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September 10, 2025Remote SensingOpen Access

The Downscaled GOME-2 SIF Based on Machine Learning Enhances the Correlation with Ecosystem Productivity

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Authors

CHChing‐yeh HuPXPinhua XieUniversity of Science and Technology of ChinaZHZhaokun HuGuangxi Medical University

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Overview

Machine learning downscales GOME-2 SIF data to improve correlation with ecosystem productivity, indicating better monitoring.

Key Points

  • The downscaled product shows a strong correlation with the original SIF data, with a correlation coefficient of 0.76.
  • Using the XGBoost model improved the explained variance in gross primary productivity from 0.66 to 0.85 in mixed forest.
  • A temporal resolution of 8 days and a spatial resolution of 0.05° × 0.05° enhance the usability of SIF data in monitoring.
  • Cross-validation confirmed the reliability of the high-resolution SIF product against ground-based observations.

Cite This Study

Hu et al. (2025) studied this question.

synapsesocial.com/papers/68c1a12754b1d3bfb60dbe09https://doi.org/10.3390/rs17152642
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