论文标题
基于卫星的饲料条件预测肯尼亚北部的牲畜的饲料条件
Satellite-based Prediction of Forage Conditions for Livestock in Northern Kenya
论文作者
论文摘要
本文介绍了第一个由地面专家标记为带有草料质量的卫星图像的数据集，并为将计算机视觉方法应用于基于指数的干旱保险提供了概念验证。我们还介绍了一种协作基准工具的结果，用于众包数据集上的精确机器学习模型。我们的方法极大地胜过肯尼亚北部保险计划的现有技术，这表明一种基于计算机的方法可能会使牧师大大受益，牧师的暴露是严重的，并且随着气候变化的变化而恶化。
This paper introduces the first dataset of satellite images labeled with forage quality by on-the-ground experts and provides proof of concept for applying computer vision methods to index-based drought insurance. We also present the results of a collaborative benchmark tool used to crowdsource an accurate machine learning model on the dataset. Our methods significantly outperform the existing technology for an insurance program in Northern Kenya, suggesting that a computer vision-based approach could substantially benefit pastoralists, whose exposure to droughts is severe and worsening with climate change.
