OEMC project use case: SIF-based high spatial resolution GPP flux estimations
Creators: name: Max-Planck Institute for Biogeochemistry
Publisher: name: Max-Planck Institute for Biogeochemistry
Year: 2025
Subjects: GreenHouse Gases (GHGs)
Gross Primary Productivity (GPP)
Sun-Induced chlorophyll Fluorescence
SIF

description: Sun-induced chlorophyll fluorescence (SIF) is a EO signal that has been shown to correlate well with gross primary productivity (GPP), thereby providing an invaluable tool to monitor carbon uptake by terrestrial ecosystems. Such data thus has the potential to contribute to the quantification of the global carbon budget (GCB), the critical annual update revealing the latest trends in global carbon emissions. More specifically, the aim of this use case is to assist the 'REgional Carbon Cycle Assessment and Processes' (RECCAP) initiative coordinated by the Global Carbon Project, which seeks to gather and integrate regional data from 14 major global regions, ensuring enough harmonization to scale these budgets globally and facilitate regional comparisons. To do so, they rely on model simulations which would greatly benefit from detailed information on terrestrial carbon fluxes as can be provided by satellite EO. However, current and past satellite instruments from which this signal can be derived have a very coarse spatial resolution (5 km at best). In this use case, we develop a satellite EO downscaling tool capable to estimate a SIF-based proxy of GPP at finer spatial resolution (e.g. 1 km) leveraging on the synergistic use of other sources of remote sensing (e.g. LST, NIRv, etc.) within a hybrid framework, in which a data-driven method is combined with known physical constraints governing the relationships between the input variables. To evaluate and calibrate this novel approach, efforts have been dedicated to match the satellite grid cells to eddy covariance flux site  ground measurements of GPP whilst quantifying the effect of spatial heterogeneity. Furthermore, we aim to deploy the downscaling approach on adjustable moving windows over a Discrete Global Grid System (DGGS) composed of hexagons, which better preserve the area and neighborhood of every cell, thus ensuring a finer representativity of the surface properties.
Stakeholders needs:

The RECCAP efforts are done volutarily by many different and diverse participants, each with distinct approaches and looking at different regions, so they should have easy access to sub-sections of the data that they should be able to download on their computers
High spatial resolution to discriminate better GPP by land cover type, possibly also to detect the effect of disturbances and of land cover change
Coverage of coastal/island regions with finer spatial scale could be desirable as these are often misrepresented
Planned implementation:
A first prototype workflow in Julia language has been developed to ingest the new  Sentinel-5P TROPOMI data based on a previous SIF downscaling approach proposed by Duveiller and Cescatti (2016) and Duveiller et al. (2020). Work has also focused on preparing the validation approach with eddy covariance flux tower data, which involves the characterization of the spatial heterogeneity within the satellite observation footprint. The connection with the DGGS has also begun. The next steps involve:

Improving the documentation and creating a jupyternotebook for demonstration.
Exploring the use of AI techniques, specifically knowledge transfer techniques, to potentially improve the current method or at least improve the computation time of the optimization functions
Testing various model configurations, including the possible extension to a DGGS
Comparing results to flux towers
Producing the final downscale SIF for the Sentinel-5p TROPOMI product
Recorded talks (ordered chronologically):

Towards a better estimation of GPP for greenhouse gas accounting by Gregory Duveiller, Open-Earth-Monitor - Global Workshop 2023;
Quantifying the (mis)match between in-situ and satellite time series by Daniel Pabon-Moreno, Open-Earth-Monitor - Global Workshop 2024;
Rethinking the grid - Towards less distorted imagery and AI by Daniel Loos, Open-Earth-Monitor - Global Workshop 2024;
Technical info
Visit the use-case page on the OEMC website to learn more: https://earthmonitor.org/sif-based-high-spatial-resolution-gpp-flux-estimations/