Remote monitoring of plant drought stress with the apparent heat capacity

Drought stress has profound impacts on ecosystems and societies, particularly in the context of climate change. Traditional drought indicators, which often rely on integrated water budget anomalies at various time scales, provide valuable insights but often fail to deliver clear, real-time assessments of vegetation stress. This study introduces the Cooling Efficiency Factor Index (CEFI), a novel metric purely derived from geostationary satellite observations, to detect vegetation drought stress by analyzing daytime surface warming anomalies. The CEFI is based on the principle that dry surfaces warm more rapidly than wet ones under identical radiative forcing, due to reduced evapotranspiration caused by stomatal closure during drought stress conditions. This process alters the apparent heat capacity of vegetated surfaces, which is defined here as the effective heat capacity that can be measured by remotely sensed data of radiation and surface temperature. By leveraging high-frequency, high-resolution data of apparent heat capacity from geostationary satellites, the study demonstrates the CEFI's ability to assess drought stress conditions on vegetated surfaces. In fact, the CEFI correlates well with evapotranspiration anomalies from established datasets used as reference, including GLEAM, ERA5-Land, and NDVI anomalies measured by MODIS, with linear correlation coefficients around 0.5 similar to the reference datasets over regions with NDVI larger than 0.2. Results underscore the CEFI's sensitivity to vegetation type, soil moisture variability, and environmental conditions, illustrating its effectiveness in identifying vegetation drought stress. The CEFI represents a promising tool for real-time drought monitoring and integration into early warning systems, particularly for arid and semi-arid regions. By complementing existing drought assessment methods, the CEFI paves the way for advancements in land-surface process studies and improved drought risk management.

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Publication Details

Journal
The Science of The Total Environment
Published
2025-09-05
DOI
https://doi.org/10.1016/j.scitotenv.2025.180391
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Remote monitoring of plant drought stress with the apparent heat capacity

Matteo Piccardo, Marco Girardello, Guido Ceccherini, Matteo Zampieri et al.
The Science of The Total Environment
Plant Water Relations and Carbon Dynamics
article

Remote monitoring of plant drought stress with the apparent heat capacity

Matteo Piccardo, Marco Girardello, Guido Ceccherini, Matteo Zampieri, Alessandro Cescatti, Ibrahim Hoteit
article en

Abstract

Drought stress has profound impacts on ecosystems and societies, particularly in the context of climate change. Traditional drought indicators, which often rely on integrated water budget anomalies at various time scales, provide valuable insights but often fail to deliver clear, real-time assessments of vegetation stress. This study introduces the Cooling Efficiency Factor Index (CEFI), a novel metric purely derived from geostationary satellite observations, to detect vegetation drought stress by analyzing daytime surface warming anomalies. The CEFI is based on the principle that dry surfaces warm more rapidly than wet ones under identical radiative forcing, due to reduced evapotranspiration caused by stomatal closure during drought stress conditions. This process alters the apparent heat capacity of vegetated surfaces, which is defined here as the effective heat capacity that can be measured by remotely sensed data of radiation and surface temperature. By leveraging high-frequency, high-resolution data of apparent heat capacity from geostationary satellites, the study demonstrates the CEFI's ability to assess drought stress conditions on vegetated surfaces. In fact, the CEFI correlates well with evapotranspiration anomalies from established datasets used as reference, including GLEAM, ERA5-Land, and NDVI anomalies measured by MODIS, with linear correlation coefficients around 0.5 similar to the reference datasets over regions with NDVI larger than 0.2. Results underscore the CEFI's sensitivity to vegetation type, soil moisture variability, and environmental conditions, illustrating its effectiveness in identifying vegetation drought stress. The CEFI represents a promising tool for real-time drought monitoring and integration into early warning systems, particularly for arid and semi-arid regions. By complementing existing drought assessment methods, the CEFI paves the way for advancements in land-surface process studies and improved drought risk management.

The Science of The Total EnvironmentVol. 1000
Trinity College Dublin (IE), European Commission (BE), Joint Research Centre (IT), King Abdullah University of Science and Technology (SA)
European Commission
Openalex Percentile: Top 78%
Plant Water Relations and Carbon Dynamics
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