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A cloud-computing framework for downscaled global 300 m SIF retrieval from Sentinel-3 and TROPOSIF
Yuxin Zhang1, Pablo Reyes-Muñoz1, Jochem Verrelst1
1Image Processing Laboratory (IPL) - University of Valencia, Catedrático Agustín Scardino Benlloch 9, Paterna, 46980, Spain.
International Journal of Applied Earth Observation and Geoinformation : ITC Journal
|June 5, 2026
Summary
This study introduces a new method to create high-resolution sun-induced chlorophyll fluorescence (SIF) maps from Sentinel-3 data. The downscaled SIF product (S3-SIF743) offers unprecedented insights into plant photosynthesis at the sub-kilometer scale.
Area of Science:
- Earth and Planetary Sciences
- Remote Sensing
- Ecology
Background:
- Sun-induced chlorophyll fluorescence (SIF) is a key indicator of photosynthetic activity.
- Existing satellite SIF products have coarse spatial resolutions ( > 500 m), limiting fine-scale ecosystem studies.
- There is a need for higher spatial resolution SIF data to understand vegetation health and function.
Purpose of the Study:
- To develop a cloud-computing framework for generating a downscaled SIF product (S3-SIF743) with 300 m spatial resolution.
- To integrate Sentinel-3 (S3) Ocean and Land Colour Instrument (OLCI) data with TROPOspheric Monitoring Instrument (TROPOMI) SIF (TROPOSIF743) using Google Earth Engine (GEE).
- To provide a flexible and operational pathway for high-resolution monitoring of terrestrial photosynthesis.
Main Methods:
- Utilized Google Earth Engine (GEE) for cloud-based processing.
- Employed a Random Forest (RF) regression framework integrating TROPOMI SIF, S3 radiances, S3-derived vegetation traits, latitude, and longitude.
- Trained and validated the model using reference data over Europe and ground-based observations globally.
Main Results:
- Achieved robust performance in model training over Europe (R² = 0.767, RMSE = 0.137 mW m⁻² sr⁻¹ nm⁻¹).
- S3-SIF743 successfully reproduced seasonal dynamics across diverse ecosystems and showed strong spatial consistency with TROPOSIF743 in agricultural regions.
- The downscaled product revealed coherent patterns of photosynthetic activity globally and reduced retrieval noise compared to TROPOMI SIF.
Conclusions:
- The developed framework successfully generates a high-resolution SIF product (S3-SIF743) at 300 m resolution.
- S3-SIF743 provides valuable insights into sub-kilometer spatial heterogeneity of terrestrial photosynthesis.
- This approach bridges the gap between existing coarse SIF products and future missions like FLEX, enabling enhanced ecosystem monitoring.
