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Distinctly identify dissolved object in a large dataset

  • 18 December 2017
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R
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Hi,

I am working on a use case of dissolving features that are touching (or share a common boundary) and also based on certain attribute criteria that these features need to fulfill.

While I was successful in doing that (I can say that by seeing samples of the output), I was also hoping if I could distinguish the actual dissolved features so that I have an accurate account of where the change happened, especially for a large dataset (a million polygons)

If someone can let me know that would be greatly helpful to test my work.

Thanks very much in advance

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Best answer by takashi 18 December 2017, 08:59

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takashi
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Hi @raghunaren, if you specify the "Dissolve Count Attribute" parameter in the Dissolver, every output feature will have a new attribute that store the number of features having been dissolved. If the count number is just 1, you can determine that the feature has not changed. Could this help you?

R
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Hi @takashi

Thanks for your very quick reply. Yes, it does help but the flow that i am using reaches the dissolver transformer at a juncture where the original polygon is broken down into multiple parts based on certain criteria, so the 'dissolve Count attribute' does not give me the desired number for me to find out the originally merged ones, meaning there are just too many false positives.

I know i might sound confusing here. I'll try to put up a detailed question on this one with my flow and a sample data if possible.

Thanks once again for a quick reply and sorry for a delayed acknowledgement.

jdh
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If you put a counter on your original features to get a uniqueID, and then in the Dissolver you generate a list with that uniqueID, you can use a listHistogrammer on that list to see if the resulting dissolved polygon contains parts of more than one original feature.

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