And you may not want to use zip codes for similar reasons.
For instance, if you have a list of conference attendees and you want to show a map of where the attendees came from, you probably don’t want to show their actual location due to privacy issues. Obscuring the source.Īn interesting aspect of this data aggregation is that you can use it to obscure the source of the data for privacy reasons. They only see data appropriate at the given scale and never struggle to discern the data. Then you can create multi-scale hexagons that turn on as you zoom in or out on the map, giving your end-users a more dynamic experience. (Use the “Summarize within” analysis tool in ArcGIS Desktop or ArcGIS Online to aggregate the data.)ĭepending on the extent or your source data, you may want to do this aggregation at a couple of different scales. If your data is represented as lines or polygons you can also overlay the data, but you should be aware that you are introducing some interpolated data into your results. This is very easy for point data, as you take all the points within a single hexagon and specify how you want to aggregate each field in the point data (maximum, minimum, average, count, etc.). You simply overlay your source data (for example, a set of points representing bridge locations) and a layer of hexagons, and then summarize the values that intersect your hexagons. You just need more detailed data than the scale of your hexagons and then you aggregate that data into your hexagons. How do you assign data to hexagons?Īssigning data to hexagons is pretty easy. Right: 20 km rectangles showing density of bridges. Left: 20 km hexagons showing density of bridges.
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