首套国家级小农农业景观地图系统,可识别田地、树木和水体。
Agricultural Landscape Understanding At Country-Scale
- 构建覆盖全国的小农农业要素分割系统,超越单纯地块划分。
- 引入新颖后处理规则,确保地图在真实场景中的准确与一致。
- 成果公开可用,助力精准农业与全球可持续发展目标。
全面理解农业景观对应对粮食安全、气候变化和资源管理等全球挑战至关重要。这需要不仅绘制作物地块,还需识别树丛和水体等关键要素,这些在主导全球南方的复杂小农系统中形成交错分布的图景。以往研究多局限于地块划分方法,且缺乏适用于实际部署的稳健后处理步骤。据我们所知,尚无针对小农农场的系统在国家尺度上实现部署与评估。本文提出首个国家级农业制图系统,突破传统地块提取,实现田地、树木和水体等农业实例的分割。通过创新后处理启发式策略优化系统在真实场景中的表现,并经多维度严格验证。生成的细粒度土地利用地图已通过 API 公开(http://agri.withgoogle.com),支持精准农业、政策制定及全球可持续发展目标推进。
原文摘要 · Abstract (English)
Comprehensive agricultural landscape understanding is critical for addressing global challenges in food security, climate change, and resource management. This requires mapping not just crop fields, but also vital features like trees and water bodies which form an intricate mosaic in complex \textit{smallholder} systems dominating the Global South. Previous efforts to develop such land use maps have been limited by a narrow focus on methods for field delineation only, and also do not develop robust post-processing steps essential for real-world deployment. Further, to our knowledge, no prior system for smallholder farms has been deployed and evaluated at a national scale. This work addresses these limitations by presenting the first national-scale agricultural mapping system that moves beyond simple field delineation to enable segmentation of agricultural instances like fields, trees and water bodies. Our system is refined for real-world application using novel post-processing heuristics to ensure map consistency and accuracy, and is validated through a rigorous, multi-faceted evaluation process. Fine-grained land use maps generated by our system are publicly accessible via an API at \textit{\href{http://agri.withgoogle.com}{http://agri.withgoogle.com}}, enabling a wide range of applications from precision agriculture and policy-making to advancing global sustainability development goals.
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