用卫星数据监测卢旺达农田，发现增产差距与目标达成路径

Satellite monitoring uncovers progress but large disparities in doubling crop yields

• 基于高分辨率卫星影像，机器学习分析1.5万个村庄产量
• 发现部分村庄距2030年产量翻倍目标已达标，部分仍严重滞后
• 可生成精准到村的增产目标，助力公平实现国家农业目标

高分辨率卫星作物产量测绘为监测可持续发展目标进展提供了巨大潜力。在卢旺达15,000个村庄中，我们识别出处于或偏离2030年产量翻倍目标的地区。该机器学习驱动的分析用于制定空间细化的生产率目标，若达成，将同时实现国家目标且不遗漏任何地区。

原文摘要 · Abstract (English)

High-resolution satellite-based crop yield mapping offers enormous promise for monitoring progress towards the SDGs. Across 15,000 villages in Rwanda we uncover areas that are on and off track to double productivity by 2030. This machine learning enabled analysis is used to design spatially explicit productivity targets that, if met, would simultaneously ensure national goals without leaving anyone behind.

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