Geological Provinces - Green: Orogen, Blue:Basin, Pink: Craton |

Elevation Map - Black: Low, White: High |

Generic Map With Rivers - Lighter regions indicate elevation |

Moisture Map - Green: High, Tan: Low |

Next we move onto temperature. Looking at an average temperature map you can see what you would expect. It is hot at the equator and cold at the poles. Now this is not hard to replicate. With a little math we can get there. With each point on the map we have an x and y position (which we will normalize to a range from 0 - 1 for better looking math). If we want a curve with a warm patch in the middle we can just use the function,

\(T(x, y) = 1 - |cos(2π*y)|\)

Temperature Map - Orange: High, Blue: Low |

\(T(x, y) = 1 - |cos(2π * y * a + b)|\)

This gives us a nice looking band of warm/cool weather somewhere on the map. One thing to note is that I skewed the b value towards the center because we took the absolute value of the cosine function. This gives a better distribution of warm and cold temperature zones. This is a good start for general temperatures, however the results are rather bland and predictable results. Nature does not behave so perfectly, it has twists and turns depending on many local factors and weather patterns. Now we can use procedural texture generation techniques here to help fudge those weather patterns for us. By adding turbulence to our function we can add more organic looking features to our temperature map. Turbulence is just slight alterations in the temperature function according to another noise function. This allows the alterations to look like they are behaving according to a pattern. Therefore it adds coherent randomness to our temperature map. Adding in our turbulence (or noise) function we get the resulting equation,
\(T(x, y) = 1 - |cos( 2π * y * a + b + turbulence(x, y) )|\)

One last touch we can add for temperature is that at higher elevations, we want a colder temperature. We can just have a bias so that at higher elevations, temperature has less effect. Then we are left with a much more organic looking temperature map. Now I did add one bit more to the temperature function. I added an x period. I made it random and extremely small, just to add a bit more randomness to the function.Modified Whittaker Diagram |

Biome Map: Biome Labels from Whittaker Diagram |

From here my next step is to render the map in 3D. Right now the map looks flat as all hell, because you can either look at a map that shows the elevations and basic information, or the biome map. The rendered map will be a good first step to creating a map that conveys a large amount of information, and is legible. I also want to look into better ways to generate land. Currently, the perlin island generator is not horrible, but I want more variety out of islands. My continent generation function is simple and abysmal, and I need to find a better way of generating more than one island, and not have them just be small clusters of islands.

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