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001022048 0247_ $$2doi$$a10.1109/IGARSS52108.2023.10281579
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001022048 041__ $$aEnglish
001022048 1001_ $$0P:(DE-HGF)0$$aPato, Miguel$$b0
001022048 1112_ $$aIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium$$cPasadena$$d2023-07-16 - 2023-07-21$$wCA
001022048 245__ $$aFast Machine Learning Simulator of At-Sensor Radiances for Solar-Induced Fluorescence Retrieval with DESIS and Hyplant
001022048 260__ $$bIEEE$$c2023
001022048 300__ $$a7563-7566
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001022048 520__ $$aIn many remote sensing applications the measured radi-ance needs to be corrected for atmospheric effects to studysurface properties such as reflectance, temperature or emis-sion features. The correction often applies radiative transferto simulate atmospheric propagation, a time-consuming stepusually done offline. In principle, an efficient machine learn-ing (ML) model can accelerate the simulation step. This is thegoal pursued here in the context of solar-induced fluorescence(SIF) emitted by vegetation around the O2-A band using thespaceborne DESIS and airborne HyPlant spectrometers. Wepresent an ML simulator of at-sensor radiances trained onsynthetic spectra and describe its performance in detail. Thesimulator is fast and accurate, constituting a promising alter-native to a full-fledged, lengthy radiative transfer code for SIFretrieval in the O2-A band with DESIS and HyPlant.Index Terms— solar-induced fluorescence, hyperspectralsensors, radiative transfer, machine learning
001022048 536__ $$0G:(DE-HGF)POF4-5112$$a5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001022048 588__ $$aDataset connected to CrossRef Conference
001022048 7001_ $$0P:(DE-HGF)0$$aAlonso, Kevin$$b1
001022048 7001_ $$0P:(DE-HGF)0$$aAuer, Stefan$$b2
001022048 7001_ $$0P:(DE-Juel1)188104$$aBuffat, Jim$$b3$$ufzj
001022048 7001_ $$0P:(DE-HGF)0$$aCarmona, Emiliano$$b4
001022048 7001_ $$0P:(DE-Juel1)188300$$aMaier, Stefan$$b5$$ufzj
001022048 7001_ $$0P:(DE-HGF)0$$aMüller, Rupert$$b6
001022048 7001_ $$0P:(DE-Juel1)162306$$aRademske, Patrick$$b7$$ufzj
001022048 7001_ $$0P:(DE-Juel1)129388$$aRascher, Uwe$$b8$$ufzj
001022048 7001_ $$0P:(DE-Juel1)129394$$aScharr, Hanno$$b9$$ufzj
001022048 773__ $$a10.1109/IGARSS52108.2023.10281579
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