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I have a data set of points which are grouped into clusters like so:

enter image description here

I'd like to use ArcGIS or Python to create a point layer of the centroids of each cluster but I can't seem to find the right tools. I looked into hot spot analysis but it doesn't seem to apply, since my features aren't numerically weighted. I also tried the Integrate tool with a reasonable tolerance but I didn't see any changes. Any advice would be much appreciated.


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up vote 1 down vote accepted

To aggregate the clusters use grouping which produces a field SS_GROUP then for each unique SS_GROUP in the feature class create a convex hull then use Feature to Point to obtain the centroid of that particular cluster, with polygons you can specify inside to guarantee that banana shaped polygons produce a centriod that is inside the polygon but that wont matter too much as the convex hull cannot be banana shaped - that would be concave.

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Thanks for the tip - can I use Feature to Point with points as an input? I don't have polygons at the moment (those red circles are just for illustration). – Mapbert Jun 10 '14 at 23:40
Oh, I thought they were real. You want to cluster them and then get the centroid of that. – Michael Miles-Stimson Jun 10 '14 at 23:41
See edit. After grouping you may want to dissolve by SS_GROUP to a multipoint so it's one feature per group. I think that you can still create a convex hull over 1 multipoint feature. This would make iteration easier. – Michael Miles-Stimson Jun 10 '14 at 23:50
The Mean Center tool might also be useful here? I haven't used it but it looks like it's built for this purpose – Stephen Lead Jun 11 '14 at 0:12
I figured you could use Mean Center in conjunction with your SS_GROUP idea, using the case field to separate them into clusters (this may not give any advantages over the Feature to Point tool though) – Stephen Lead Jun 11 '14 at 0:15

ArcGIS has a few tools in the Spatial Statistics toolbox that might be useful.

Mean Center

Identifies the geographic center (or the center of concentration) for a set of features.

Median Center

Identifies the location that minimizes overall Euclidean distance to the features in a dataset.

Central Feature

Identifies the most centrally located feature in a point, line, or polygon feature class.

I think the Mean Center would be most useful here when used with the Case Field option.

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I see now that previous comments describe what I just posted at approximately the same time. – Fezter Jun 11 '14 at 0:18
The median / mean centre still needs the case field or it will create only one point. – Michael Miles-Stimson Jun 11 '14 at 0:21
Yes, that's true, and I mention that at the end of my answer. – Fezter Jun 11 '14 at 0:26

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