Data to Understanding soil and plant interaction by combining ground‐based quantitative electromagnetic induction and airborne hyperspectral data

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Title:Main Title: Data to Understanding soil and plant interaction by combining ground‐based quantitative electromagnetic induction and airborne hyperspectral data
Description:Abstract: This data set contains ground-based apparent electrical conductivity (ECa) of eight depth ranges of investigation. These were inverted for a three-layer electrical conductivity model. Five .dat files contain the depth-specific inverted electrical conductivity and respective layer thicknesses. Three dat-files correspond to airborne plant performance data. Additionally, six figures show the linear regressions between soil information (electrical conductivity property) and plant performance and one video shows the quasi-3D EMI inversion results.
Identifier:10.5880/TR32DB.31 (DOI)
Related Resource:Is Referenced By Text 10.1029/2018GL078658 (DOI)
Citation Advice:von Hebel, Christian, Matveeva, Maria, et al. (2018): Data to Understanding soil and plant interaction by combining ground‐based quantitative electromagnetic induction and airborne hyperspectral data. DOI:10.5880/TR32DB.31
Responsible Party
Creators:Christian von Hebel (Author), Maria Matveeva (Author), Elizabeth Verweij (Author), Patrick Rademske (Author), Manuela Sarah Kaufmann (Author), Cosimo Brogi (Author), Harry Vereecken (Author), Uwe Rascher (Author), Jan van der Kruk (Author)
Funding References:Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 32: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation
European Space Agency: FLEX-EU: ESA FLEX-EU
Publisher:CRC/TR32 Database (TR32DB)
Publication Year:2018
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Filename:2018GL078658_Soil-PlantInteraction_Data-Documentation_Information.zip
Data Type:Dataset - Dataset
Size:16 Datasets
File Size:2.2 MB
Date:Created: 24.07.2018
Mime Type:application/zip
Data Format:ASCII
Language:English
Status:Completed
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Download Permission:Free
Download Information:By downloading this dataset you accept adequate reference in case this data will be discussed or used in any publication or presentation. Please use the following citation: von Hebel, Christian, Matveeva, Maria (2018): Data to Understanding soil and plant interaction by combining ground‐based quantitative electromagnetic induction and airborne hyperspectral data. TR32DB. DOI 10.5880/TR32DB.31
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:[Creative Commons] Attribution 4.0 International (CC BY 4.0)
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Specific Information - Data
Temporal Extent:30.06.2015, 14:50:00 - 18.04.2016, 17:40:00
Lineage:The ground-based electromagnetic induction (EMI) measurements were performed using the three-coil CMD-MiniExplorer used with vertical coplanar (VCP) coils and the six-coil CMD-MiniExplorer Special Edition used with horizontal coplanar (HCP) coils. A single frequency GPS delivered spatial coordinates with low accuracy (meter range) but good precision. The processed high resolution georeferenced ECa values of nine coil configurations were regridded using a nearest neighbor interpolation with a spatial resolution of 1x1 m. These ECa maps were calibrated to obtain quantitative EMI data that were used in the inversion. We used inverted vertical electrical sounding data to predict ECa and linear regression with measured ECa obtained calibration factors. These turned the qualitative data into quantitative EMI data for inversion. The HCPs97 data contained few negative data and were not considered. To invert, we used the Maxwell-based full physical electromagnetic induction forward model (Keller & Frischknecht, 1966; Wait, 1951) in the shuffled complex evolution algorithm (Duan et al., 1993). The misfit between modeled and real data was evaluated using the L1-norm without smoothing or damping. The parallelized horizontally layered quasi-3D three-layer inversion scheme (von Hebel et al., 2014) ran on the JURECA supercomputer (Krause & Thörnig, 2016). The airborne HyPlant push-broom spectrometer (Rascher et al. 2015) passively measures sun-induced fluorescence (F) data with 1x1 m spatial resolution. To obtain quantitative maps of F, we used the improved Fraunhofer line depth (iFLD) approach (Wieneke et al., 2016), a modification of the 3FLD approach (Maier et al., 2003) further developed by Damm et al. (2015). After F retrieval a 2D digital (disk) filter that uses 2D convolution was applied to reduce noise. Additionally, we calculated NDVI. Linear regression between depth-specific EMI inversion results and plant data explain the subsurface role and plant performance. Acknowledgements: We acknowledge SFB/TR32 ‘Pattern in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation’ funded by DFG. We thank ESA funding the airborne fluorescence measurements, Contract 4000107143/12/NL/FF/If-CCN3. We thank TERENO and ACROSS, as well as the Jülich supercomputer center.
Subtype:Natural Science Data
Instruments:CMD-MiniExplorer [CMD-MiniExplorer]

Airborne Imaging Spectrometer [HyPlant]

Lippmann [4pointLight]
Metadata Details
Metadata Creator:Christian von Hebel
Metadata Created:25.07.2018
Metadata Last Updated:25.07.2018
Subproject:B6
Funding Phase:3
Metadata Language:English
Metadata Version:V50
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Metadata Downloads:13
Dataset Downloads:8
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