Real-time image processing is desirable in any field survey as it enables the success of the<br>experiment to be assessed on the spot and leads to a cost-effective survey since the experimental<br>geometry may be changed to attain the desired goals or the optimum depth of exploration. The<br>specific roles played by a novel imaging algorithm in optimizing survey design parameters, data<br>quality control, target definition and increased productivity are emphasized using examples drawn<br>from shallow dc and TEM investigations of glacial overburden, an old landfill site, complex<br>bedrock topography and underground mine workings. The effectiveness of this imaging tool is<br>gauged by comparison with borehole data and suggestions are offered for optimizing shallowdepth<br>surveys.


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