I would try the change detector or the matcher first.

 

Itay

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I looked at those but the problem is that they check for exact geometry matches.  For instance, I have a line that is 1000ft long in one dataset and that line is split into maybe 50 segments in the other dataset.  The ChangeDetector shows 1 feature deleted and 50 added.

 

 

What I am after is the "leftover" features that are not included in the segmented dataset.  So the 1000ft line, for example, may have a few segments that are not in the other dataset.  I want to identify those segments.

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Hi,   How about the following trick?   Class 'A' --> LineJoiner --> Bufferer --> SpatialFilter rBASE]   Class 'B' --> SpatialFilter eCANDIDATE]   LineJoiner joins 'A' lines to form longer lines. Set very small value (e.g. 0.000001) to Bufferer's "Buffer amount" parameter, Bufferer will create long-slender polygons surrounding the joined lines. Select "CONTAINS" at SpatialFilter's "Tests to perform" parameter. Run the workspace. 'B' segments missing on 'A' lines will go to FAILED] port of SpatialFilter.

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I imagine that the segmented dataset lines have more than 2 coordinates so I would try the following:

 

• Segment the non segmented dataset (1000ft line) with the chopper set to 2 vertices.
• Use a spatial relator with the newly segmented dataset as base and the segmented dataset as candidate, test for equals.
• Use a tester or testfilter to filter out the newly segmented lines which are not equal to the originally segmented dataset (_related_candidates != 1)
• recombine the new segments if needed using the linejoiner

 

Hope this helps.

 

 

 

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How about an intersector with SeparateColinearSegment = YES? You filter the output list and you should get what you need.

 

I would use a coordinate rounder beforehand to make sure you work with the appropriate tolerance.

 

 

JP

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Or, after splitting 'B' lines into segments, CommonSegmentFinder may be applicable.

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You could try buffering the line segments in "B" with a butt end then use the clipper.  Any thing "Clipped_Outside is your missing sections in "A"

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Thanks everyone for all the responses!  I tried a number of the different ideas and most of them worked but there were some lines that didn't make it through that should have.  The best result set for me was to use a buffer of 0.000001 on data set "B" with end cap set to None.  I then clipped data set "A" and the Outside + Clipped Outside ports gave me the data I was looking for.

 

 

Thanks again,

 

 

Jerrod

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I was able to perform a geographic subtraction using two Choppers, a PointOnAreaOverlayer, and a Matcher.

 

 

Step 1:  Send the first linear dataset to a chopper with vertex = 1.  This will convert your linear dataset to a point dataset.

 

 

Step 2:  In parallel, send the first linear dataset to a chopper with vertex = 2.  This will convert your multi-segment lines to simple segments.

 

 

Step 3.  Send the second linear dataset and the point data from Step 1 to a PointOnAreaOverlayer.  This will split all of the lines in the second linear dataset at the nodes of the first linear dataset.

 

 

Step 4.  Send the line ouptput from the PointOnAreaOverlayer and the line output from the chopper in Step 2 to a Matcher.  The Matcher will find all instances where the line segments from the first dataset overlap with the line segments from the second dataset.

 

 

Step 5.  Send the Not Matched output from the Matcher to your Writer.

 

 

Dataset 1 => Chopper (vertex =1 ) => PointOnLineOverlayer (via Point)

 

 

Dataset 1 => Chopper (vertex = 2) => Matcher

 

 

Dataset 2 => PointOnLineOverlayer (via Line) => Matcher => Not Matched

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