I have point data, where one point represents one 1 storm water outfall, looks like this:

enter image description here

(point data is across all of Long Island, New York).

I am having a bit of difficulty finding the best tool to create a raster density map. Essentially I want to use a density layer in a weighted overlay model (an area with high density of storm water outfalls would be less suitable...). I do not think I need to use Hot Spot Analysis because I am only interested in high v low density and not if they are actually statistically different from each other. I also have tried point density tool but I am having trouble figuring out the inputs (like radius length and cell size, etc).


2 Answers 2


This may be easier if you think of it in separate steps: first calculate the quantitative density, then reclassify that result into "high" and "low."

The Point Density tool inputs will be:

  • Input point features: your outfall points
  • Population field: Use NONE for this, because each point is being counted once. (If a point could represent multiple instances, e.g. if points represented people in a household, then this would be where to select the relevant count field. That doesn't apply here.)
  • Output raster: location for the output raster
  • Output cell size: This is optional, but will let you control the cell size of the output raster. The smaller the cell, the more refined the results, but the bigger the raster file.
  • Neighborhood: This value indicates how large of a neighborhood the tool will search for points. For example, a circle neighborhood of 5 meters (radius 5, units "Map" [assuming your map is in meters, here]), the tool will count all points that fall within a 5 meter radius circle around each cell.

Once you've got that, you can either use symbology to simply visualize the values as high/low, or you can run it through the Reclassify tool to get a raster of high/low data.


I think Point Density makes the most sense. I'd set the population field to "NONE" since you seem to want each point to count as one. The output will be a raster.

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