Note:
This workflow may not be appropriate if you have any of the following:- A small number of images and you do not require a very high level of accuracy. Instead, use the georeferencing tools in ArcGIS Pro as a simpler alternative. (For a collection of more than a few dozen images, or if you need an accurate orthorectified result, use the Frame Camera workflow.)
- Imagery that has already been orthorectified. Instead, see Manage preprocessed orthophotos.
- Match-AT, ISAT, Applanix, ADS40, ADS100, or you're using satellite data. Instead, use the aerial imagery raster type or satellite raster type defined in ArcGIS. (BINGO will require the Frame Camera workflow.)
- Unprocessed aerial imagery captured with a line scanning sensor, such as the ITRES CASI, SPECIM AISA, and so on.
- Processing drone images using ArcGIS Drone2Map or ortho mapping in ArcGIS Pro Advanced—the software automatically does these calculations behind the scenes.
Orthorectification ensures that when an image is viewed on a map, all pixels in the image are placed in an accurate (x,y) position on the ground. In many scenarios requiring imagery, GIS users can obtain imagery that is already orthorectified so it can be dragged directly into the map and it will appear in the proper location. In some cases, however, users may obtain a collection of frame camera images that are not orthorectified. In this case, photogrammetric processing will be required to display the images with map-like accuracy.
This workflow is applied to imagery from full-frame sensors, which refers to the physical camera used to capture imagery. These include professional large-format and medium-format cameras—either digital mapping cameras or film cameras—usually carried on an aircraft.
Before you can accurately view unprocessed source imagery (or unprocessed scans of historical imagery) from full-frame sensors on a map, you'll need to apply a photogrammetric camera model that can be implemented within ArcGIS. Based on geometric information about the camera and its location when each image was captured, the software can then calculate exactly where the image would appear on the ground.
To apply photogrammetry in ArcGIS, images from frame full-frame sensors are collected into mosaic datasets using the Frame Camera raster type. This raster type requires two tables:
- Frames table, which contains camera information specific to each frame, such as the perspective x,y,z location in an appropriate coordinate system, and the orientation (expressed as omega, phi, and kappa angles) of the camera.
- Cameras table, which contains camera-specific parameters, such as focal length and the principal point x,y coordinate.
Explore the following resources to learn more about the proper configuration of the input data for the Frame Camera raster type. (Not sure where to start? Look for the star by Esri's most helpful resources.)
Note:
To create and edit mosaic datasets, you'll need ArcGIS Pro Standard or ArcGIS Pro Advanced. The Ortho Mapping workspace requires ArcGIS Pro Advanced. To view orthorectified images in stereo or image space, you'll need the ArcGIS Image Analyst extension for ArcGIS Pro.
Imagery Workflows resources
Review the community-supported tools and best practices for working with and automating imagery and remote sensing workflows:
- Read Frame Camera Best Practices for frame camera workflow advice for a variety of image configurations (for example, nadir, oblique, and multisensor), terrain sources (use of ArcGIS Online world elevation versus a local DTM file), and more.*
- The Frame Camera Manual Sample provides sample data and instructions for manually creating a mosaic dataset using the Frame Camera raster type, using a frames table and cameras table that are provided.*
- The Frame Camera Automated Script provides sample data and a Python script for automating the creation of a mosaic dataset using the Frame Camera raster type, using an accurate aerotriangulation result as input.
- Prepare scanned historical aerial photos to use this workflow with these custom geoprocessing tools.
- Download a script to apply this workflow (behind the scenes) to manage drone images after they've been processed in ArcGIS Drone2Map. This script will read the photogrammetric metadata from the completed Drone2Map project and create a single-frame mosaic dataset using the Frame Camera raster type. (This is a recommended best practice for automating data management.)
- Read documentation explaining best practices for creating mosaic datasets and structuring and formatting imagery and rasters.
ArcGIS help
Review the following links on reference materials for ArcGIS products:
- Review the following links on reference materials for ArcGIS products: Read about the raster types used to support aerial imagery in ArcGIS, including the Frame Camera raster type.
- Read about the Frames table schema used in the Frame Camera raster type.
- Read about the Cameras table schema used in the Frame Camera raster type.
- Learn about managing imagery and raster data with mosaic datasets.
ArcGIS blogs, articles, story maps, and technical papers
Review the following supplemental guidance about concepts, software functionality, and workflows:
- Read this blog for a quick review of when to use mosaic datasets to manage frame camera imagery.
Developer resources
Review the following resources and support for automating and customizing workflows:
- Visit the MDCS GitHub repository to download a Python script to help automate the creation and configuration of mosaic datasets.
Esri Community
Use the online imagery community to connect, collaborate, and share experiences:
- See what the Imagery and Remote Sensing community is saying about using the Frame Camera raster type.