- I have a point Feature Class and a polygon Feature Class. For the purpose of this discussion let's assume THOUSANDS of points and TWO polygons. The points have a unique identifier, and any number of points can have the same unique identifier.
- Counting the number of points within the polygons is not what I'm after. I want to count the number of points with a unique ID (like barcode for example) in Polygon 1 that are also found within Polygon 2 (and also the inverse, unique detection in Polygon 1 not in 2 and unique detections in 2 not 1).
- This applies to animal tracking. An animal tracklog is detected in area A and also detected in area B, based on the barcode in an attribute field.
- What I first did was a spatial join, whereby the point Feature Class was the target layer and the polygon layer the join layer. This gives a column in the point Feature Class with the Polygon_ID.
- I then used Summary Statistics to produce an output table that gives me Polygon_ID, barcode and count (using PolyID as the CASE). This is great because for each unique barcode I now have a maximum of two rows, one for Polygon 1 and one for Polygon 2 (the count is largely irrelevant for my purposes).
- However, using this summary table I now want to somehow count the number of unique barcodes that are assigned Polygon ID 1 and Polygon ID 2. Any suggestions?