000859494 001__ 859494 000859494 005__ 20250129092506.0 000859494 0247_ $$2Handle$$a2128/21206 000859494 037__ $$aFZJ-2019-00346 000859494 1001_ $$0P:(DE-Juel1)145932$$avon Hebel, Christian$$b0$$eCorresponding author$$ufzj 000859494 1112_ $$aTR32 Conference: Terrestrial Systems Research: Monitoring, Prediction & High Performance Computing$$cBonn$$d2018-04-04 - 2018-04-06$$wGermany 000859494 245__ $$aGround-based quantitative electromagnetic induction measurements and inversions show that patterns in airborne hyperspectral data are caused by subsoil structures 000859494 260__ $$c2018 000859494 3367_ $$033$$2EndNote$$aConference Paper 000859494 3367_ $$2DataCite$$aOther 000859494 3367_ $$2BibTeX$$aINPROCEEDINGS 000859494 3367_ $$2DRIVER$$aconferenceObject 000859494 3367_ $$2ORCID$$aLECTURE_SPEECH 000859494 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1548257257_28684$$xAfter Call 000859494 520__ $$aNon-invasive geophysical fixed-boom multi-coil electromagnetic induction (EMI) instruments return apparent electrical conductivity (ECa) values that depend on subsurface soil properties. Using different transmitter-receiver coil separations and orientations, ECa values of different depths of investigation (DOI) are obtained. After calibration, the quantitative EMI data are inverted to obtain electrical conductivity (σ) changes over depth assuming a layered subsurface model. Airborne hyperspectral measurements are used to estimate plant performance and growth, however, the top- and subsoil structural changes influencing plant performance and growth is often ignored. Here, we have investigated the origin of observed patterns in sun-induced fluorescence data by performing quantitative large-scale EMI measurements and quantitative inversions. The fixed-boom multi-coil EMI ECa data of nine coil configurations indicated spatial patterns due to buried paleo-river channels. After inversion, the obtained layered quasi-3D electrical conductivity model showed a relatively homogeneous ploughing layer and the presence of the paleo-river channels at > 1 m depth. Contrary to often used assumptions, σ of the ploughing layer only showed minor correlation to fluorescence data (r ~ 0.35), while the subsoil returned a significant correlation (r ~ 0.65) indicating a substantial influence of the subsoil on the plant performance, especially during dry periods which is probably due to differences in soil water holding capacity. For the first time, we have related soil-depth specific 3D subsurface information obtained by quantitative multi-coil EMI data inversions with sun-induced fluorescence data and have shown that above surface plant performance is caused by subsoil structural changes. Consequently, the subsurface structures should be incorporated in plant modeling as well as in terrestrial system modeling tools to improve the understanding of soil-vegetation-atmosphere exchange processes. 000859494 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0 000859494 7001_ $$0P:(DE-Juel1)130098$$aMatveeva, Maria$$b1$$ufzj 000859494 7001_ $$0P:(DE-Juel1)169328$$aVerweij, Elizabeth$$b2 000859494 7001_ $$0P:(DE-Juel1)129388$$aRascher, Uwe$$b3$$ufzj 000859494 7001_ $$0P:(DE-Juel1)162306$$aRademske, Patrick$$b4$$ufzj 000859494 7001_ $$0P:(DE-Juel1)168418$$aBrogi, Cosimo$$b5$$ufzj 000859494 7001_ $$0P:(DE-Juel1)168553$$aKaufmann, Manuela$$b6$$ufzj 000859494 7001_ $$0P:(DE-Juel1)140421$$aMester, Achim$$b7$$ufzj 000859494 7001_ $$0P:(DE-Juel1)129549$$aVereecken, Harry$$b8$$ufzj 000859494 7001_ $$0P:(DE-Juel1)129561$$avan der Kruk, Jan$$b9$$ufzj 000859494 8564_ $$uhttps://juser.fz-juelich.de/record/859494/files/CvH_EMI-4-Plants_Abstract_TR32_Conference2018_final.pdf$$yOpenAccess 000859494 8564_ $$uhttps://juser.fz-juelich.de/record/859494/files/CvH_EMI-4-Plants_Abstract_TR32_Conference2018_final.pdf?subformat=pdfa$$xpdfa$$yOpenAccess 000859494 909CO $$ooai:juser.fz-juelich.de:859494$$pdriver$$pVDB$$popen_access$$popenaire 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145932$$aForschungszentrum Jülich$$b0$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)130098$$aForschungszentrum Jülich$$b1$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129388$$aForschungszentrum Jülich$$b3$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)162306$$aForschungszentrum Jülich$$b4$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)168418$$aForschungszentrum Jülich$$b5$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)168553$$aForschungszentrum Jülich$$b6$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)140421$$aForschungszentrum Jülich$$b7$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129549$$aForschungszentrum Jülich$$b8$$kFZJ 000859494 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129561$$aForschungszentrum Jülich$$b9$$kFZJ 000859494 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0 000859494 9141_ $$y2018 000859494 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 000859494 920__ $$lyes 000859494 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0 000859494 9201_ $$0I:(DE-Juel1)ZEA-2-20090406$$kZEA-2$$lZentralinstitut für Elektronik$$x1 000859494 9801_ $$aFullTexts 000859494 980__ $$aconf 000859494 980__ $$aVDB 000859494 980__ $$aI:(DE-Juel1)IBG-3-20101118 000859494 980__ $$aI:(DE-Juel1)ZEA-2-20090406 000859494 980__ $$aUNRESTRICTED 000859494 981__ $$aI:(DE-Juel1)PGI-4-20110106