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000866614 1001_ $$0P:(DE-Juel1)172711$$aSiegmann, Bastian$$b0$$eCorresponding author
000866614 245__ $$aThe High-Performance Airborne Imaging Spectrometer HyPlant-From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain
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000866614 520__ $$aThe HyPlant imaging spectrometer is a high-performance airborne instrument consisting of two sensor modules. The DUAL module records hyperspectral data in the spectral range from 400–2500 nm, which is useful to derive biochemical and structural plant properties. In parallel, the FLUO module acquires data in the red and near infrared range (670–780 nm), with a distinctly higher spectral sampling interval and finer spectral resolution. The technical specifications of HyPlant FLUO allow for the retrieval of sun-induced chlorophyll fluorescence (SIF), a small signal emitted by plants, which is directly linked to their photosynthetic efficiency. The combined use of both HyPlant modules opens up new opportunities in plant science. The processing of HyPlant image data, however, is a rather complex procedure, and, especially for the FLUO module, a precise characterization and calibration of the sensor is of utmost importance. The presented study gives an overview of this unique high-performance imaging spectrometer, introduces an automatized processing chain, and gives an overview of the different processing steps that must be executed to generate the final products, namely top of canopy (TOC) radiance, TOC reflectance, reflectance indices and SIF maps.
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000866614 7001_ $$00000-0002-8221-5739$$aAlonso, Luis$$b1
000866614 7001_ $$00000-0001-7249-7106$$aCelesti, Marco$$b2
000866614 7001_ $$00000-0002-7192-2032$$aCogliati, Sergio$$b3
000866614 7001_ $$0P:(DE-HGF)0$$aColombo, Roberto$$b4
000866614 7001_ $$00000-0001-8965-3427$$aDamm, Alexander$$b5
000866614 7001_ $$0P:(DE-HGF)0$$aDouglas, Sarah$$b6
000866614 7001_ $$0P:(DE-HGF)0$$aGuanter, Luis$$b7
000866614 7001_ $$0P:(DE-HGF)0$$aHanuš, Jan$$b8
000866614 7001_ $$0P:(DE-HGF)0$$aKataja, Kari$$b9
000866614 7001_ $$0P:(DE-HGF)0$$aKraska, Thorsten$$b10
000866614 7001_ $$0P:(DE-Juel1)130098$$aMatveeva, Maria$$b11
000866614 7001_ $$00000-0002-5283-3333$$aMoreno, Jóse$$b12
000866614 7001_ $$0P:(DE-Juel1)161185$$aMuller, Onno$$b13
000866614 7001_ $$0P:(DE-HGF)0$$aPikl, Miroslav$$b14
000866614 7001_ $$0P:(DE-Juel1)138884$$aPinto, Francisco$$b15
000866614 7001_ $$0P:(DE-Juel1)178996$$aQuirós Vargas, Juan$$b16
000866614 7001_ $$0P:(DE-Juel1)162306$$aRademske, Patrick$$b17
000866614 7001_ $$0P:(DE-HGF)0$$aRodriguez-Morene, Fernando$$b18
000866614 7001_ $$0P:(DE-HGF)0$$aSabater, Neus$$b19
000866614 7001_ $$0P:(DE-Juel1)7338$$aSchickling, Anke$$b20
000866614 7001_ $$0P:(DE-HGF)0$$aSchüttemeyer, Dirk$$b21
000866614 7001_ $$00000-0001-7564-7296$$aZemek, František$$b22
000866614 7001_ $$0P:(DE-Juel1)129388$$aRascher, Uwe$$b23
000866614 773__ $$0PERI:(DE-600)2513863-7$$a10.3390/rs11232760$$gVol. 11, no. 23, p. 2760 -$$n23$$p2760 -$$tRemote sensing$$v11$$x2072-4292$$y2019
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