This title appears in the Scientific Report :
2014
Combined satellite and proximal soil sensing approach for improved catchment characterization
Combined satellite and proximal soil sensing approach for improved catchment characterization
Recent developments in proximal soil sensing techniques offer unique opportunities to characterize the vadose zone across spatial scales, especially when combining these techniques with remote sensing approaches. Here, we link RapidEye satellite imagery and multi-depth-level electromagnetic inductio...
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Personal Name(s): | von Hebel, Christian (Corresponding Author) |
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Rudolph, Sebastian / Weihermüller, Lutz / Huisman, Johan Alexander / Mester, Achim / Vereecken, Harry / van der Kruk, Jan | |
Contributing Institute: |
Agrosphäre; IBG-3 |
Published in: | 2014 |
Imprint: |
2014
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Conference: | Terneno International Conference 2014, Bonn (Germany), 2014-09-29 - 2014-10-03 |
Document Type: |
Conference Presentation |
Research Program: |
Terrestrial Systems: From Observation to Prediction Modelling and Monitoring Terrestrial Systems: Methods and Technologies |
Publikationsportal JuSER |
Recent developments in proximal soil sensing techniques offer unique opportunities to characterize the vadose zone across spatial scales, especially when combining these techniques with remote sensing approaches. Here, we link RapidEye satellite imagery and multi-depth-level electromagnetic induction (EMI) measurements of 20 ha arable land around Selhausen (Germany) and investigate one specific 1.1 ha plot using geophysical and conventional soil sampling methods. For the area, large-scale leaf area index (LAI) was estimated from the satellite images and compared to the lateral and vertical apparent electrical conductivity (ECa) distributions that were recorded using the multi-configuration EMI. Increasing and decreasing ECa values with depth separated the area into the lower terrace (LT) and the upper terrace (UT), respectively. At the mainly gravelly UT, distinct LAI patterns coincided with higher ECa values that were measured with the deepest sensing EMI coil configuration. Soil analysis revealed higher subsoil clay content and a related higher water holding capacity that enabled better crop performance under drought conditions. To extract depth information, we selected a plot that showed UT sediments in the eastern part and LT sediments (loamy silt) toward the west. Here, we developed a dedicated quantitative EMI inversion scheme to obtain a layered subsurface electrical conductivity model from multi-configuration EMI data. The smoothly changing lateral and vertical electrical conductivities were validated with grain size distribution maps and two previously measured 120 m long electrical resistivity tomography (ERT) transects. Overall, the 3-D subsurface model obtained with EMI inversions and the independent ERT inversions showed very similar subsurface structures. Small differences in absolute electrical conductivity values within certain layers were attributed to varying soil moisture states at different dates. Consequently, the combined sensor and data processing approach opens up new perspectives for an improved characterization of relatively large areas up to the km2-scale and provided subsoil information that can improve models that aim at improved descriptions of catchment processes. |