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一个大规模的,多任务,多感应数据集,用于美国2018-2022年气候意识的作物监测
Adrian Höhl1,2, Stella Ofori-Ampofo3, Miguel-Ángel Fernández-Torres4
1Data Science in Earth Observation, Technical University of Munich (TUM), 80333, Munich, Germany. adrian.hoehl@tum.de.
Scientific data
|January 20, 2026
概括
一个新的数据库,CropClimateX,为连续的美国提供全面的农业数据. 该资源整合了遥感,天气和环境数据,以支持可持续农业和作物建模研究.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 气候变化,极端天气和日益增长的粮食需求给全球粮食生产带来了压力.
- 可持续农业需要及时获取有关天气,作物和产量的数据.
- 缺乏大规模,全面的作物监测数据集,阻碍了农业研究.
研究的目的:
- 推出CropClimateX,一个用于农业监测的新型大规模数据库.
- 优化位置采样,以广泛覆盖连续美国的种植面积.
- 提供支持可持续农业和作物建模的综合数据集.
主要方法:
- 开发了CropClimateX数据库,其中包含15,500个数据立方体 (12x12公里).
- 集成的多源数据:多传感器图像 (Sentinel-1/2,Landsat-8,MODIS),天气数据 (Daymet),极端事件和环境特征 (土壤,地形).
- 优化了美国连续1,527个县的位置采样.
主要成果:
- 创建了一个涵盖主要种植面积的综合数据集.
- 将各种数据类型集成到一个统一的结构中.
- 建立了农业研究的宝贵资源.
结论:
- CropClimateX解决了对大规模综合农业数据的需求.
- 该数据库支持先进的农业监测和研究.
- 促进可持续农业实践和作物建模方面的进步.
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