the exterior orientation and other information specific for each image comprising your image collection. TheCameras tablecontains all the camera calibration information for computing the interior orientation, but you can add the camera information manually in the wizard or as a table. To edit the Camera parameters, you can hover over the Camera ID and click the Edit Properties button. You’ll also need to specify theFrame Spatial Reference, which be provided with your data.
In this workflow, we used the exterior orientation information that was provided along with our source imagery to create the Frames table in the necessary schema. We then pointed to a table that has the information for one camera, with CameraID = 0 (see the screen shot below - there's a check mark next to the 0 under Cameras).
*We are updating this for ArcGIS Pro 2.3 to be more user-friendly for a better experience!
Step 4: To correct for terrain displacement, you need to include an elevation source. The cool thing about working with the ArcGIS platform is you can access the thousands of maps, apps and data layers available in theArcGIS Living Atlas, so if you don’t have your own elevation data you can search for one and use it into your project. Here’s what we did:
In our ArcGIS Pro project, zoom to the area of interest in Hollywood.
On the Map tab, click Add Data and add data to the map.
Select the Living Atlas option under the Portal group and search for "Terrain." Add the Terrain imagery layer. At first, you might not be able to see much variation in the terrain. Click on the Appearancetab under theImage Service Layergroup and selectDRA(Dynamic Range Adjustment) to stretch the terrain imagery in the extent you are viewing.
In the Contents pane, right-click on the Terrain imagery layer and select Data > Export Raster.
In the Export Raster settings, specify the output raster dataset and set the Clipping Geometry to the Current Display Extent.
Now we can add our new DEM to the workspace. To do this, open theData Loader Optionspane in theImage Collection page. Click the browse button to navigate to the DEM created above, or use your own DEM.
Step 5:Finally, we left all the other values as default and clicked Finish.
A Logwindow will tell you how the creation of the workspace is coming along, and if there are any problems, an error message will be displayed. When it’s complete, you’ll see the newOrtho Mapping Entitiesin yourContentspane: various control points including Ground Control Points, Check Points and Tie Points, the mosaic dataset that was created using your source data, and placeholders for Data Products, Solution Data, and QA/QC Data that haven’t been created yet.
Make sure to zoom and pan around the map to check out your Image Collection. With the Image Collection selected in theContentspane, you can open theDatatab from theMosaic Layercontext menu. Here you can change theSortandOverlapoptions for your mosaic dataset. We recommend using the Closest to Center or Closest to Nadir options for viewing.
Now that you have all your ortho mapping components organized in your workspace, the next step is to block adjust your data to make sure it’s map-accurate. Stay tuned for the next part of this blog series,Ortho Mapping with Aerial Data Part II: Getting Adjusted, where we’ll show you how to perform a block adjustment to make sure your data is ready for product generation and stereo compilation!
We showed you how to set up an ortho mapping workspace for aerial imagery. For an example of how to set up an ortho mapping workspace for satellite data, check out this short video!
With the Image Analyst extension in ArcGIS Pro 2.1 (or later), non-orthorectified and suitably overlapping images with appropriate metadata can be viewed in stereo! This stereoscopic viewing experience can enable 3D feature extraction. See more information at http://esriurl.com/stereo.
If your organization has a collection of images and you’d like to use the stereo viewing capability in ArcGIS Pro, where do you start? The key questions are:
What type of sensor collected the data, and
What orientation data do you have along with the images?
In order to display images as stereo pairs, ArcGIS must have detailed information about the location of the sensor (x,y,z) as well as its orientation – and this is unique information for every image. Information about the sensor (typically called a camera model or sensor model) is also required.
There are a few conceptually simple cases, although each has important details to follow within its own workflow and documentation.
If you have two overlapping satellite images, you can go directly to stereo viewing.
If you have a collection of satellite images, you can build a mosaic dataset and ingest the images using the specific raster type for that satellite, run the Build Stereo Model geoprocessing tool, then proceed to the stereo view. The raster type for the satellite reads the required orientation data.
If your imagery came from a professional aerial camera system:
If you have an output project file from aerotriangulation (AT) software (e.g. Match-AT or ISAT), ArcGIS includes raster types which ingest the orientation data for you, so this is similar to the satellite case: build a mosaic dataset with the proper raster type, Build Stereo Model, and proceed to stereo viewing.
If you have a project file from AT software not currently supported, Python raster types are under development for additional sensors e.g. for the Vexcel Ultracam. For more information, watch for announcements on GeoNet or on http://esriurl.com/ImageryWorkflows. Alternatively, if you have a table of camera and frame orientation values, see the next bullet.
If you have a table of data values representing the exterior orientation as well as a camera model (interior orientation), you will build a mosaic dataset and ingest the images using the “Frame camera” raster type.
This document (http://esriurl.com/FrameCameraBestPractices) provides a workflow for how to prepare the necessary camera & frame data, then configure the mosaic dataset.
If you have scanned film but without the results of AT software, refer to the FrameCameraBestPractices. With ArcGIS Pro 2.1, some values may have to be estimated, and the positional accuracy may not be optimum. ArcGIS Pro 2.2 (and later versions) support fiducial measurement.
If your imagery was captured using a drone, you will need to use photogrammetric software to generate the camera model and orientation data.
If you process your drone imagery using Ortho Mapping in ArcGIS Pro Advanced (see http://esriurl.com/OrthoMappingHelp), after the Adjust step is completed, the Image Collection mosaic dataset will be ready for viewing in stereo (after Build Stereo Model).
If you are using Drone2Map, please see this item ArcGIS Online http://esriurl.com/D2Mmanagement to download a geoprocessing tool which can ingest the images into a mosaic dataset.