The parameters used in computing the block adjustment are defined in the Adjustment Options dialog box. The appropriate adjustment options are presented depending on the type of workspace defined when you set up your ortho mapping project. For example, RPC triangulation is performed for satellite images and frame triangulation is performed for aerial images.
The block adjustment settings specific for satellite imagery and digital aerial imagery are described below. These parameters are used in tie point or ground control point (GCP) computation, and computing the block adjustment.
For more information about adjustment options for drone and scanned imagery, see Adjustment options for drone and scanned imagery.
Image Location Accuracy
The inherent positional accuracy of your imagery depends on the sensor viewing geometry, type of sensor and level of processing. Positional accuracy is usually described as part of the imagery deliverable. Choose the keyword that best describes the accuracy of your imagery.
Images have a large shift and a large rotation (more than 5 degrees). The scale invariant feature transform (SIFT) algorithm will be used in the point matching computation.
Images have a medium amount of shift and a small rotation (less than 5 degrees). The Harris algorithm will be used in the point matching computation. This is the default.
Images have a small shift and a small rotation. The Harris algorithm will be used in the point matching computation.
Choose the tolerance level for matching tie points between image pairs.
The similarity tolerance for the matching imagery pairs will be low. This option will produce the most matching pairs, but some of the matches may have a higher level of error.
The similarity tolerance for the matching pairs will be medium. This is the default.
The similarity tolerance for the matching pairs will be high. This option will produce the least number of matching pairs, but each matching pair will have a lower level of error.
The relative number of tie points between image pairs to be created.
This produces the fewest number of tie points.
This produces an intermediate number of tie points. This is the default.
This produces the most tie points.
Determines whether the output points will have a regular or random distribution.
- Random— Points are generated randomly. Randomly generated points are better for overlapping areas with irregular shapes. This is the default.
- Regular—Generates points based on a fixed pattern.
Mask polygon feature
A polygon feature class used to exclude areas you do not want used in computing tie points.
In the attribute table of the feature class, the mask field controls the inclusion or exclusion of areas for computing tie points. A value of 1 indicates that the areas defined by the polygons (inside) will be excluded from the computation. A value of 2 indicates the defined polygons (inside) will be included in the computation while areas outside of the polygons will be excluded.
Compute ground control points
You can use a reference image to calculate GCPs. When choosing a reference image for GCP computation, make sure your reference image has good georeferencing quality in terms of geopositional accuracy and clarity, and the resolution is similar to your source imagery. For example, the default ArcGIS Online World Imagery Service may be a good reference for computing GCPs for your satellite data, but will likely not be a good reference for high resolution and highly accurate aerial imagery.
The adjustment options for Compute ground control points include the Reference Image which is the source image you want to base your ground control points on, and the parameter settings similar to those above:
- Image Location Accuracy
- Point Similarity
- Point density
- Point Distribution
Tie points with a residual error greater than the Maximum Residual value will be not be used in computing the adjustment. The measurement unit of the residual is pixels.