BYTETOOLS

GeoJSON Simplifier

Shrink GeoJSON with the Ramer-Douglas-Peucker algorithm at a tolerance in metres, and see the before-and-after outline and the file size saving.

Drop a .geojson file here, or click to browseSimplified locally — the file is never uploaded

Paste a FeatureCollection or drop a .geojson file, then set a tolerance in metres to thin out the vertices.

What is the GeoJSON Simplifier?

This simplifier thins out the vertices in a GeoJSON file using the Ramer–Douglas–Peucker algorithm. You set the tolerance in metres, which is converted into degrees at the mean latitude of your own data, so 25 m means 25 m whether the file covers Norway or Kenya.

  • Ramer–Douglas–Peucker simplification with the tolerance set in real metres
  • Optional radial-distance pre-pass that removes clustered points before the main run
  • Before-and-after outlines drawn on one canvas, with the surviving vertices marked
  • Reports points before and after, percentage removed and file size saved
  • Polygon rings stay closed and never drop below the four positions GeoJSON requires
  • Properties, feature ids and extra members are copied through unchanged
  • Runs entirely in your browser — no upload, and no server-imposed size limit

How to use the GeoJSON Simplifier

  1. 1

    Drop a .geojson file onto the box, or paste the FeatureCollection into the text area.

  2. 2

    Set the tolerance in metres, or use the quick 5 m to 250 m buttons.

  3. 3

    Leave the radial-distance pre-pass on for GPS tracks; turn it off for hand-drawn boundaries.

  4. 4

    Compare the grey original outline against the blue simplified one, and check the point counts.

  5. 5

    Copy the result or download the smaller .geojson file.

About the GeoJSON Simplifier

This simplifier thins out the vertices in a GeoJSON file using the Ramer–Douglas–Peucker algorithm. You set the tolerance in metres, which is converted into degrees at the mean latitude of your own data, so 25 m means 25 m whether the file covers Norway or Kenya. An optional radial-distance pre-pass strips clustered GPS points first, which makes big tracks far faster to process.

It exists because a raw GPS track or a detailed administrative boundary carries far more detail than a web map can ever draw. Cutting a 40,000-point coastline down to 2,000 points typically looks identical at normal zoom levels while loading many times faster on a phone.

The before-and-after outlines are drawn on top of each other so you can see exactly what the tolerance did, and the point count and file size saving are reported for both. Polygon rings are re-closed after simplifying so the output stays valid, and properties travel through untouched. Everything runs in your browser and nothing is uploaded.

Frequently asked questions

What does the Douglas-Peucker algorithm actually do?

It draws a straight line between the first and last point of a shape, finds the point furthest from that line, and keeps it only if it is further away than your tolerance. Then it repeats on each half. Points that barely deviate from the line get dropped, so the overall shape survives while the detail goes.

What tolerance should I use?

It depends on the zoom you will draw at. For a country-level map 500–1000 m is fine; for a city map 5–25 m keeps street-level shape; for a GPS track 5–10 m removes noise without cutting corners. Try a value, look at the overlay, and adjust.

Will simplifying break my polygons?

Not here. Rings are re-closed after simplification and any ring that would drop below four positions is left untouched and reported. Very aggressive tolerances can still make adjacent polygons stop sharing an edge, which is a limitation of per-feature simplification rather than of this tool.

How much smaller will my file get?

Commonly 60–95% for GPS tracks and detailed boundaries, because those formats record far more points than a screen can show. The tool measures both the vertex reduction and the byte saving, and rounding coordinates on top of that usually saves as much again.

What is the radial-distance pre-pass for?

GPS receivers log points on a timer, so standing still produces a tight cluster of near-identical positions. The pre-pass drops points closer together than half the tolerance before Douglas–Peucker runs, which both cleans up that noise and speeds the main pass up considerably.

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