2

I have a large shapefile of GPS points. Each point has a unique point ID number, but they are all part of different clusters, where each cluster has a unique cluster ID number (there is no overlap between clusters). For example, points 1, 2, and 3 are part of Cluster 100 and points 4, 5, and 6 are part of Cluster 200. I have done a Select by Location query of these points based on their proximity to a road feature class, and now have about 1400 points selected. I would now like to select any additional points that share a common Cluster ID to the already selected points. For example, say I captured points 1 and 2 of Cluster 100 with the locational selection query, how would I capture point 3 of Cluster 100 as well, in an efficient query? Or is there a way to have a subquery in the Select by Location query that would look at the cluster ID attribute?

Improve this question

2 Answers 2

Reset to default
1

Sounds like you can use the 'Select by Attributes' tool with the selection method set to 'Add to Current Selection'

enter image description here

Then just build your query to select all the points with a Cluster ID for the group that you're interested in. That will add any that got missed by the spatial query.

Improve this answer
2
  • Is there a query that can efficiently identify 100+ unique cluster IDs?
    – oatmeal
    Jan 5, 2017 at 22:36
  • I'm afraid I don't understand your question. If you just want to see all the unique values present in a field just select the field in the dialog box and click the "Get Unique Values" button. If you need to do things automatically - as in get the computer to do this for you - then you're looking at using a python script or maybe a model. That is a whole other ball of wax.
    – Kevin
    Jan 6, 2017 at 16:37
0

Here's what I ended up doing: After doing my Select by Location query, I made a selectional layer of those points within the defined proximity of the road. I then ran a Frequency tool with the Cluster ID as the only frequency field and saved the table. I then joined this frequency table to the full set of points based on the Cluster ID, keeping only matching records. I then started an editing session and deleted all the points indicated in the joined table.

Improve this answer

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.