Abandoned project from 2020-2021, version 1.12.2
These pictures are from the Contagion project, made for and by the Vic's Modern Warfare mod team, and which would be a DayZ-like survival game, had it been finished. The project was abandoned in early 2022, leaving this 15k x 10k world—a product of 9 world designers and 2,000 hours of work—without a satisfying end. Its development was troubled; this world was the 3rd iteration, and even between the first and last things built on this world is significant skill progression, meaning a few-months-old sub-project became obsolete… in a cycle characteristic of large projects begun by novices.
More information about picture #12 (not important; just technical narration):
We were building this airport when the project was cancelled. Had it been completed, it would've represented a significant shift in the building process, as we were experimenting with using Google Earth photogrammetry data as the basis for our builds. It would've allowed for easier gradient coloring, and lessened the cognitive load of deciding "what should go here?", as we could simply reference the Google Earth location to see what's there, if we got that decision fatigue.
It was an immature technology, though, as visible in the picture: many colors were too noisy (structure walls, concrete floors), underrepresented (yellow paint on airplane roads), oversaturated with inappropriate blocks (yellow and green terracotta and concrete as grass at bottom-center of picture), and corrupted by photogrammetric shadows (shadowed building sides translated to darker and bluer blocks in Minecraft).
Correcting these problems with 2020's technology would've meant tweaking the colormap before importing the 3D model into Minecraft, limiting block types for different colors, and manual in-game fixing. But, with modern technology, I've wondered if, for example, a neural network could be trained to detect and fix these problems, such as using natural blocks for terrain and vegetation, building-appropriate blocks for man-made structures, and detecting then deleting shadows in the photogrammetric models.