Okay I've seen a ton of procedural earth generation blog posts. Random bisections, noise, fractals, erosion, watersheds, biomes and climate derivation, etc etc.

Why did the author of this one choose this approach rather than some other approach? What issues did they see with others that they decided to write their own? What's unique here?

Or maybe: What's the ultimate procedural earth generation technique? Is there anyone following these and comparing them?

Procedural generation's history mirrors that of symbolic AI - hand tuned, interpretable procedures that parallel the conceptual models we have of a generating process.

The choices the author made reflect the way they conceptualize the generating process. This is in contrast to a data-informed approach.

A data-informed approach to island generation would be a spatially auto-correlated generating model whose parameters were derived from real life data on islands. You would then be able to generate more in-distribution islands that were statistically similar to islands in the corpus.

You don't often see this in the proc-gen world because part of the fun is adding epicycles and various tunable knobs.

> Why did the author of this one choose this approach rather than some other approach? What issues did they see with others that they decided to write their own? What's unique here?

I'm not sure what you mean here. A lot (most?) procedural systems use Voronoi methods for procedural terrain generation, so this isn't some wholly novel solution. From what I can tell (haven't looked into it super deeply), it looks like Lloyd's algorithm is basically a variation of random bisections.