UK Scientists Leverage AI and Satellite Data to Map Hedgehog Habitats
Cambridge researchers have pioneered a novel approach to wildlife conservation, using machine learning to identify hedgehog habitats from space. By analyzing Sentinel satellite imagery, the team detects blackberry thickets—critical shelters for the vulnerable species.
The hybrid model combines logistic regression, nearest-neighbor classification, and ESA's TESSERA system with crowdsourced data from iNaturalist. Field tests in Cambridge confirmed the system's accuracy in locating large thickets, though canopy-obscured bushes proved challenging.
This breakthrough demonstrates how AI can transform ecological monitoring at scale. The methodology opens doors for tracking other elusive species through environmental proxies rather than direct observation.
