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Zohdy's method for the inversion of dc-resistivity data has been adapted to the inversion of airborne electromagnetic (AEM) data. AEM responses are first transformed into apparent-conductivity depth profiles, followed by an iterative adjustment of layer thicknesses and interval conductivities. The start model, including the number of layers, is determined from the data. This approach optimizes model flexibility without the need for parameter regularization. Results from Zohdy's inversion applied to TEMPEST, GEOTEM, and [Formula: see text] data acquired in a range of conductivity scenarios including the Bull Creek prospect in Queensland, Australia; the Boteti area, Botswana; and the Reid-Mahaffy test site in Ontario, Canada, show well-delineated target zones. A comparison with Occam's inversion shows good agreement between the conductivity-depth models recovered by the two methods, with Zohdy's inversion being 25 to 80 times faster.

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The quantities measured in transient electromagnetic (TEM) surveys are usually either magnetic field components or their time derivatives. Alternatively it might be advantageous to measure the spatial derivatives of these quantities. Such gradiometer measurements are expected to have lower noise levels due to the negative interference of ambient noise recorded by the two receiver coils. Error propagation models are used to compare quantitatively the noise sensitivities of conventional and gradiometer TEM data. To achieve this, eigenvalue decomposition is applied on synthetic data to derive the parameter uncertainties of layered‐earth models. The results indicate that near‐surface gradient measurements give a superior definition of the shallow conductivity structure, provided noise levels are 20–40 times smaller than those recorded by conventional EM instruments. For a fixed‐wing towed‐bird gradiometer system to be feasible, a noise reduction factor of at least 50–100 is required. One field test showed that noise reduction factors in excess of 60 are achievable with gradiometer measurements. However, other collected data indicate that the effectiveness of noise reduction can be hampered by the spatial variability of noise such as that encountered in built‐up areas. Synthetic data calculated for a vertical plate model confirm the limited depth of detection of vertical gradient data but also indicate some spatial derivatives which offer better lateral resolution than conventional EM data. This high sensitivity to the near‐surface conductivity structure suggests the application of EM gradiometers in areas such as environmental and archaeological mapping.

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