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Compute Control Points and Fiducials and Tie Points, Generate Block Adjustment Report

Husam Jubeh
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Compute Control Points and Fiducials and Tie Points, Generate Block Adjustment Report Tools

Compute Control Points

How to Compute Control Points Tool in Arc Toolbox ArcMap ArcGIS??

Compute Control Points Tool
Compute Control Points

Path to access the tool

:

Compute Control Points Tool, Ortho Mapping Toolset, Raster Box, Data Management Tools Toolbox

 

Compute Control Points

Creates the control points between the mosaic dataset and the reference image. The control points can then be used in conjunction with tie points to compute the adjustments for the mosaic dataset.

1.    Input Mosaic Dataset

The input mosaic dataset that will be used to create control points.

2.    Input Reference Images

The reference images that will be used to create control points for your mosaic dataset. If you have multiple images, create a mosaic dataset from the images and use the mosaic dataset as the reference.

3.    Output Control Point Table

The output control point table. This table will contain the control points that were created.

4.    Similarity (optional)

Specifies the similarity level for matching tie points.

  1. 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.
  2. MEDIUM—The similarity criteria for the matching points will be medium.
  3. 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.

5.    Output Image Features (optional)

The output image feature points table. This will be saved as a polygon feature class. This output can be quite large.

6.    Point Density (optional)

The number of tie points to be created.

  1. LOW—Set the density of points to be low. This will create the fewest number of tie points.
  2. MEDIUM—Set the density of points to be medium. This will create a moderate number of points.
  3. HIGH—Set the density of points to be high. This will create the highest number of points.

7.    Point Distribution (optional)

Specifies whether the points will have regular or random distribution.

  1. RANDOM—Points are generated randomly. Randomly generated points are better for overlapping areas with irregular shapes.
  2. REGULAR—Points are generated based on a fixed pattern. Points based on a fixed pattern use the point density to determine how frequently to create points.

8.    Image Location Accuracy (optional)

Specifies the keyword that describes the accuracy of the imagery.

  1. LOW—Images have a large shift and a large rotation (> 5 degrees).The SIFT algorithm will be used in the point-matching computation.
  2. MEDIUM—Images have a medium shift and a small rotation (<5 degrees).The Harris algorithm will be used in the point-matching computation.
  3. HIGH—Images have a small shift and a small rotation.The Harris algorithm will be used in the point-matching computation.

9.    Area of Interest (optional)

Limit the area in which tie points are generated to only this polygon feature class.

Compute Fiducials

How to Compute Fiducials Tool in Arc Toolbox ArcMap ArcGIS??

Compute Fiducials Tool
Compute Fiducials

Path to access the tool

:

Compute Fiducials Tool, Ortho Mapping Toolset, Raster Box, Data Management Tools Toolbox

 

Compute Fiducials

Computes the fiducial coordinates in image and film space for each image in a mosaic dataset.

Fiducials are marks, normally four or eight, in aerial photos used as reference. They are an important factor for determining the image transformation from image to film known as interior orientation. This tool is used to automatically find the image coordinates of the fiducials for each images in a mosaic dataset based on a user-provided fiducial template file. A fiducial template file is a table that has required fields for storing either fiducial pictures or paths to the pictures. For more information about fiducials, see Refine Interior Orientation Using Fiducials.

1.    Mosaic Dataset

The mosaic dataset created from scanned aerial photos using scanned raster type or frame camera raster type.

2.    Query Definition (optional)

A query definition string that defines a subset of rasters for computing fiducials.

3.    Output Fiducial Table

The output table that stores all the fiducial coordinate information in image and film space.

4.    Fiducial Templates (optional)

The fiducial template table that contains required fields for storing fiducial pictures and other properties.

5.    Film Coordinate System (optional)

A keyword that defines the film coordinate system of the scanned aerial photograph. It is used in computing fiducial information and affine transformation construction.

  1. NO_CHANGE —Maintain the coordinate system of the mosaic dataset. Do not change the film coordinate system of the scanned aerial photograph. Maintain the coordinate system of the mosaic dataset.
  2. X_RIGHT_Y_UP—The origin of the scanned photo's coordinate system is the center, and positive X points right and positive Y points up.
  3. X_UP_Y_LEFT—The origin of the scanned photo's coordinate system is the center, and positive X points up and positive Y points left.
  4. X_LEFT_Y_DOWN—The origin of the scanned photo's coordinate system is the center, and positive X points left and positive Y points down.
  5. X_DOWN_Y_RIGHT—The origin of the scanned photo's coordinate system is the center, and positive X points down and positive Y points right.

Compute Tie Points

How to Compute Tie Points Tool in Arc Toolbox ArcMap ArcGIS??

Compute Tie Points Tool
Compute Tie Points

Path to access the tool

:

Compute Tie Points Tool, Ortho Mapping Toolset, Raster Box, Data Management Tools Toolbox

 

Compute Tie Points

Computes the tie points between overlapped mosaic dataset items. The tie points can then be used to compute the block adjustments for the mosaic dataset.

1.    Input Mosaic Dataset

The input mosaic dataset that will be used to create tie points.

2.    Output Control Point Table

The output control point table. The table will contain the tie points created by this tool.

3.    Similarity (optional)

Specifies the similarity level for matching tie points.

  1. 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.
  2. MEDIUM—The similarity criteria for the matching points will be medium.
  3. 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.

4.    Input Mask (optional)

A polygon feature class used to exclude areas you do not want in the computation of control points.

A field with a name of mask can control the inclusion or exclusion of areas. 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.

5.    Point Density (optional)

The number of tie points to be created.

  1. LOW—Set the density of points to be low. This will create the fewest number of tie points.
  2. MEDIUM—Set the density of points to be medium. This will create a moderate number of points.
  3. HIGH—Set the density of points to be high. This will create the highest number of points.

6.    Point Distribution (optional)

Specifies whether the points will have regular or random distribution.

  1. RANDOM—Points are generated randomly. Randomly generated points are better for overlapping areas with irregular shapes.
  2. REGULAR—Points are generated based on a fixed pattern. Points based on a fixed pattern use the point density to determine how frequently to create points.

7.    Image Location Accuracy (optional)

Specifies the keyword that describes the accuracy of the imagery.

  1. LOW—Images have a large shift and a large rotation (> 5 degrees).The SIFT algorithm will be used in the point-matching computation.
  2. MEDIUM—Images have a medium shift and a small rotation (<5 degrees).The Harris algorithm will be used in the point-matching computation.
  3. HIGH—Images have a small shift and a small rotation.The Harris algorithm will be used in the point-matching computation.

8.    Output Image Features (optional)

The output image feature points table. This will be saved as a polygon feature class. This output can be quite large.

Generate Block Adjustment Report

How to Generate Block Adjustment Report Tool in Arc Toolbox ArcMap ArcGIS??

Generate Block Adjustment Report Tool
Generate Block Adjustment Report

Path to access the tool

:

Generate Block Adjustment Report Tool, Ortho Mapping Toolset, Raster Box, Data Management Tools Toolbox

 

Generate Block Adjustment Report

Generates a report after performing ortho mapping block adjustment to a mosaic dataset. The report is critical in evaluating the quality and accuracy of the ortho mapping products.

1.    Input Mosaic Dataset

The input mosaic dataset path.

2.    Input Solution Table

The associated solution point table after block adjustment.

3.    Input Solution Points

The solution point feature class.

4.    Output Report

The output ortho mapping report file path and name. The supported output format for a website is HTML.

5.    Input Control Points for Adjustment (optional)

The associated control points table, which may include tie points and ground control points.

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