一个长期的亚洲米分布数据集,空间分辨率为30米
Shaoping Li1, Ruoque Shen1, Jiale Jiang1
1School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, 519082, Guangdong, China.
Scientific data
|June 20, 2025
概括
本研究介绍了全球作物数据集-大米 (GCD-Rice),为16个亚洲国家提供了关键的长期,高分辨率的大米绘图. 这一数据集有助于监测粮食安全和大米种植产生的甲排放.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 遥感 遥感 遥感 遥感
背景情况:
- 米是全球的主要食品,也是人类甲排放的重要来源.
- 准确地绘制亚洲大米分布地图对于粮食安全和气候变化监测至关重要.
- 现有的遥感数据受到云层的限制,这阻碍了长期的高分辨率大米绘图.
研究的目的:
- 开发全球作物数据集-大米 (GCD-大米) 用于绘制大米种植的地图.
- 为16个亚洲国家提供长期 (1990-2023) 的高分辨率数据集.
- 改善对粮食安全和来自大米田的温室气体排放的监测.
主要方法:
- 使用了Landsat和Sentinel-1卫星图像.
- 采用现象学方法与随机森林模型相结合.
- 使用258,547个现场样本和统计区域比较验证的地图.
主要成果:
- 实现了高的验证准确度:89.88%的用户准确度,88.52%的生产者准确度和88.85%的整体准确度.
- 统计区的比较显示出与R2=0.768,斜率=0.874,RMSE=0.346.8的强烈一致.
- 为16个亚洲国家创建了跨越三个季节的水种植综合数据集.
结论:
- GCD-Rice数据集提供了一个可靠的,高分辨率的工具来跟踪大米的分布.
- 这一数据集对于有关粮食安全和气候变化减缓的知情决策至关重要.
- 该方法为未来的农业监测系统提供了坚实的框架.
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