An ortho mapping workspace is an ArcGIS Pro subproject that is dedicated to ortho mapping workflows. It is a container within an ArcGIS Pro project folder that binds together all the resources and derived files that belong to a single image collection in one ortho mapping task. In particular, it contains an image collection to be adjusted, which is managed using the mosaic dataset data model, the generated ortho mapping products, internal files used in the adjustment process, and necessary information that manages the workspace.
You can copy or delete an ortho mapping workspace. You can have more than one ortho mapping workspace within a project, where each workspace opens its own map view. It is recommended that you use one project for each ortho mapping task. You can use multiple ortho mapping workspaces to manage the different versions of your ortho mapping tasks.
Create an ortho mapping workspace
You can create an ortho mapping workspace from drone imagery, satellite imagery (with a Rational Polynomial Coefficient [RPC] camera model), digital aerial imagery, scanned aerial photography, or an existing mosaic dataset. The type of ortho mapping workspace defines the methods and algorithms that are used to process the image type. Choose the appropriate type when you create an ortho mapping workspace for your data. The New Ortho Mapping Workspace wizard on the Imagery tab allows you to create an ortho mapping workspace from a collection of images or an existing mosaic dataset, and it also allows you to import or add from an existing ortho mapping workspace.
The wizard guides you through the process of creating an ortho mapping workspace, in which you enter information to define your project, such as name, description, and workspace type, Ortho Mapping in this case. Depending on the Sensor Data Type setting of the workspace—for example, drone or satellite—the wizard pane presents appropriate options such as location of your source image collection, camera, or sensor model files, and spatial reference system.
There are several types of ortho mapping workspaces that can be created for your image data:
When you complete the New Ortho Mapping Workspace wizard, an Ortho Mapping folder appears in the project folder structure in the Catalog pane, and the List by Ortho Mapping Entities list view in the Contents pane allows you to view all the ortho mapping workspace entities created by the wizard.
The entities in the ortho mapping workspace vary depending on the type of workspace you created.
Entity Group | Entity | Description | Drone | Aerial-Digital | Aerial-Scanned | Satellite |
---|---|---|---|---|---|---|
Data Products | Digital Terrain Model (DTM) | Model of the ground or bare earth calculated from overlapping images. | ||||
Digital Surface Model (DSM) | Model of the surface, including above-ground features such as tree canopies and buildings calculated from overlapping images. | |||||
Orthomosaic | Mosaicked orthoimage | |||||
Solution Data | Solution Table | Stores the computed transformation information for each image. ImageID—Image identification number. This will be the same value as the OBJECTID field in the mosaic dataset footprint table. RMS—The average Root Mean Square error for all the solution points in each image. RMS is expressed in pixel units. Quality—The quality of the adjustment for each image. A value of 1 indicates perfect quality. | ||||
Solution Points | Contains all points resulting from the bundle block adjustment computation, such as the points in 3D ground coordinates. ImageID—The image identification number. This will be the same value as the OBJECTID field in the mosaic dataset footprint table. PointID— The block adjustment solution points derived from the corresponding tie points having the same PointID. Type—A coded field that indicates the coordinate space of the point:
Status— A coded field that defines whether the point is used in the block adjustment:
Residual—Residual error of the adjusted solution point. The unit is pixels. XResidual—Residual error in the x-direction of the adjusted solution point. The unit is pixels. YResidual—Residual error in the y-direction of the adjusted solution point. The unit is pixels. | |||||
Fiducial Table | Contains all fiducials detected and used to refine the interior orientation. ImageID—The image identification number. This will be the same value as the OBJECTID field in the mosaic dataset footprint table. ImageX—X fiducial coordinate in image space. ImageY—Y fiducial coordinate in image space. FilmX—X fiducial coordinate in film space. FilmY—Y fiducial coordinate in film space. Score—The pixel-matching quality for each image. Status—A coded field used by the Refine Interior Orientation pane when searching for unsolved images:
Residual—Residual error from transforming from film space to image space in the image. The unit is pixels. XResidual—Residual error in the X direction from transforming the fiducial from film space to image space. The unit is pixels. YResidual—Residual error in the Y direction from transforming the fiducial from film space to image space. The unit is pixels. | |||||
QA/QC Data | Overlap Polygons | Contains control point coverage in areas where images overlap. Here you can identify areas that need additional control points to improve block adjustment results. Control points include ground control points (GCPs), tie points, and check points. ImageID—Image identification number. This will be the same value as the OBJECTID field in the mosaic dataset footprint table. ImageID2— Image identification number of the image that overlaps with the corresponding ImageID. ID—A unique identifier for the overlapping images consisting of ImageID and ImageID2, delimited by a period. Count—The number of overlapping images assessed. PointCount—The number of control points in the overlapping area. PointCoverage—The percentage of the overlap area covered by control points. Multirays—The number of unique PointIDs or tie point sets in the overlap area. Mask—A coded field that indicates whether the overlap area will be used when computing tie points:
| ||||
Coverage Polygons | Contains control point coverage for each image in the image collection. Here you can identify areas that need additional control points to improve the block adjustment results. Control points include GCPs, tie points, and check points. ImageID—Image identification number. This will be the same value as the OBJECTID field in the mosaic dataset footprint table. Coverage—The percentage of image area covered by control points. Count—The number of control points in the image. Multirays—The number of unique PointIDs or tie point sets in the image. | |||||
Control Points | Ground Control Points | Points with known ground coordinates, usually generated from ground survey. | ||||
Check Points | Points with known ground coordinates that are used for assessing the accuracy of the adjustment process. These are ground control survey points not used in computing the photogrammetric solution. | |||||
Tie Points | Points representing pairs of pixels that correspond to the same location where images overlap. Tie points do not have known ground coordinates, but each has its own image coordinates in rows and columns. ImageID—Image identification number. This will be the same value as the OBJECTID field in the mosaic dataset footprint table. PointID—The point identification number. This value will represent the same point location over the various overlapped images Type—A code to define the type of control point that the row represents:
Status—A code to define the status of the point:
Score—A score that is generated by the matching algorithm, which is based on image correlation. The value range for the score is 0.0 to 1.0, where a score of 0 is the best match. Rays—The number of points that have the same PointID. V1 and V2—If the Type field is equal to 2 or 3 (GCP or check point), the values indicate the accuracy of the control points, expressed in meters:
If the x,y accuracy or z accuracy is not available, a value of -2 means that the accuracy is unknown. If you want the system to calculate the accuracy, type a value of -1 in the field. | |||||
Flight Data | Flight Path | The flight path of the drone imaging platform. | ||||
Camera Locations | Drone sensor location and pointing information at the moment of image capture, including latitude, longitude, altitude, and time. | |||||
Source Data | Image Collection | The mosaic dataset created to manage the source imagery for the ortho mapping workspace. |
To learn about adjusting your imagery, see Block adjustment.
Rename an ortho mapping workspace
When you open an ortho mapping workspace in ArcGIS Pro, it will create a map in the Maps container with the same name as the workspace name.
Note:
You can rename an ortho mapping workspace if it is a copy of an existing workspace and no additional processes have been run on the new copy.
Later, if you rename the workspace in the Ortho mapping container in the Catalog pane, it will not rename the map stored in the Maps container. The renamed workspace remains linked to the original map in the Maps container. As a result, you will see the following error when you try to open the attribute table of the mosaic dataset.
Additionally, you will see issues when opening the renamed workspace because it tries to load data using its original name.
In the Contents pane, you can see all previously working layers are moved to the Reference Data category with a broken source icon . You can resolve the issue by following the steps below.
- Remove the broken layers.
- Right-click Data Products, Solution Data, QA/QA Data and other existing related data, and click the Synchronize option.
The correct data will be linked to your renamed workspace and loaded into the map. This allows you to retain your existing map symbology.
- Alternatively, you can delete the related map in the Maps container.
When you open the renamed workspace, a new map will open using the renamed name with correct paths. However, since you are starting with a new map, everything you saved in the original map, such as symbology or other reference layers, will be lost.
Related topics
- Create an ortho mapping workspace for drone imagery
- Create an ortho mapping workspace for RedEdge or Altum imagery
- Create an ortho mapping workspace for satellite imagery
- Orthorectify a single satellite scene
- Create an ortho mapping workspace for digital aerial imagery
- Create an ortho mapping workspace for scanned aerial imagery
- Create an ortho mapping workspace from a mosaic dataset
- Block adjustment