Ground-Truthing Process

Biodiversity mapping uses data to make predictions about the biodiversity across all of Earth’s ecoregions. With this kind of machine learning work there is always a degree of uncertainty. SPUN sees areas with high uncertainty as opportunities to “ground truth” our predictions — collecting real-life samples from areas where our model has made predictions allows us to check those predictions against the biodiversity we find and strengthens our models.