Physiological and Hyperspectral Responses of Individual European Beech Trees to Drought Stress: A Pilot Study During a Compound Drought and Heatwave Event

European beech is a species of both ecological and economic relevance in Europe. However, its high sensitivity to drought poses a significant risk amid increasing climate extremes. This study aimed to evaluate the physiological and spectral responses of beech to drought stress, combining in situ leaf-level measurements with hyperspectral remote sensing data. We set up the experiment in an Alpine European beech forest in northern Italy, which included three water treatments: control, water stress, and irrigation. Physiological data (i.e., leaf gas exchange and chlorophyll content), alongside airborne hyperspectral remote sensing data, were collected from 20 to 29 July 2022 during a compound drought and heatwave (CDHW) event. Water-stressed trees exhibited significantly reduced photosynthetic rates, lower photosystem II efficiency, and higher non-photochemical quenching, indicating impaired photosynthetic performance. Water-stressed beech exhibited up to 70% reduced photosynthesis and 35% lower leaf chlorophyll content under severe drought conditions. Hyperspectral vegetation indices, particularly the RENDVI, CIRE, and SPRI, successfully detected stress status. This exploratory study, based on an intensive analysis of four trees, demonstrates the feasibility of integrating physiological measurements with hyperspectral remote sensing to detect drought-stress signatures in European beech at the individual-tree level, establishing a methodological framework for more extensive future research.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2026-02-03
DOI
https://doi.org/10.3390/rs18030488
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Physiological and Hyperspectral Responses of Individual European Beech Trees to Drought Stress: A Pilot Study During a Compound Drought and Heatwave Event

Mirco Rodeghiero, S. Pilati, Karolina Sakowska, Chiara Torresan et al.
Remote Sensing
Remote Sensing in Agriculture
article

Physiological and Hyperspectral Responses of Individual European Beech Trees to Drought Stress: A Pilot Study During a Compound Drought and Heatwave Event

Mirco Rodeghiero, S. Pilati, Karolina Sakowska, Chiara Torresan, Francesca Ugolini, Mustafa Elfahl, Michele Dalponte, Luca Belelli Marchesini, Luis Alonso Chorda
article en

Abstract

European beech is a species of both ecological and economic relevance in Europe. However, its high sensitivity to drought poses a significant risk amid increasing climate extremes. This study aimed to evaluate the physiological and spectral responses of beech to drought stress, combining in situ leaf-level measurements with hyperspectral remote sensing data. We set up the experiment in an Alpine European beech forest in northern Italy, which included three water treatments: control, water stress, and irrigation. Physiological data (i.e., leaf gas exchange and chlorophyll content), alongside airborne hyperspectral remote sensing data, were collected from 20 to 29 July 2022 during a compound drought and heatwave (CDHW) event. Water-stressed trees exhibited significantly reduced photosynthetic rates, lower photosystem II efficiency, and higher non-photochemical quenching, indicating impaired photosynthetic performance. Water-stressed beech exhibited up to 70% reduced photosynthesis and 35% lower leaf chlorophyll content under severe drought conditions. Hyperspectral vegetation indices, particularly the RENDVI, CIRE, and SPRI, successfully detected stress status. This exploratory study, based on an intensive analysis of four trees, demonstrates the feasibility of integrating physiological measurements with hyperspectral remote sensing to detect drought-stress signatures in European beech at the individual-tree level, establishing a methodological framework for more extensive future research.

Remote SensingVol. 18(3)
Fondazione Edmund Mach (IT), University of Helsinki (FI), Mediterranean Center for Environmental Studies (ES), Ministry of Agriculture and Forestry (FI), National Research Council (IT)
Climate action
Openalex Percentile: Top 71%
Remote Sensing in Agriculture
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.