Finding missing features after generalisation

After a long day a number of ideas have popped into my head. I'm sure greater minds than I will have other ideas...

 

 

So my thought would be to add the two Readers (Orig and Generalized) and use them as inputs into a  Matcher based on some similar attribute (id for example). Output only the Not_Matched features and the Generalized features (direct from Reader) to the output.

 

 

This should give you all Generalized features plus any original features that didn't make it through the Generalizer in the first place. You could also use the Duplicate remover right before the writer if for whatever reason there were duplicate Generalized features but to my somewhat addled brain that is probably unlikely anyway.

 

 

Good luck.

Not mentioned here (but obvious?) is the ChangeDetector. Also worth looking at is the GOIDGenerator. Not sure how this deals with similar geometries, however it might be usefull.

 

 

Even though you have a generalized dataset, is the start and end point of a line still the same? If yes, you can extract the start and end point of a line as a "unique ID" and then compare these. 

 

 

Good luck!

Hi,

 

 

If the original features have unique ID as an attribute and the generalized features keep the ID, FeatureMerger may work too.

 

  Add 2 readers, one for the generalized features, one for the original features. Put a FeatureMerger. Connect the generalized reader to REQUESTER port. Connect the original reader to SUPPLIER port. Set the unique ID attribute to Requester / Supplier Join Attribute of the FeatureMerger. Then, all generalized features are going to COMPLETE port, the missing original features are going to UNREFERENCED port.

 

  In addition, because some attributes may have been changed after generalization, it might be better to remove the attributes except ID of the original features before connecting to FeatureMerger for saving attributes of generalized features.