Visualising One Million Building Footprints with GeoArrow and

Kyle Barron demonstrates how to use to render data in GeoArrow format, starting with a GeoJSON dataset of one million building footprints in Utah.

We’ve been able to make web maps with GeoJSON data for some time now, and converting GeoJSON to GeoArrow and preparing the data for requires extra development work, so why would you want to use GeoArrow? The short answer: It’s incredibly fast.

GeoArrow overlaps almost exactly with the format that expects! So can render from GeoArrow’s physical representation very efficiently. For point and linestring geometry types, the underlying coordinates array can essentially be copied directly to the GPU with no CPU processing required. For polygon geometries, only polygon tessellation still needs to happen on the CPU.

We’re looking at the not-so-distant future of web mapping here, when we can render millions of features onto a web map without a noticeable impact on performance.