Coordinate precision

Choosing the right #coordinate #precision matters (there’s an xkcd about it!): Too little distorts your data, too much bloats it unnecessarily. This interactive tool by #Mapbox makes this tradeoff visually understandable.
Author

Ralph Straumann

Published

February 24, 2026

Besides identifying the correct CRS1 of one’s (or more often: others’) datasets correctly, choosing an appropriate level of coordinate precision (for example, when converting to GeoJSON or WKT2) can present pitfalls in data management.

There’s even an xkcd about it (you know it’s serious when it’s in the xkcd canon):

Coordinate precision. Explainer here. (source: xkcd)

I’ve recently come across an interactive (maybe a bit less humorous, but more practical) introduction to this topic, by Mapbox: “Understand GeoJSON coordinate precision” (direct link to the full-screen map).

This tool features an interactive map displaying a grid of regularly spaced points representing single-digit increments of coordinate precisions overlaid on New York City. As you vary the coordinate precision using a slider, the map dynamically updates to show how the points represent a smaller or larger area. It’s tricky to describe but instantly intuitive when you see it:

Coordinate precision 2, 4, and 6 (from the top). The last map (which cannot be zoomed in further) shows a zebra crossing / crosswalk under the point raster. (source: Mapbox)

The Mapbox tool is a nice way to visualize how coordinate precision influences the representation of spatial data. And it can help you choose a suitable precision, without unnecessarily bloating your data.

Footnotes

  1. Coordinate reference system.↩︎

  2. Well-Known Text, a markup language for representing vector geometries.↩︎