From pixels to planning: Earth AI for nature restoration
Google Research
Researchers developed a deep learning model to convert satellite imagery into detailed vector maps identifying small woodland features like hedgerows and copses across England that are invisible to standard satellite detection. The model was trained using Google's Remote Sensing Foundations Vision-Transformer pre-trained on 300 million satellite images, then fine-tuned on 247 km² of annotated British countryside data. The vectorized dataset enables landowners and conservationists to measure and expand these ecological features across the UK to enhance carbon storage and biodiversity without displacing agricultural land.
Why it matters
Climate & Sustainability
