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The problem of equivalence in dc resistivity inversion is well known. The ability to invert resistivity data successfully depends on the uniqueness of the model as well as the robustness of the inversion algorithm. To study the problems of model uniqueness and resolution, theoretical data are inverted using variations of a nonlinear least‐squares inversion. It is only through model studies such as this one, where the true solutions are known, that realistic and meaningful comparisons of inversion methods can be undertaken. The data are inverted using three schemes of fixed‐layer thickness where only the resistivity varies, and the results are compared to the variable parameter inversion where both the layer resistivities and thicknesses are allowed to vary. The purpose of fixing the layer thicknesses is to reduce the number of parameters solved for during the inversion process. By doing this, nonuniqueness may be reduced. The fixed‐layer thickness schemes are uniform thickness, geometrical progression of thickness, and logarithmic progression of thickness. By applying each inversion scheme to different models, the layer thickness that minimizes the data rms error for various numbers of layers is determined. The curve of data rms error versus model rms error consists of three general regions: unique, nonunique, and no resolution. A good inversion routine simultaneously minimizes the data rms and model rms errors. The variable parameter scheme is best at simultaneously minimizing the data rms and model rms errors for models that can be resolved through the inversion process. The optimum number of layers in the model can be determined by using a modified F‐test.

The presence of magnetic iron oxides in the soil can seriously hamper the performance of electromagnetic sensors for the detection of buried land mines and unexploded ordnance (UXO). Previous work has shown that spatial variability in soil water content and texture affects the performance of ground penetrating radar and thermal sensors for land mine detection. In this paper we aim to study the spatial variability of iron oxides in tropical soils and the possible effect on electromagnetic induction sensors for buried low-metal land mine and UXO detection. We selected field sites in Panama, Hawaii, and Ghana. Along several horizontal transects in Panama and Hawaii we took closely spaced magnetic susceptibility readings using Bartington MS2D and MS2F sensors. In addition to the field measurements, we took soil samples from the selected sites for laboratory measurements of dual frequency magnetic susceptibility and textural characteristics of the material. The magnetic susceptibility values show a significant spatial variation in susceptibility and are comparable to values reported to hamper the operation of metal detectors in parts of Africa and Asia. The absolute values of susceptibility do not correlate with both frequency dependence and total iron content, which is an indication of the presence of different types of iron oxides in the studied material.