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.
Mapping Farmed Landscapes from Remote Sensing
Michelangelo Conserva,Alex Wilson,Charlotte Stanton,Vishal Batchu,Varun Gulshan
Published 2025 in arXiv.org
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- Publication year
2025
- Venue
arXiv.org
- Publication date
2025-06-16
- Fields of study
Agricultural and Food Sciences, Geography, Computer Science, Environmental Science
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Semantic Scholar
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