2001年至2019年全球干旱地区的增强现象学数据集
Yuqi Dong1,2,3, Yu Zhou4,5, Li Zhang6,7
1International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, People's Republic of China.
Scientific data
|July 9, 2025
概括
准确的干地现象学对于理解碳汇至关重要. 一个新的全球干旱地现象数据集 (GDPD) 使用高分辨率卫星数据来改善检索,帮助气候变化研究.
科学领域:
- 地球和环境科学 地球和环境科学
- 遥感 遥感 遥感 遥感
- 生态生态学 生态生态学
背景情况:
- 干旱地区显著影响全球碳汇的变化,而现象学是碳封存的关键因素.
- 基于卫星的陆地表面现象学 (LSP) 在干旱地区的检索是具有挑战性的,因为稀疏的植被和现有的粗分辨率产品和算法的局限性.
研究的目的:
- 开发一个高精度的全球干旱地现象学数据集 (GDPD),以更好地了解干旱地生态系统对气候变化的反应.
- 解决干旱地区现有的LSP产品的局限性.
主要方法:
- 使用了MODIS NBAR (Nadir双向反射分布函数调整反射) 的每日500米增强植被指数 (EVI) 数据.
- 开发并应用了一种改进的检索算法,该算法具有动态,像素智能的振幅值,用于现象检测.
- 在2001-2019年期间产生了GDPD,覆盖了全球干旱地区的88.4%.
主要成果:
- GDPD与现场现象学数据 (PhenoCam GCC) 和流量塔总初级生产 (GPP) 数据有很强的一致性.
- 在现场和流量塔测量时,观察到季节开始 (SOS) 和季节结束 (EOS) 的高相关系数.
- 该数据集成功地弥补了其他现有LSP产品中缺失的区域.
结论:
- 高分辨率的卫星数据和改进的算法对于准确的干地现象检索至关重要.
- GDPD为研究干地生态系统动态及其对气候变化的反应提供了宝贵的资源.
- 这一数据集将加强地球系统模型的开发和验证.
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