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Stop using zip codes for geospatial analysis (2019)

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Re: Stop using zip codes for geospatial analysis (2019)

#3
Great article. Zip codes can be super expedient. But you have to be self aware that for many uses cases they function WORSE than a random grid. Because they have built-in aggregation of a central post office(and surrounding) with a certain radius of rural/less dense surrounding.

So for example, if you are sorting “rural zips” vs “urban zips” it will only take you so far, and may actually be harmful.

Same goes with MSAs/DMAs (media markets). These have to be used for buying media, but for geospatial analysis they are suboptimal for the same reasons.

Easiest way to dip your toe into the water of something better is to start with A-D census counties.

Re: Stop using zip codes for geospatial analysis (2019)

#4
To put it in plain mathematical language, ZIP codes are not defined as polygons [0]. The consequence is that performing any analysis with an assumption that ZIP codes are polygons is bound to be error-prone.

0: https://manifold.net/doc/mfd8/zip_codes_are_not_areas.htm

Re: Stop using zip codes for geospatial analysis (2019)

#10
post #6

Instead of zip use the following? Use Addresses Use Census Units Use your own Spatial Index Why not lat, long?

It depends on if you want to model a point or an area. lat/lng gives you a point, but you often want an area to, for example, count how many people are in that area. A spatial index like H3 provides a grid of area units.
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