Global Sentinel-3 OLCI CCC at an 8-day interval from 2016 to 2024: Part 3

This dataset is part of the full collection: https://doi.org/10.5281/zenodo.15593487 Citation: Please cite the following publication when using this dataset: Li, D., Croft, H., Duveiller, G., Schreiner-McGraw, A.P., Belwalkar, A., Cheng, T., Zhu, Y., Cao, W., & Yu, K. (2025). Global retrieval of canopy chlorophyll content from Sentinel-3 OLCI TOA data using a two-step upscaling method integrating physical and machine learning models. Remote Sensing of Environment, 328, 114845. https://doi.org/10.1016/j.rse.2025.114845本数据集隶属于完整数据集集合：https://doi.org/10.5281/zenodo.15593487 引用要求： 使用本数据集时，请引用下述出版物： Li, D., Croft, H., Duveiller, G., Schreiner-McGraw, A.P., Belwalkar, A., Cheng, T., Zhu, Y., Cao, W., & Yu, K. (2025). 利用融合物理模型与机器学习模型的两步升尺度方法从Sentinel-3 OLCI顶层反射率（Top-of-Atmosphere, TOA）数据反演全球冠层叶绿素含量. 《环境遥感（Remote Sensing of Environment）》, 328, 114845. https://doi.org/10.1016/j.rse.2025.114845