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中国主要谷物地区500米农业干旱影响数据集:朝着基于影响的干旱监测

Jiali Shi^1,2, Yan-Fang Sang^3,4,5, Amir AghaKouchak^6,7

¹Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.

Scientific data

|February 4, 2026

概括

一个新的高分辨率数据集量化了2006-2020年中国农业干旱的影响. 这一农业干旱影响地区数据集 (ADIA-CMGR) 有助于干旱监测和农业管理.

科学领域:

农业科学农业科学
环境监测环境监测
遥感遥感遥感遥感

背景情况:

量化农业干旱影响数据至关重要,但缺乏有效的干旱监测和预测.
现有的数据限制阻碍了开发可靠,影响驱动的干旱评估.
需要高分辨率的网格化数据集来捕捉空间和时间干旱动态.

研究的目的:

为了生成一个高分辨率的,中国主要谷物地区农业干旱影响的定量数据集.
为改善基于影响的干旱监测和预测提供数据.
支持农业干旱管理和实践改进.

主要方法:

为2006-2020年制定了一个500米网格农业干旱影响地区数据集 (ADIA-CMGR).
采用基于叶面积指数 (LAI) 的相对值方法来确定干旱影响.
对不同种类的作物 (夏季收获,秋季收获,早期大米) 进行三级干旱影响的提取面积.

主要成果:

创建了一个全面的数据集,包括干旱覆盖,干旱损坏和作物失败的地区.
与定性记录对数据集进行了验证,证实了精确的时间变化和空间分布.
揭示了不同作物生长季节农业干旱影响的显著空间和跨年动态.

结论:

ADIA-CMGR数据集为农业干旱影响评估提供了必要的高分辨率定量数据.
该数据集为管理干旱影响和加强中国农业实践提供了坚实的基础.
准确的干旱影响数据对于推进干旱监测,预测和农业抵御能力至关重要.

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