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001032256 1001_ $$00000-0003-3401-7081$$aPacheco-Labrador, Javier$$b0$$eCorresponding author
001032256 245__ $$aEcophysiological variables retrieval and early stress detection: insights from a synthetic spatial scaling exercise
001032256 260__ $$aLondon$$bTaylor & Francis$$c2025
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001032256 520__ $$aThe 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.
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001032256 7001_ $$00000-0001-5887-7890$$aCendrero-Mateo, M. Pilar$$b1
001032256 7001_ $$00000-0002-5699-0352$$aVan Wittenberghe, Shari$$b2
001032256 7001_ $$00000-0002-1623-9337$$aHernandez-Sequeira, Itza$$b3
001032256 7001_ $$00000-0002-2275-0713$$aKoren, Gerbrand$$b4
001032256 7001_ $$00000-0002-7331-7004$$aPrikaziuk, Egor$$b5
001032256 7001_ $$00000-0003-3235-0948$$aFóti, Szilvia$$b6
001032256 7001_ $$00000-0001-6546-6459$$aTomelleri, Enrico$$b7
001032256 7001_ $$00000-0003-3299-4380$$aMaseyk, Kadmiel$$b8
001032256 7001_ $$00000-0002-7195-5280$$aČereković, Nataša$$b9
001032256 7001_ $$00000-0003-3468-0967$$aGonzalez-Cascon, Rosario$$b10
001032256 7001_ $$aMalenovský, Zbyněk$$b11
001032256 7001_ $$00000-0001-5676-3750$$aAlbert-Saiz, Mar$$b12
001032256 7001_ $$00000-0003-1294-9507$$aAntala, Michal$$b13
001032256 7001_ $$00000-0003-3211-5120$$aBalogh, János$$b14
001032256 7001_ $$00000-0002-0956-5628$$aBuddenbaum, Henning$$b15
001032256 7001_ $$aDehghan-Shoar, Mohammad Hossain$$b16
001032256 7001_ $$00000-0001-6874-6667$$aFennell, Joseph T.$$b17
001032256 7001_ $$00000-0002-0151-1334$$aFéret, Jean-Baptiste$$b18
001032256 7001_ $$aBalde, Hamadou$$b19
001032256 7001_ $$00000-0002-4999-673X$$aMachwitz, Miriam$$b20
001032256 7001_ $$00009-0002-4971-3370$$aMészáros, Ádám$$b21
001032256 7001_ $$00000-0001-5532-932X$$aMiao, Guofang$$b22
001032256 7001_ $$00000-0002-0537-6803$$aMorata, Miguel$$b23
001032256 7001_ $$00000-0002-3649-2786$$aNaethe, Paul$$b24
001032256 7001_ $$00000-0003-2839-522X$$aNagy, Zoltán$$b25
001032256 7001_ $$00000-0001-8737-706X$$aPintér, Krisztina$$b26
001032256 7001_ $$00000-0001-6560-986X$$aPullanagari, R. Reddy$$b27
001032256 7001_ $$00000-0002-0953-7045$$aRastogi, Anshu$$b28
001032256 7001_ $$0P:(DE-Juel1)172711$$aSiegmann, Bastian$$b29
001032256 7001_ $$00000-0003-3385-3109$$aWang, Sheng$$b30
001032256 7001_ $$00000-0003-3915-6099$$aZhang, Chenhui$$b31
001032256 7001_ $$aKopkáně, Daniel$$b32
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