2025/06/16 by Michelangelo Conserva, Alex Wilson, Conserva, Michelangelo +7
Earth and Planetary Sciences · Environmental Science · #Computer Vision and Pattern Recognition (cs.CV) #Environmental Changes in China #FOS: Computer and information sciences #Machine Learning (cs.LG) #Rangeland Management and Livestock Ecology #Remote Sensing and Land Use
paper · pdf · doi:10.48550/arxiv.2506.13993
openalex publication_date 2025/06/16 · openalex created_date 2025/10/18 · openalex updated_date 2026/07/28
Effective management of agricultural landscapes is critical for meeting global biodiversity targets, but efforts are hampered by the absence of detailed, large-scale ecological maps. To address this, we introduce Farmscapes, the first large-scale (covering most of England), high-resolution (25cm) map of rural landscape features, including ecologically vital elements like hedgerows, woodlands, and stone walls. This map was generated using a deep learning segmentation model trained on a novel, dataset of 942 manually annotated tiles derived from aerial imagery. Our model accurately identifies key habitats, achieving high f1-scores for woodland (96%) and farmed land (95%), and demonstrates strong capability in segmenting linear features, with an F1-score of 72% for hedgerows. By releasing the England-wide map on Google Earth Engine, we provide a powerful, open-access tool for ecologists and policymakers. This work enables data-driven planning for habitat restoration, supports the monitoring of initiatives like the EU Biodiversity Strategy, and lays the foundation for advanced analysis of landscape connectivity.