Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements
Patterns in crop development and yield are often directly related to lateral and vertical changes in soil texture causing changes in available water and resource supply for plant growth, especially under dry conditions. Relict
geomorphologic features, such as old river channels covered by shallow sediments can challenge assumptions of uniformity in precision agriculture, subsurface hydrology, and crop modeling. Hence a better detection of these
subsurface structures is of great interest. In this study, the origins of narrow and undulating leaf area index (LAI) patterns showing better crop performance in large scale multi-temporal satellite imagery were for the
first time interpreted by proximal soil sensor data. A multi-receiver electromagnetic induction (EMI) sensormeasuring soil apparent electrical conductivity (ECa) for six depths of exploration (DOE) ranging from 0–0.25 to
0–1.9 m was used as reconnaissance soil survey tool in combination with selected electrical resistivity tomography (ERT) transects, and ground truth texture data to investigate lateral and vertical changes of soil properties at
ten arable fields. The moderate to excellent spatial consistency (R
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