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Ecophysiological variables retrieval and early stress detection: insights from a synthetic spatial scaling exercise

insights from a synthetic spatial scaling exercise
Authors: Pacheco-Labrador, Javier; Cendrero-Mateo, M.Pilar; Van Wittenberghe, Shari; Hernandez-Sequeira, Itza; Koren, Gerbrand; Prikaziuk, Egor; Fóti, Szilvia; +26 Authors

Ecophysiological variables retrieval and early stress detection: insights from a synthetic spatial scaling exercise

Abstract

The ability to access physiologically driven signals, such as surfacetemperature, photochemical reflectance index (PRI), and suninducedchlorophyll fluorescence (SIF), through remote sensing(RS) are exciting developments for vegetation studies. Accessingthis ecophysiological information requires considering processesoperating at scales from the top-of-the-canopy to the photosystems,adding complexity compared to reflectance index-basedapproaches. To investigate the maturity and knowledge of thegrowing RS community in this area, COST Action CA17134SENSECO organized a Spatial Scaling Challenge (SSC). Challengeparticipants were asked to retrieve four key ecophysiological variablesfor a field each of maize and wheat from a simulated fieldcampaign: leaf area index (LAI), leaf chlorophyll content (Cab), maximumcarboxylation rate (Vcmax,25), and non-photochemicalquenching (NPQ). The simulated campaign data included hyperspectraloptical, thermal and SIF imagery, together with groundsampling of the four variables. Non-parametric methods that combinedmultiple spectral domains and field measurements were usedmost often, thereby indirectly performing the top-of-the-canopy tophotosystem scaling. LAI and Cab were reliably retrieved in mostcases, whereas Vcmax,25 and NPQ were less accurately estimated anddemanded information ancillary to RS imagery. The factors consideredleast by participants were the biophysical and physiologicalcanopy vertical profiles, the spatial mismatch between RS sensors,the temporal mismatch between field sampling and RS acquisition,and measurement uncertainty. Furthermore, few participantsdeveloped NPQ maps into stress maps or provided a deeper analysisof their parameter retrievals. The SSC shows that, despiteadvances in statistical and physically based models, the vegetationRS community should improve how field and RS data are integratedand scaled in space and time. We expect this work will guide newcomersand support robust advances in this research field.

International journal of remote sensing 0, 1 - 26 (2024). doi:10.1080/01431161.2024.2414435

Published by Taylor & Francis, London

Countries
Spain, Netherlands, France, France, France, Spain, France, France
Keywords

[SDE] Environmental Sciences, Temporal mismatch, down-scaling, plant physiology, Plant physiology, downscaling, photosystem, Spatial scaling, Remote sensing, Fluorescence, thermal, 620, ITC-HYBRID, Photosystem, Top of the canopy, hyperspectral, Hyperspectral, Thermal, top of the canopy, ITC-ISI-JOURNAL-ARTICLE, Down-scaling, fluorescence, spatial scaling, temporal mismatch

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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