000872668 001__ 872668 000872668 005__ 20210130004247.0 000872668 0247_ $$2Handle$$a2128/23900 000872668 037__ $$aFZJ-2020-00159 000872668 041__ $$aEnglish 000872668 1001_ $$0P:(DE-Juel1)178852$$aBusch, Carsten$$b0$$eCorresponding author 000872668 245__ $$aUntersuchungen von nicht-destruktiven Verfahren zur Messung von Kohlenstoffakkumulation in Pflanzen: Sonneninduzierte Chlorophyllfluoreszenz und Eddy-Kovarianz$$f - 2020-12-17 000872668 260__ $$c2019 000872668 300__ $$a91 p. 000872668 3367_ $$2DataCite$$aOutput Types/Supervised Student Publication 000872668 3367_ $$02$$2EndNote$$aThesis 000872668 3367_ $$2BibTeX$$aMASTERSTHESIS 000872668 3367_ $$2DRIVER$$amasterThesis 000872668 3367_ $$0PUB:(DE-HGF)19$$2PUB:(DE-HGF)$$aMaster Thesis$$bmaster$$mmaster$$s1579180946_23008 000872668 3367_ $$2ORCID$$aSUPERVISED_STUDENT_PUBLICATION 000872668 502__ $$aMasterarbeit, Köln, 2019$$bMasterarbeit$$cKöln$$d2019$$o2020-12-17 000872668 520__ $$aVegetation drives 90 % of the gas exchange between biosphere and atmosphere resulting in the dependency of vital vegetation for stable gas concentrations in the atmosphere. The commonly used method for measuring gas fluxes is eddy covariance (EC), which measures the difference between incoming and outcoming gas and specifies these measurements on a source region called footprint. Another method for quantifying gas fluxes is sun-induced chlorophyll fluorescence (SIF), which is an electromagnetic signal in a spectral region between 640 and 800 nm emitted by plants during photosynthesis. SIF correlates strongly with the photosynthetic efficiency and therefore with the assimilation of carbon. In the following thesis a new method for linking SIF with gross primary production (GPP) is postulated. The Method uses the EC-Footprint for spatially weighting SIF and GPP. The used footprints were subsequently divided in different percentages. The aim of this thesis is the analysis of the correlation between SIF and GPP regarding the use of different percentages of the EC footprint. Hyperspectral scenes were taken with the sensor HyPlant on four days during summer of 2018. With these scenes SIF can be estimated due to the iFLD method which uses two oxygen absorption bands at 678 and 760 nm. Two additional SIF products were considered: F Ratio describes the ratio between the estimated F 687 and F 760 . F tot is characterized by the total Fluorescence of the entire emission spectrum. GPP were estimated with the measured net ecosystem exchange (NEE) by the method of REICHSTEIN et al. (2005). The estimation of the footprints was calculated by the method of KORMANN & MEIXNER (2001). A script written in python spatially matched and read the different data sets. Afterwards the script exported values of GPP and SIF for different percentages of the footprint, which were used to calculate the coefficient of determination per percentage per statio per SIF product. The results show a strong correlation with the use of small percentages of the footprint for the northern station, while the southern and both stations combined show no or small correlation in all percentages of the footprint. The extent of the fields could play an important role in the calculations due to the larger extent of the footprints. Higher percentages overlap the fields boundaries and therefore bordering plant species could manipulate the results. However, the results of the northern station show a possible use of the method for future investigations. 000872668 536__ $$0G:(DE-HGF)POF3-582$$a582 - Plant Science (POF3-582)$$cPOF3-582$$fPOF III$$x0 000872668 7001_ $$0P:(DE-Juel1)172754$$aKrieger, Vera$$b1$$eThesis advisor 000872668 7001_ $$0P:(DE-Juel1)129388$$aRascher, Uwe$$b2$$eThesis advisor 000872668 8564_ $$uhttps://juser.fz-juelich.de/record/872668/files/Busch_Carsten_Masterarbeit_2019.pdf$$yOpenAccess 000872668 8564_ $$uhttps://juser.fz-juelich.de/record/872668/files/Busch_Carsten_Masterarbeit_2019.pdf?subformat=pdfa$$xpdfa$$yOpenAccess 000872668 909CO $$ooai:juser.fz-juelich.de:872668$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire 000872668 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178852$$aForschungszentrum Jülich$$b0$$kFZJ 000872668 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)172754$$aForschungszentrum Jülich$$b1$$kFZJ 000872668 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129388$$aForschungszentrum Jülich$$b2$$kFZJ 000872668 9131_ $$0G:(DE-HGF)POF3-582$$1G:(DE-HGF)POF3-580$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lKey Technologies for the Bioeconomy$$vPlant Science$$x0 000872668 9141_ $$y2019 000872668 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 000872668 920__ $$lyes 000872668 9201_ $$0I:(DE-Juel1)IBG-2-20101118$$kIBG-2$$lPflanzenwissenschaften$$x0 000872668 980__ $$amaster 000872668 980__ $$aVDB 000872668 980__ $$aUNRESTRICTED 000872668 980__ $$aI:(DE-Juel1)IBG-2-20101118 000872668 9801_ $$aFullTexts