These maps were generated using machine learning, by a configuration of neural networks called a Generative Adversarial Network (GAN). This particular model, StyleGAN2, was trained on thousands of hand-curated maps from the European Digital Archive of Soil Maps (EuDASM) and the US Geological Survey (USGS).

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