Solar Induced Fluorescence as an Application Ready Early Warning Indicator of Flash Drought

Abstract Flash drought has garnered major attention due to its devastating impact on both agricultural and ecological systems impacting production and income for producers, due to its rapid onset nature, and poor predictability. Solar‐induced fluorescence (SIF) is an increasingly well‐known and reliable indicator of vegetation health which captures rapid changes in how plants absorb and use light under stress. Recent efforts leveraging machine learning trained on spaceborne SIF and vegetation data from other sensors are producing seamless maps of SIF at spatial resolutions (∼5 km) aligned with land management needs. Three recent studies, Mohammadi et al. (2022, https://doi.org/10.1073/pnas.2202767119 ), Parazoo et al. (2024, https://doi.org/10.1029/2024GL108310 ), and Behera et al. (2025, https://doi.org/10.1029/2024GL113419 ), directly show the value of high‐resolution SIF mapping for flash drought early warning. Through advanced studies and calibration, we contend that SIF‐based data products are ready for immediate use by the drought monitoring community including the U.S. Drought Monitor.

Authors

Institutions

Publication Details

Journal
Geophysical Research Letters
Published
2025-12-02
DOI
https://doi.org/10.1029/2025gl119408
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Solar Induced Fluorescence as an Application Ready Early Warning Indicator of Flash Drought

Beth Fuchs
1 citations
Geophysical Research Letters
Remote Sensing in Agriculture
1.72
article

Solar Induced Fluorescence as an Application Ready Early Warning Indicator of Flash Drought

Beth Fuchs
article en
1 citations

Abstract

Abstract Flash drought has garnered major attention due to its devastating impact on both agricultural and ecological systems impacting production and income for producers, due to its rapid onset nature, and poor predictability. Solar‐induced fluorescence (SIF) is an increasingly well‐known and reliable indicator of vegetation health which captures rapid changes in how plants absorb and use light under stress. Recent efforts leveraging machine learning trained on spaceborne SIF and vegetation data from other sensors are producing seamless maps of SIF at spatial resolutions (∼5 km) aligned with land management needs. Three recent studies, Mohammadi et al. (2022, https://doi.org/10.1073/pnas.2202767119 ), Parazoo et al. (2024, https://doi.org/10.1029/2024GL108310 ), and Behera et al. (2025, https://doi.org/10.1029/2024GL113419 ), directly show the value of high‐resolution SIF mapping for flash drought early warning. Through advanced studies and calibration, we contend that SIF‐based data products are ready for immediate use by the drought monitoring community including the U.S. Drought Monitor.

Geophysical Research LettersVol. 52(23)
University of Nebraska–Lincoln (US), Jet Propulsion Laboratory (US)
National Aeronautics and Space Administration, California Institute of Technology, Jet Propulsion Laboratory
Openalex Percentile: Top 12%
Remote Sensing in Agriculture
1.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.