Stop using Perlin noise and use Simplex noise, or something even better, instead. We've come up with much, much better random noise generators in the last forty years, there's really no excuse to still use Perlin, especially in a setting where grid-aligned artifacts are going to end up in your geometry. It's a "learning about noise" algorithm, not a "using it for reals" algorithm.
Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
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Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#12It’s not a ‘topological’ map (though there is such a thing) — it’s a ‘topographical’ one. This is an error I see often.
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#13Most of the images don't seem to load for me
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#14To my geologist's eyes there is a fundamental flaw in this method: the assumption of randomness. All mountain ranges are driven up by lateral forces, so simply look on a satellite image to notice how they are made of ranges[0]. I do wonder if this propensity can be introduced to the code. [0] https://en.m.wikipedia.org/wiki/Zagros_Mountains#/media/File...
One thing you can do is take a DEM and match the distributions, then sample those distributions for new terrain. This can (in theory) reproduce any characteristic represented in the original signal. It can even be relatively efficient compared to things like erosion models if you constrain the number of octaves in the signal.
What's DEM?
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#15Earlier quoted context omitted.
One thing you can do is take a DEM and match the distributions, then sample those distributions for new terrain. This can (in theory) reproduce any characteristic represented in the original signal. It can even be relatively efficient compared to things like erosion models if you constrain the number of octaves in the signal.
What's DEM?
Digital Elevation Model (https://en.wikipedia.org/wiki/Digital_elevation_model)
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#16To my geologist's eyes there is a fundamental flaw in this method: the assumption of randomness. All mountain ranges are driven up by lateral forces, so simply look on a satellite image to notice how they are made of ranges[0]. I do wonder if this propensity can be introduced to the code. [0] https://en.m.wikipedia.org/wiki/Zagros_Mountains#/media/File...
In general, are aware of any physically-based long-term geological process models with real life fidelity as a goal, and that have a remote chance of being feasible for gamedev?
I imagine that, analogous to work done in weather forecasting, someone can shove DEM files into the pattern-matching engine of an AI, but I do wonder how feasible a completely algorithmic model will be.
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#17To my geologist's eyes there is a fundamental flaw in this method: the assumption of randomness. All mountain ranges are driven up by lateral forces, so simply look on a satellite image to notice how they are made of ranges[0]. I do wonder if this propensity can be introduced to the code. [0] https://en.m.wikipedia.org/wiki/Zagros_Mountains#/media/File...
This image from the same article is stunning. Those massive formations look like CGI to me. They're just too far removed from the sort of mountains I'm familiar with.
Notice the cars in the foreground for scale.
https://en.m.wikipedia.org/wiki/Zagros_Mountains#/media/File...
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#18The article mentions Minecraft — if you’re interested, check out “Reinventing Minecraft world generation by Henrik Kniberg”, a great talk about procedural generation by one of the developers: https://youtu.be/ob3VwY4JyzE
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#19Nice writeup.
If you are interested in this sort of thing, you might be interested in: https://jangafx.com/software/geogen
(Haven't used it myself, but I understand their EmberGen tool is well thought of in visual fx)
Re: Mountains, Cliffs, and Caves: A Guide to Using Perlin Noise for Procedural Gen
#20To my geologist's eyes there is a fundamental flaw in this method: the assumption of randomness. All mountain ranges are driven up by lateral forces, so simply look on a satellite image to notice how they are made of ranges[0]. I do wonder if this propensity can be introduced to the code. [0] https://en.m.wikipedia.org/wiki/Zagros_Mountains#/media/File...
You can get much more realistic results at a smaller scale for e.g. waterways using iterative methods -- simulating rainfall and erosion. I imagine the same would be true at mountain ranges using some model of your lateral forces to influence the heightmap. The main issue with this will be the computation time, naturally. Not that that should stop anyone, but it's likely the reason you don't see it in shipped games.
Diffusion limited aggregation is another interesting option for mountains assuming you're willing to employ an approach that isn't single pass. However a naive implementation is extremely expensive compared to other iterative options.
To be fair to OP though it doesn't model lateral forces. It just produces a visually plausible result (to my non-geologist eye at least).