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001033976 037__ $$aFZJ-2024-06812
001033976 041__ $$aEnglish
001033976 1001_ $$0P:(DE-Juel1)188104$$aBuffat, Jim$$b0$$eCorresponding author
001033976 245__ $$aA Multi-Layer Perceptron Approach for SIF Retrieval in the O2-A Absorption band from Hyperspectral Imagery of the HyPlant Airborne Sensor System
001033976 260__ $$c2024
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001033976 520__ $$aAccurate estimation of solar-induced fluorescence (SIF) from passively sensedhyperspectral remote sensing data has been identified as instrumental in assessingthe photosynthetic activity of plants for various scientific and ecologicalapplications at various spatial scales. Different techniques to derive SIFhave been developed over the last decades. In view of ESA’s upcoming EarthExplorer satellite mission FLEX aiming to provide high-quality global imageryfor SIF retrieval an increased interest is placed in physical approaches.We present a novel method to retrieve SIF in the O2-A absorption band ofhyperspectral imagery acquired by the HyPlant sensor system. It aims at atight integration of physical radiative transfer principles and self-supervisedneural network training. To this end, a set of spatial and spectral constraintsand a specific loss formulation are adopted. In a validation study we find goodagreement between our approach and established retrieval methods as wellas with in-situ top-of-canopy SIF measurements. In two application studies,we additionally find evidence that the estimated SIF (i) satisfies a first-ordermodel of diurnal SIF variation and (ii) locally adapts the estimated opticaldepth in topographically variable terrain.
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001033976 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x1
001033976 588__ $$aDataset connected to CrossRef
001033976 7001_ $$0P:(DE-HGF)0$$aPato, Miguel$$b1
001033976 7001_ $$0P:(DE-HGF)0$$aAlonso, Kevin$$b2
001033976 7001_ $$0P:(DE-HGF)0$$aAuer, Stefan$$b3
001033976 7001_ $$0P:(DE-HGF)0$$aCarmona, Emiliano$$b4
001033976 7001_ $$0P:(DE-HGF)0$$aMaier, Stefan$$b5
001033976 7001_ $$0P:(DE-HGF)0$$aMüller, Rupert$$b6
001033976 7001_ $$0P:(DE-Juel1)162306$$aRademske, Patrick$$b7$$ufzj
001033976 7001_ $$0P:(DE-Juel1)172711$$aSiegmann, Bastian$$b8$$ufzj
001033976 7001_ $$0P:(DE-Juel1)129388$$aRascher, Uwe$$b9$$ufzj
001033976 7001_ $$0P:(DE-Juel1)129394$$aScharr, Hanno$$b10$$ufzj
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001033976 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129388$$aForschungszentrum Jülich$$b9$$kFZJ
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001033976 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5112$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001033976 9131_ $$0G:(DE-HGF)POF4-217$$1G:(DE-HGF)POF4-210$$2G:(DE-HGF)POF4-200$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-2173$$aDE-HGF$$bForschungsbereich Erde und Umwelt$$lErde im Wandel – Unsere Zukunft nachhaltig gestalten$$vFür eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten$$x1
001033976 9141_ $$y2024
001033976 920__ $$lyes
001033976 9201_ $$0I:(DE-Juel1)IAS-8-20210421$$kIAS-8$$lDatenanalyse und Maschinenlernen$$x0
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