Cleaning up overlapping points

[ShauntDer-Grigorian]

I'm making a map of mining locations throughout the world for certain commodities using a shapefile acquired from the USGS, however after filtering out only the commodities that I'm interested in, I'm left with 310,000 points. I don't need to show every single last point since many of them aren't visible anyway. I came up with the idea of showing only 1 point for every 10 mile radius, but don't know how to achieve this. Does anyone know how to do this? If anyone has alternative ideas or suggestions, I would appreciate it greatly. Thank you.

[KristofVydt]

This is not the appropriate forum section ("Geocoding") for this question.

However, I think you should be able to obtain the desired result using
[1] the "Point To Raster" conversion tool (see http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/Point_to_Raster/00120000002z000000/ & http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/How_Point_To_Raster_works/001200000035...) that allows you to set your radius (actually raster cell size) ;
[2] the "Raster To Point" conversion tool (see http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//001200000007000000.htm) to convert back to point features.

If you need to keep original point feature attributes, you might have to do some additional steps to link them again.

Kristof Vydt
Esri Certified Desktop Associate
Esri BeLux

[KevinMayall]

Yes, this is not a geocoding problem/solution, but you should be able to do this without resorting to raster conversion.  The Integrate tool will move your points to the same location if they are within a xy tolerance (backup your data first!).  Then once they are located on top of each other, you can use Collect Events to create single point features with a count of the number of source features that are in the group.  Another approach is to create a Topology on the point data layer with an appropriate cluster tolerance - this seems to aggregate the points to a common location that respects the tolerance.  I haven't used this latter approach before though.