Reyes-Muñoz et al. (2026) Assessing the Role of Global Satellite-Derived SIF and Vegetation Traits as Proxy Predictors of Gross Primary Productivity

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-09-23
• Authors: Pablo Reyes-Muñoz, Emma De Clerck, Yuxin Zhang, Dávid D. Kovács, Jochem Verrelst
• DOI: 10.3390/rs18193278

Research Groups

• Department of Earth System Science, University of California, Irvine
• Max Planck Institute for Biogeochemistry

Short Summary

This study investigates the relationships between solar-induced chlorophyll fluorescence (SIF), vegetation traits, meteorological drivers, and gross primary productivity (GPP) using global satellite and reanalysis datasets. The results show that satellite-derived SIF and vegetation traits can capture variability associated with meteorological forcing relevant for GPP prediction.

Objective

• Investigate the spatiotemporal extent to which satellite-derived SIF and vegetation traits encode meteorological constraints for prediction of GPP

Study Configuration

• Spatial Scale: Global, with a focus on Europe
• Temporal Scale: Annual cycle, with a specific analysis in 2019

Methodology and Data

• Models used: Gaussian process regression (GPR)
• Data sources:
  • Satellite data: TROPOMI, Sentinel-3, MODIS
  • Reanalysis data: ERA5-Land
  • Tower-based observations for empirical model validation

Main Results

• Strong agreement between two GPP products based on satellite-derived SIF and vegetation traits (median R=0.76)
• Significant influence of incoming shortwave radiation, temperature, soil moisture, latent heat flux, and leaf area index on SIF dynamics over large regions

Contributions

• This study highlights the complementary role of satellite SIF and vegetation traits as proxy predictors of ecosystem productivity monitoring
• The findings provide insights relevant for the recently launched FLEX mission

Funding

• Not specified in the provided text

Citation

@article{ReyesMuñoz2026Assessing,
  author = {Reyes-Muñoz, Pablo and Clerck, Emma De and Zhang, Yuxin and Kovács, Dávid D. and Verrelst, Jochem},
  title = {Assessing the Role of Global Satellite-Derived SIF and Vegetation Traits as Proxy Predictors of Gross Primary Productivity},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18193278},
  url = {https://doi.org/10.3390/rs18193278}
}