TY  - JOUR
AU  - Brogi, C.
AU  - Huisman, J. A.
AU  - Pätzold, S.
AU  - von Hebel, C.
AU  - Weihermüller, L.
AU  - Kaufmann, Manuela
AU  - van der Kruk, J.
AU  - Vereecken, H.
TI  - Large-scale soil mapping using multi-configuration EMI and supervised image classification
JO  - Geoderma
VL  - 335
SN  - 0016-7061
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - FZJ-2018-05254
SP  - 133 - 148
PY  - 2019
AB  - Reliable and high-resolution subsurface characterization beyond the field scale is of great interest for precision agriculture and agro-ecological modelling because the shallow soil (~1–2m depth) is responsible for the storageof moisture and nutrients that are accessible to crops. This can potentially be achieved with a combination of direct sampling and Electromagnetic Induction (EMI) measurements, which have shown great potential for soilcharacterization due to their non-invasive nature and high mobility. However, only a few studies have used EMI beyond the field scale because of the challenges associated with a consistent interpretation of EMI data frommultiple fields and acquisition days. In this study, we performed a detailed EMI survey of an area of 1 km2 divided in 51 agricultural fields where previous studies showed a clear connection between crop performanceand soil properties. In total, nine apparent electrical conductivity (ECa) values were measured at each location with a depth of investigation ranging between 0–0.2 to 0–2.7 m. Based on the combination of ECa maps andavailable soil maps, an a priori interpretation was performed and four sub-areas with characteristic sediments and ECa were identified. Then, a supervised classification methodology was used to divide the ECa maps intoareas with similar soil properties. In a next step, soil profile descriptions to a depth of 2m were obtained at 100 sampling locations and 552 samples were analyzed for textural characteristics. The combination of the classifiedmap and ground truth data resulted in a 1m resolution soil map with eighteen units with a typical soil profile and texture information. It was found that the soil profile descriptions and texture of the EMI-based soil classes were significantly different when compared using a two-tailed t-test. Moreover, the high-resolution soil map corresponded well with patterns in crop health obtained from satellite imagery. It was concluded that this novel EMI data processing approach provides a reliable and cost-effective tool to obtain high-resolution soil maps to support precision agriculture and agro-ecological modelling.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000447095700014
DO  - DOI:10.1016/j.geoderma.2018.08.001
UR  - https://juser.fz-juelich.de/record/851722
ER  -