Mamić et al. (2025) Solar-induced fluorescence as a robust proxy for vegetation productivity across climate zones and vegetation types in the United States

Identification

• Journal: Remote Sensing Applications Society and Environment
• Year: 2025
• Date: 2025-10-17
• Authors: Luka Mamić, Mj Riches, Delphine K. Farmer, Francesco Pirotti
• DOI: 10.1016/j.rsase.2025.101760

Research Groups

• Department of Civil, Building and Environmental Engineering, Sapienza University of Rome, Italy
• Department of Chemistry, Colorado State University, United States
• Department of Land and Agroforestry Systems (TESAF), University of Padua, Italy
• Interdepartmental Research Centre in Geomatics (CIRGEO), University of Padua, Italy
• Department of Agricultural Biology, Colorado State University, United States

Short Summary

This study provides the first continental-scale assessment of Solar-induced fluorescence (SIF) across diverse vegetation types and climate zones in the contiguous United States, demonstrating SIF's consistently stronger and more reliable correlation with Gross Primary Productivity (GPP) than Normalized Difference Vegetation Index (NDVI), even under high vapor pressure deficit (VPD) conditions.

Objective

• To conduct the first continental-scale assessment of seasonal SIF signatures for 33 vegetation types across 24 climate zones in the contiguous United States.
• To evaluate how the relationships between SIF, Gross Primary Productivity (GPP), and Normalized Difference Vegetation Index (NDVI) vary across different vegetation types and climate regimes, particularly under environmental stress such as high Vapor Pressure Deficit (VPD).

Study Configuration

• Spatial Scale: Contiguous United States; continental-scale assessment across 33 vegetation types and 24 K¨oppen climate zones. Data aggregated to a spatial resolution of 7 km.
• Temporal Scale: Three-year period from 2019 to 2021, with daily data aggregated to weekly intervals.

Methodology and Data

• Models used: Locally Estimated Scatterplot Smoothing (LOESS) for generating smooth seasonal curves; Linear regression for analyzing relationships between variables.
• Data sources:
  • TROPOspheric Monitoring Instrument (TROPOMI) satellite Solar-induced fluorescence (SIF) data (TROPOSIF dataset, 743–758 nm window).
  • Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day Gross Primary Productivity (GPP) estimates.
  • MODIS daily Normalized Difference Vegetation Index (NDVI) data.
  • University of Idaho Gridded Surface Meteorological Dataset (GRIDMET) daily Vapor Pressure Deficit (VPD) values.
  • United States Department of Agriculture (USDA) Cropland Data Layer (CDL) for land cover classification (30 m resolution, aggregated to 7 km).
  • K¨oppen-Geiger climate zones raster.
  • An open-access web-based visualization tool and associated datasets.

Main Results

• SIF consistently exhibits stronger and more reliable correlations with GPP than NDVI across the majority of vegetation types and environmental conditions in the contiguous U.S.
• The GPP-SIF relationship remains robust even under high VPD conditions, confirming SIF's capability to track productivity in dry environments, with some exceptions noted for perennial crops.
• NDVI, while reflecting canopy greenness, frequently decouples from GPP under stress, particularly in arid climates and for perennial crops, demonstrating limited sensitivity to dynamic changes in canopy physiology.
• Distinct differences in SIF-NDVI and GPP-NDVI relationships were observed based on vegetation type and climate zone.
• Deciduous forests show the strongest seasonal SIF amplitude, whereas evergreen forests maintain more stable, lower-intensity fluorescence profiles throughout the year.
• C4 crops (e.g., corn) demonstrate a stronger GPP-SIF coupling and greater resilience in SIF-NDVI relationships under high VPD compared to C3 crops (e.g., soybean).
• In perennial crops such as almonds, high VPD can lead to a decoupling of GPP and SIF, where SIF values remain high due to increased non-photochemical quenching (NPQ) despite a decline in GPP.
• The study developed and made available an open-access visualization tool for exploring climate-specific SIF signatures.

Contributions

• Presents the first continental-scale assessment of SIF dynamics across 33 vegetation types and 24 K¨oppen climate zones in the contiguous U.S.
• Demonstrates SIF's broad applicability as a physiologically-based proxy for ecosystem productivity across diverse climates, consistently outperforming NDVI in predicting GPP, especially under environmental stress.
• Highlights the critical need to interpret SIF in conjunction with other variables (e.g., GPP, VPD) to differentiate between active photosynthesis and photoprotective stress responses.
• Identifies climate-specific SIF signatures at a continental scale, offering valuable insights for climate-smart crop management, productivity assessment, and satellite-based ecosystem modeling.
• Introduces a novel open-access visualization tool and associated datasets, fostering interactive exploration of climate-specific SIF signatures and enhancing research transparency and reproducibility.

Funding

• European Space Agency (ESA) Sentinel-5p + Innovation activity Contract N◦4000127461/19/I-NS (for TROPOSIF products).
• Italian National PhD Program in Earth Observation funded by the European Union – Next Generation EU through the Project of Italian Recovery and Resilience Plan (NRRP) (B53C22004370006).

Citation

@article{Mamić2025Solarinduced,
  author = {Mamić, Luka and Riches, Mj and Farmer, Delphine K. and Pirotti, Francesco},
  title = {Solar-induced fluorescence as a robust proxy for vegetation productivity across climate zones and vegetation types in the United States},
  journal = {Remote Sensing Applications Society and Environment},
  year = {2025},
  doi = {10.1016/j.rsase.2025.101760},
  url = {https://doi.org/10.1016/j.rsase.2025.101760}
}