Match Control Points (Data Management)

Summary

Creates matching tie points for a given ground control point and initial tie point in one of the overlapping images.

The ortho mapping block adjustment workflow often involves adding ground control points for a more accurate adjustment. One ground control point is typically associated with a tie point in each overlapping image. When there are many overlapping images for one ground control point, manually creating tie points for each image is labor intensive.

Usage

• If the input control point set doesn't have a ground control point, the tool will fail.

• If the input control point set has ground control points but no initial tie point, the tool will fail.

• If no associated tie points are found, the input control point set remains unchanged, and a warning message appears that states no new tie points were found.

• An input control point set can be a JSON string object that is a list of points as shown below.

  Input control point sets

  [
  {
  "poinId": <id>,
  "x": 
  "y":
  "z":
  "xyAccuracy":
  "zAccuracy":
  "spatialReference":{<spatialReference>}, // default WGS84
  "imagePointSpatialReference": {}, // default ICS
  "imagePoints": [
  {"imageId": 
   "x":
       "y": 
      },
     …
     ]
  }
  ]

Syntax

MatchControlPoints(in_mosaic_dataset, in_control_points, out_control_points, {similarity})

Parameter	Explanation	Data Type
in_mosaic_dataset	The mosaic dataset that contains the source imagery from which the tie points will be created.	Mosaic Dataset; Mosaic Layer
in_control_points	The input control point set that contains a list of ground control point features and at least one initial tie point for each ground control point.	File; Feature Class; Feature Layer; String
out_control_points	The output control point features that contain ground control points.	Feature Class
similarity (Optional)	Specifies the similarity level for matching tie points. LOW —The similarity criteria for the two matching points will be low. This option will produce the most matching points, but some of the matches may have a higher level of error. MEDIUM —The similarity criteria for the matching points will be medium. HIGH —The similarity criteria for the matching points will be high. This option will produce the least number of matching points, but each matching will have a lower level of error.	String

Code sample

MatchControlPoints example 1 (Python window)

This is a Python sample for the MatchControlPoints tool.

import arcpy
mdpath = "c:/omproject/dronecollection.gdb/droneimgs"
initpointset = "c:/omproject/initialgcpset.json"
arcpy.MatchControlPoints_management(mdpath, initpointset, out_control_points="c:/omproject/matchedpointsets.shp", similarity="HIGH")

MatchControlPoints example 2 (stand-alone script)

This is a Python sample for the MatchControlPoints tool.

import arcpy
import json
mdpath = "c:/omproject/dronecollection.gdb/droneimgs"
initpointset = [
    {
        "x": -117.21684675264804,
        "y": 34.052400694386705,
        "z": 123,
        "pointId": 1,
        "imagePoints": [
            {
                "imageID": 7,
                "x": -5635883367.549803,
                "y": -26485513430.170017,
                "u": -5635883367.549803,
                "v": -26485513430.170017
            }
        ]
    }
]
arcpy.MatchControlPoints_management(
        mdpath, in_control_points=json.dumps(initpointset), out_control_points="c:/omproject/matchedpointsets.shp", similarity="HIGH")

Environments

Current Workspace, Parallel Processing Factor

Licensing information

• Basic: No
• Standard: Yes
• Advanced: Yes