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Ortho mapping workflow

The ortho mapping workflow involves the following steps:

  1. Create an ortho mapping workspace
  2. Measure fiducials
  3. Perform block adjustment
  4. Input ground control points
  5. Finalize the block adjustment
  6. Update the DTM

Once this workflow is complete, you can generate orthomosaics or DEMs, or use the image collection directly.

Information about the standard workflow for each step can be found in Ortho Mapping in ArcGIS Pro. Below, find recommendations and troubleshooting tips for processing historical images.

Create an ortho mapping workspace

After you have built the Cameras and Frames tables, use the ortho mapping wizard to create a new workspace using the Aerial – Scanned option. Options for creating Cameras and Frames tables include the following:

  • Compile the tables in either *.csv format (before working in ArcGIS Pro) or ArcGIS table format, then load those tables when prompted by the ortho mapping workspace creation wizard.
  • These tables can also be prepared before creating your workspace using the Build Frame and Camera Tables tool.

While adding frame and camera tables, always select an appropriate DEM source. This will create a proper DEM link in the Raster Function chain of the mosaic dataset, and update the image as soon as block adjustment is successful. Without a DEM, even if the block adjustment results are good, it will not update the viewer and the mosaic will appear incorrect.

Learn more about creating an ortho mapping workspace for scanned aerial imagery in ArcGIS Pro.

Measure fiducials

Once your ortho mapping workspace has been created, for best accuracy you should perform fiducial measurement to align each frame of film with the calibrated camera model. For this step, you’ll use the Refine Interior Orientation button on the Ortho Mapping ribbon.

Learn more about refining interior orientation using fiducials.

If your Cameras table includes the known fiducial locations (in microns) from the camera calibration report, the fiducial measurement workflow includes the following steps:

  • Define a template for a single fiducial at the position identified by the template type (the left middle fiducial in the following example).

    Screenshot highlighting the fiducial position

  • Use the Compute button to measure fiducials in all other images
  • Visually check the accuracy of the computed results
  • Apply the measurements to the images

If your Cameras table did not include the known fiducial locations (or you did not have a camera calibration report), the fiducial measurement workflow will include the following steps:

  • Capture a template for all middle and corner fiducials for a single image

    screenshot highlighting corner or edge fiducials

  • Select Compute to measure all other photos
  • Visually check the accuracy of the computed results
  • Apply the measurements to the images

Continue below for details regarding fiducial measurement in these two cases.

Camera coordinates for fiducial locations are known

If you entered known fiducial coordinates in the Cameras table, the Refine Interior Orientation interface will appear. You will have one entry in the table for either (or both) edge or corner fiducials. You’ll pan and zoom in the upper window to navigate to a representative fiducial location and capture a template (sample image) for the fiducial. More information can be found in the ArcGIS Pro Help.


It is recommended to capture a very small area around the center of the fiducial. The tool may fail if you capture a large area.

Screenshot highlighting small area around the center of the fiducial

After you have created a template image for one corner (and/or side) fiducial, you can click Compute Fiducial Coordinates to measure all of the images in your workspace.


Depending on the state of your workspace, you may see a blank view at the top of the fiducial menu if the view is zoomed in too far. In this case, use the World button to zoom out to the full image in the upper view, then navigate to zoom in to a fiducial as necessary.

Screenshot of the Refine Interior Orientation interface

Camera coordinates for fiducial locations are unknown

If you do not have a camera calibration report, you may not be able to enter the known fiducial coordinates into the Cameras table. Starting with ArcGIS Pro 2.6, the Refine Interior Orientation interface will allow you to proceed by navigating to capture the template image for all fiducials in one group (e.g. all four corners or all four edges). If your camera includes both edge and corner fiducials, it is recommended you capture all eight.

In this case, the bottom of the user interface will show eight entries in the table for the possible fiducial locations. You’ll need to select one location at a time, navigate to the fiducial, and then capture an image of each. Once all measurements are completed for one image, you can select Compute Fiducial Coordinates and ArcGIS will first calculate the fiducial locations in the camera coordinate system, then perform the image file fiducial measurement on all images in the collection.

Screenshot of the fiducial position interface

Perform aerotriangulation and block adjustment

The next step in ortho mapping is to run aerotriangulation to automatically find tie points between images in overlap areas, then a block adjustment to resolve and later to improve the accuracy of the interior and exterior orientation.

Learn more about performing block adjustment in ArcGIS Pro.

Following are some things to keep in mind when completing aerotriangulation and block adjustment:

The first time you run the Adjust tool, the software will automatically generate tie points while performing a simultaneous, multi-station relative orientation of images in the block. After tie points have been found, re-running Adjust (for example, after entering ground control points) will be much faster since only absolute orientation is performed.

If you are using the ortho mapping ribbon interface, the settings applied for tie point collection and block adjustment are predefined based on the image type (in this case, scanned aerial photos) as well as assumptions about the accuracy of the initial orientation data. If you need more detailed control over these steps, you can run individual geoprocessing tools, including Compute Block Adjustment to calculate new values for the exterior orientation and Apply Block Adjustment to apply the new values within the mosaic dataset.

After running block adjustment, check to verify that your images are at the correct scale and in the correct positions. Also check to verify that all images were successfully processed. If you find some images were removed from the block, you can use the Tie Point Editor to restore them to the project. Add tie points from any rejected images to appropriate neighbor images, then re-run the block adjustment.

The image collection in the map may not be accurate enough for a final product. If not, proceed to adding ground control points (GCPs).


ArcGIS Pro has the ability to perform camera calibration to compute lens distortion values. For professional mapping cameras, distortion values are so small that this can be ignored for many projects, but some users will want to see the radial distortions. By checking Perform Camera Calibration, distortions are automatically computed. For users running the geoprocessing tool instead of using the ortho mapping ribbon,the user will need to define Adjustment option CameraCalibration as 1 to activate the option to compute distortion coefficients.

Apply ground control

Using accurate ground control is recommended to ensure the best accuracy in your final products. If you have information regarding control points recorded at the time of the film flight, refer to Add GCPs to your ortho mapping workspace for information about how to ingest a table of control points and then link the points to the images. You can follow the default workflow described in Help.

Some film projects may be very old or poorly documented, and do not have high quality control points. In this case, you have the following options:

Options for the best available ground control

For best accuracy, you will need to apply ground control in the block adjustment process.

You need both a source of control and to be able to identify the control point locations in the images. Depending on the age and scan quality of your imagery, finding photo-identifiable points may be challenging.


The interface to enter GCPs is not enabled until after an initial block adjustment.

Sources of horizontal control

Optimum ground control is collected using a modern GPS receiver on permanent objects visible in the historical photos. Examples could be corners of concrete sidewalks or, in natural terrain, it may be possible to locate large rocks visible in the photos.

You may extract control from an orthomosaic with known accuracy. If available for your project area, you can load a suitable reference orthomosaic into the map and add control points to your historical imagery using this imagery for a visual reference.

One recommended source for projects in the United States is to load the NAIP image service from the ArcGIS Living Atlas. There are different years available, so you may need to view the oldest NAIP layer.

Many users also reference the Esri World Imagery basemap to extract control points. Since Esri collects this imagery from a variety of different sources, the horizontal accuracy of this imagery is not reported. Consult this service for more information about the accuracy of the World Imagery basemap.

When extracting control from existing imagery, be sure to measure points that are on the terrain, not elevated features such as tops of buildings. It is also better to select points that are on flat terrain—they are likely to be more accurate and can also possibly be used as vertical control.

If you are processing photos from multiple years, start by processing the most recent date and applying your best available control. Then, use the orthomosaic output you just created as control for the previous year; continue in this manner until all your images are processed. For example, you would process 2020 imagery, use it as control for 2019, then use the processed 2019 imagery as control for 2018.

Sources of vertical control

Note that control points extracted from the map will determine Z values using the ground elevation source currently loaded in the map. By default, the ortho mapping workspace loads the World Terrain service into the map, and this layer will provide Z values for control points.

screenshot of the World Elevation service as the default elevation surface

If you have an alternative terrain dataset for this area, it can be added into the map prior to control point extraction (click the Add Data button and select Elevation Source).

screenshot of the interface for adding an alternate elevation source

It’s important to ensure correct vertical reference for GCPs. If you are using an alternative DEM for vertical control, ensure the units are correct for your project coordinate system (typically meters vs. feet). If you need to rescale vertical units, you can add an arithmetic raster function to apply a vertical multiplier to the DEM values.

Also be sure to determine if the vertical reference for your DEM is a geoid (sea level, to provide orthometric height) or ellipsoid. It is uncommon for a DEM to reference ellipsoidal height, but if you have this case, you can add an arithmetic raster function to apply a vertical offset to the DEM values.

Entering control points

With a suitable reference image in the map, you’ll need to enter and link to control points.

For each control point added into the table, selecting that control point will populate the lower portion of the UI with the list of images that (may) contain that point. Control points are measured (or linked) in this graphical user interface to show the pixel location for the point in each image.

When the first image is linked, ArcGIS Pro will search in neighbor images and automatically link other images if possible. Those images successfully linked will show a blue “+” sign in the GCP user interface—for example, in the following screenshot, all images except DY-27-15 were automatically linked.


It is important to ensure that the same terrain model used for extracting the ground control is used to generate the ortho photos. This does not apply if a DEM will be generated from the adjusted images.

Screenshot pointing out the button for addding GCPs in the GCP manager

Screenshot showing the images that have been linked in the GCP user interface

It’s recommended to view the location of each GCP link to ensure accuracy—each link may be edited if necessary.

The number of control points required depends on the accuracy required and the density of the tie points that were collected, which is affected by the quality of the imagery, image content, and overlap between frames. In traditional photogrammetric projects, ground control would be placed approximately every four frames. It is especially important to have control at the extremities of a project, since this is where errors will quickly extrapolate. In many cases it may be helpful to add the ground control in an iterative manner. First, add a few ground control points, then do the block adjustment. This should improve the accuracy of the block and make it easier to find additional control points. Ground controls must be determined and measured in overlapping areas of the block being processed.


Currently, the GCP Manager has option to define points to be used for Control or as Check points. If you want to use some control only as Horizontal control, then set the Z accuracy to Zero. This will not control adjustments to Z values, and will only report residuals in XY. The same may be done for vertical control by setting XY accuracy to Zero.

Using check points to measure accuracy

Note that control points are used to control the block adjustment process. Although the processing report will show residual errors for the calculated locations of these points, this does not equate to the overall accuracy of the final product.

To generate an independent measure of accuracy, a separate set of points, called check points, are used to measure errors after the block adjustment. (The check points are not used within the block adjustment calculations.)

Presuming you can identify enough suitable points, enter all GCPs into the ortho mapping project. After the measurement (linking) process is completed, but before running the final block adjustment, some of the GCPs are converted to check points (select and right click to change mode).

Screenshot of the option to change to check point in the GCP Manager

Check points are then withheld from the block adjustment and a summary of project accuracy is reported for check points in the processing report.

Screenshot of the adjustment report, with checkpoint accuracy summarized

Proceeding without ground control

If it is not possible to apply suitable control as described above, you can omit the ground control step, perform a free adjust block adjustment, and create an orthomosaic that may have limited accuracy.

In this case, it is better to let the system generate a terrain model and use that than it is to use an existing terrain model that may have little relation to the image locations. You could then use georeferencing tools to adjust your orthomosaic to ensure the correct scale and achieve best alignment with your GIS data (or an Esri basemap).

Finalizing the block adjustment

After control points have been entered and linked to photos, you will need to re-run the block adjustment to apply the control to the project, then update the image collection terrain model.

Note that when the configuration of the ortho mapping workspace is set to aerial scanned, the DTM is not applied within the mosaic dataset until you specifically define it.

Updating the image collection terrain model

Even if you've got a good block adjustment result, the resulting orthomosaic may still have poor accuracy until you update the image collection with a suitable DTM.

The accuracy of the DEM has a significant effect on the accuracy of the resulting orthophotos. In the nadir region of each frame, the accuracy of the DEM has limited effect, but at edge of the frame the error in the orthophoto can match the error in the terrain model. It is also important to ensure that the same terrain model that was used for extracting the ground control is used to orthorectify the imagery.

Use a preexisting DTM

If you already have a suitable DTM, you can use that to update the image collection. In many cases, especially for smaller-scale imagery, you can export a local DTM file from the World Elevation service in the ArcGIS Living Atlas to use.

On the Output menu on the ribbon, click Custom, then select only the Orthorectify Images option.

Screenshot of the Custom wizard button

Screenshot of the orthomosaic options in the Custom wizard

On the next page, either select Use workspace’s reference DEM (if you defined the desired final DTM at project setup), or navigate to an appropriate bare earth DTM (such as World Terrain available from the ArcGIS Living Atlas).


The imagery must be aligned with the DTM to generate a good quality orthorectified result. The World Terrain service is a suitable DTM for a scanned film project, but if your mosaic is misaligned from its proper location more than 10 meters, you will need to have control points in your project or consider extracting a DTM from the imagery.

Screenshot of the interface for choosing a DTM to apply to your image collection

Generate and use a DTM from the imagery

If the accuracy of the existing terrain model is not sufficient or if the terrain has changed significantly, then you can use ortho mapping tools to generate a terrain model. The advantage of generating and using a terrain model from the imagery after block adjustment is that the accuracy of the resulting ortho imagery will not be related to inaccuracies in the original terrain model.

In this case, refer to Extract DEMs from the imagery, where you can use the custom menu to first extract a DEM (choose type=DTM) and then apply it to the image collection.

Presuming good results after defining the image collection DTM, you are ready to use the existing mosaic dataset directly or generate persisted output products.