I am looking to combine points based on their location that are in the same feature class. I have many points that are coded for individually from geotagged photos of homes. These points are in roughly the same place but there are multiple photos per home. All of these photos, and therefore points, are in the same feature class. I know I could use a spacial join, but that would involve separating out each duplicate photo into a separate feature class, a merge function, or snap tool but all of these methods would be too tedious for the magnitude of data and points I am working with. How can I combine these without separating them into different feature classes?
which will give you a polygon
If you want to stick with points you could take the centroid of the clusters, then spatially join your original points to the centroids.
Other suggestions would depend on what you want to do.... analysis? symbolize? etc
Thank you! I would love to stick with points and taking the centroid of each individually I think would be more time consuming than separating out the feature classes. The plan would be to symbolize the points in order to show some outside attributes of each home, once each is individual and not many points....
You don't need to take the centroid of each point. The tool aggregates the points, as they are clustered into a polygon based on a proximal distance. You take the centroid of those polygons, then join your data back to it