Advancing Precision Agriculture Through Integrated Resistivity Imaging: A Multi-Scale Soil Characterization Approach

This study introduces a novel integrative framework for subsurface soil characterization in precision agriculture using multi-dimensional electrical resistivity imaging. Field surveys over a 25 m × 15 m test plot employed Wenner and Dipole–Dipole electrode configurations, with data acquired along intersecting lines and inverted using a custom Python-based 1D Levenberg–Marquardt solver and commercial 2D/3D software (Res2DInv and Res3DInv). The integration of one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) resistivity models provides a more robust and spatially coherent interpretation of near-surface lithology. Results consistently delineate a resistive surface layer (~150–500 Ω·m) overlying a conductive zone (~50–125 Ω·m) at 1–3 m depth, corresponding to a potential clay-rich or water-saturated horizon. Notably, this study is among the first to systematically compare and validate 1D, 2D, and 3D inversion results in agricultural settings, supported by borehole correlation. The comparative analysis of array sensitivities further highlights the strengths of combining vertical and lateral resolution for improved subsurface imaging. This multi-scale geophysical approach advances the methodological frontier in precision agriculture by enabling accurate, non-invasive delineation of soil moisture zones and shallow aquifers—critical parameters for data-driven irrigation and land-use planning in tropical agroecosystems.