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Updated: Sep 12, 2025

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全球碳流数据集是由远程传感和多个流量网络观测的融合产生的
Qiwang Yuan1, Xufeng Wang2, Tao Che3
1School of Computer Science, China University of Geosciences, Wuhan, 430078, China.
Scientific data
|August 5, 2025
概括
我们创建了GloFlux,使用机器学习创建了一个全球碳流数据集. 这一数据集追踪了2000-2023年间的植被动态和生态系统对气候变化的反应.
科学领域:
- 地球系统科学 地球系统科学
- 生态生态学 生态生态学
- 遥感 遥感 遥感 遥感
背景情况:
- 准确的全球碳流量数据对于理解生态系统动态和气候变化至关重要.
- 现有的数据集在空间时间覆盖和多种数据源的整合方面存在局限性.
研究的目的:
- 开发一个全面的全球碳流数据集,GloFlux,整合多个数据源.
- 提供可靠的总初级生产率 (GPP),净生态系统交换 (NEE) 和生态系统呼吸 (RECO) 的估计.
主要方法:
- 开发了一种机器学习模型,将现场观测 (FLUXNET,AmeriFlux,ICOS,JapanFlux2024,HBRFlux) 与卫星遥感和气象数据相结合.
- 数据集涵盖2000-2023年,空间分辨率为0.1° × 0.1°,月度时间分辨率为0.1°.
主要成果:
- 在独立站点的验证显示出强的表现:GPP为0.84,NEE为0.66,RECO为0.80.
- 全球流动的时空模式与已建立的数据集 (FLUXCOM,MODIS) 保持一致.
结论:
- 全球碳流量 (GloFlux) 为全球碳流量估计提供了强大可靠的数据集.
- 该数据集是评估全球植被动态和生态系统对气候变化的反应的宝贵资源.
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