Pabon-Moreno et al. (2026) Sun Induced Fluroscence Downscaling processor using openEO and Copernicus Data Space Ecosystem Infrastructure

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

Identification

• Journal: Open MIND
• Year: 2026
• Date: 2026-03-30
• Authors: Daniel E. Pabon-Moreno, Qiqi Deng
• DOI: 10.5281/zenodo.19334966

Research Groups

Open-Earth-Monitor Cyberinfrastructure project

Short Summary

This paper describes a mechanistic model-based workflow for downscaling Sun-induced chlorophyll fluorescence (SIF) observations from the Sentinel-5P TROPOMI sensor to finer spatial resolutions, aiming to improve the spatio-temporal coupling between SIF and gross primary productivity (GPP).

Objective

• To develop and illustrate a downscaling process for SIF observations, leveraging a mechanistic model that relates SIF with land-surface temperature and a vegetation index (NIRv), to overcome spatio-temporal resolution limitations of existing SIF platforms and enhance SIF's utility as a GPP indicator.

Study Configuration

• Spatial Scale: Input data from Sentinel-5P TROPOMI at 3.5 km × 5.5-7 km nadir resolution, with the objective of increasing (downscaling) this spatial resolution.
• Temporal Scale: Daily observations from Sentinel-5P TROPOMI.

Methodology and Data

• Models used: A mechanistic model relating SIF with land-surface temperature and NIRv (a vegetation index). The workflow is implemented using openEO.
• Data sources: Sun-induced chlorophyll fluorescence (SIF) observations from the Sentinel-5P TROPOMI sensor.

Main Results

• The paper presents the development and description of a reproducible workflow for SIF downscaling, which integrates a mechanistic model with Sentinel-5P TROPOMI data.
• It outlines the computational steps and tools (e.g., openEO, pixi) required to perform SIF downscaling, providing a practical tutorial for users.
• The developed processor aims to enable more detailed observation of SIF/GPP relationships in terrestrial ecosystems by increasing the spatial resolution of SIF data.

Contributions

• Development of a novel, mechanistic SIF downscaling workflow designed to address the spatio-temporal resolution limitations of current satellite SIF observations.
• Provision of a reproducible and accessible tutorial for implementing the SIF downscaling processor, facilitating broader application and research.
• Enhancement of SIF's potential as a direct measure of plant physiological status and an indicator for GPP estimation by enabling finer-scale analysis.

Funding

• Open-Earth-Monitor Cyberinfrastructure project
• European Union's Horizon Europe research and innovation programme (grant 101059548)

Citation

@article{PabonMoreno2026Sun,
  author = {Pabon-Moreno, Daniel E. and Deng, Qiqi},
  title = {Sun Induced Fluroscence Downscaling processor using openEO and Copernicus Data Space Ecosystem Infrastructure},
  journal = {Open MIND},
  year = {2026},
  doi = {10.5281/zenodo.19334966},
  url = {https://doi.org/10.5281/zenodo.19334966}
}