Wu et al. (2026) The conditional nature of error estimates in multi-source satellite SIF cross-evaluation: How product combinations, statistical models, spatial scales, and temporal treatments shape the conclusions

Identification

• Journal: Remote Sensing of Environment
• Year: 2026
• Date: 2026-10-07
• Authors: Xiaodan Wu, Qicheng Zeng, Yuxin Wang, Rongqi Tang, Jing Pei, Gaofei Yin, Xiaojun Li, Jianguang Wen, Qing Xiao
• DOI: 10.1016/j.rse.2026.115716

Research Groups

• Faculty of Geosciences and Engineering, Southwest Jiaotong University (China)
• International Institute for Earth System Sciences, Nanjing University (China)
• College of Water Sciences, Beijing Normal University (China)
• Gansu Water Resources and Hydropower Survey Design and Research Institute Co.,Ltd. (China)
• National Engineering Research Center for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences (China)

Short Summary

This study investigates the methodological sensitivity of cross-evaluation results in multi-source satellite solar-induced chlorophyll fluorescence (SIF) products and develops a diagnostic framework to assess this sensitivity. The key finding is that certain analytical choices can lead to biased error estimates.

Objective

• Investigate the conditional nature of error estimates in multi-source satellite SIF cross-evaluation

Study Configuration

• Spatial Scale: Global and regional scales
• Temporal Scale: 2018-2021

Methodology and Data

• Models used: Three-Cornered Hat (TCH) and Quadruple Collocation Analysis (QCA)
• Data sources: Four representative SIF products from TROPOMI, GOME-2, OCO-2, and TROPOSIFCaltech

Main Results

• The closest agreement was found between the two TROPOMI products.
• QCA mitigated bias in error estimates when a product combination included two products that share observations from the same sensor.
• Coarser-resolution products were more sensitive to spatial aggregation, while seasonal-cycle removal reduced error estimates for all products.

Contributions

• This study provides a diagnostic framework for assessing methodological sensitivity of cross-evaluation results in multi-source satellite SIF products.
• The findings highlight the importance of considering product-specific error characteristics and analytical frameworks when evaluating error estimates.

Funding

• Not specified

Citation

@article{Wu2026conditional,
  author = {Wu, Xiaodan and Zeng, Qicheng and Wang, Yuxin and Tang, Rongqi and Pei, Jing and Yin, Gaofei and Li, Xiaojun and Wen, Jianguang and Xiao, Qing},
  title = {The conditional nature of error estimates in multi-source satellite SIF cross-evaluation: How product combinations, statistical models, spatial scales, and temporal treatments shape the conclusions},
  journal = {Remote Sensing of Environment},
  year = {2026},
  doi = {10.1016/j.rse.2026.115716},
  url = {https://doi.org/10.1016/j.rse.2026.115716}
}