Each step is displayed, stacked on top of the previous and denoted by a difference in the color. By repeating this hundreds of times, you end up with a 3D terrain map.įor my final piece on 3D terrain generation for my concentration, I again tried to combine each step in the algorithm into the final image. In this form, it is called the diamond-square algorithm.Īs shown in the above image, the algorithm takes a series of alternating diamonds and squares and fills in the center point of each. The midpoint displacement algorithm is most commonly used for 3D terrain generation. To better illustrate this, I laid out the algorithm’s steps by color: With some coloring, this eventually creates a detailed 2D terrain like the bottom layer: In two dimensions, instead of varying the spacing, the algorithm varies the height of each point. My final piece for this visualization included some extra colored circles for context: This can be audiolized as tones (hence the name “noise”) or can just be left as a series of randomly spaced points. Over multiple iterations, this creates a more and more detailed set of points spaced at different distances. At each iteration, the computer creates new points in between pairs of existing points. The first version of this is generating noise. This is called the midpoint displacement algorithm. By adding in a bit of random variation, a computer can create realistic terrain from only two starting points. For example, if you have two points with the values 10 and 20, you can add another point at 15. For each of the visualizations in this series, I variations on the “midpoint displacement algorithm.” The idea behind this algorithm is that you can add layers of detail to a data set by adding values based on the averages of the surrounding values.
Computers mainly use terrain generation for simulations and games. My third series in my AP Portfolio was on terrain generation.
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