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从2003年到2018年全球每日平均空隙无土地表面温度数据集的综合
Xin Pan1,2, Xu Ding3,4, Kevin Tansey5
1College of Geography and Remote Sensing, Hohai University, Nanjing, 210098, China. px1013@hhu.edu.cn.
Scientific data
|July 10, 2025
概括
这项研究通过结合遥感和再分析数据,创建了一个无间隙的陆地表面温度 (LST) 产品. 新的LST数据集提供了更高的准确性,特别是在干旱和寒冷的地区.
科学领域:
- 地球科学 地球科学 地球科学
- 环境科学 环境科学
- 遥感 遥感 遥感 遥感
背景情况:
- 土地表面温度 (LST) 对能量平衡,水文,气象学,地理学和生态学至关重要.
- 遥感是LST检索的主要方法,但云层会导致大量数据缺口.
- 缺少LST数据阻碍了其在各种科学领域的应用.
研究的目的:
- 开发具有高空间和时间分辨率的无间隙地表温度 (LST) 产品.
- 为了克服遥感LST数据中缺失值的局限性.
- 提高LST数据的准确性和适用性,特别是在具有挑战性的地区.
主要方法:
- 整合了两个每日平均陆地表面温度 (DMLST) 遥感数据集 (Zhan等人. 和等人. 和等人. ) 的情况.
- 与两个重新分析数据集的融合:GLDAS和ERA5-Land.
- 生成一种合成的LST产品,具有1公里的空间和每日时间分辨率.
主要成果:
- 合成的LST产品实现了大约2K的根平均平方误差 (RMSE).
- 与现有数据集相比,新产品的准确性有所提高 (0.40.6 K RMSE增加).
- 在干旱和寒冷地区观察到LST数据准确度的显著提高.
结论:
- 拟议的无间隙LST产品有效地解决了遥感LST中的数据差距.
- 综合方法产生了更准确和可靠的LST数据集.
- 这种增强的LST产品对于地球和环境科学中的各种应用非常有价值.
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