Work

Combining electromagnetic induction and satellite-based NDVI data for improved determination of management zones for sustainable crop production

Year: 2025

Type: article

Abstract: . Accurate delineation of management zones is essential for optimizing resource use and improving yield in precision agriculture. Electromagnetic induction (EMI) provides a rapid, non-invasive method to map soil variability, while the Normalized Difference Vegetation Index (NDVI) obtained with remote sensing captures above-ground crop dynamics. Integrating these datasets may enhance management zone delineation but presents challenges in data harmonization and analysis. This study presents a workflow combining unsupervised classification (clustering) and statistical validation to delineate management zones using EMI and NDVI data in a single 70 ha field of the patchCROP experiment in Tempelberg, Germany. Three datasets were investigated: (1) EMI maps, (2) NDVI maps, and (3) a combined EMI-NDVI dataset. Historical yield data and soil samples were used to refine the clusters through statistical analysis. The results demonstrate that four EMI-based zones effectively captured subsurface soil heterogeneity, while three NDVI-based zones better represented yield variability. A combination of EMI and NDVI data resulted in three zones that provided a balanced representation of both subsurface and above-ground variability. The final EMI-NDVI derived map demonstrates the potential of integrating multi-source datasets for field management. It provides actionable insights for precision agriculture, including optimized fertilization, irrigation, and targeted interventions, while also serving as a valuable resource for environmental modelling and soil surveying.

Source: SOIL

DOI: 10.5194/soil-11-655-2025