Arizona State University, School of Computing and Augmented Intelligence, Tempe, AZ, 85281, USA.
University of Maryland, Department of Geographical Sciences, College Park, MD, 20740, USA.
Sci Data. 2024 May 10;11(1):486. doi: 10.1038/s41597-024-03306-z.
Satellite Earth observations (EO) can provide affordable and timely information for assessing crop conditions and food production. Such monitoring systems are essential in Africa, where food insecurity is high and agricultural statistics are sparse. EO-based monitoring systems require accurate cropland maps to provide information about croplands, but there is a lack of data to determine which of the many available land cover maps most accurately identify cropland in African countries. This study provides a quantitative evaluation and intercomparison of 11 publicly available land cover maps to assess their suitability for cropland classification and EO-based agriculture monitoring in Africa using statistically rigorous reference datasets from 8 countries. We hope the results of this study will help users determine the most suitable map for their needs and encourage future work to focus on resolving inconsistencies between maps and improving accuracy in low-accuracy regions.
卫星对地观测（EO）可为评估作物状况和粮食生产提供经济实惠且及时的信息。在粮食安全水平高且农业统计数据匮乏的非洲，此类监测系统必不可少。基于 EO 的监测系统需要精确的耕地图来提供有关耕地的信息，但缺乏数据来确定众多可用的土地覆盖图中哪一个最能准确识别非洲国家的耕地。本研究使用来自 8 个国家的统计上严格的参考数据集，对 11 种可公开获取的土地覆盖图进行了定量评估和对比，以评估它们在非洲进行耕地分类和基于 EO 的农业监测的适用性。我们希望本研究的结果将有助于用户确定最适合其需求的地图，并鼓励未来的工作重点关注解决地图之间的不一致性和提高低精度区域的准确性。
