Airborne geophysics and remote sensing: some common ground in presentation techniques and interpretation

Synopsis

Airborne geophysical techniques — aeromagnetic, electromagnetic and gamma-ray spectrometer surveys — are long established methods in mineral exploration whose main debt to the advent of satellite imagery has been its use as topographic base maps of last resort. Historically, there has been little common ground between the treatment of geophysical data sets which reflect rock properties at depth, and the surficial overview provided by remote sensing.

The microcomputer technologies of the eighties have started to break down this barrier. In the first place, the techniques of presenting remote sensing data in colour are gradually being adopted and adapted for the presentation of (increasingly large) geophysical data sets with impact and meaning for the non-geophysicist. In the second place, inexpensive systems affordable by small exploration offices now provide the possibility of implementing Geographic Information Systems adequate for overlaying data sets of different origins — remote sensing, geophysical surveys, geochemical surveys — and conveniently integrating their interpretation.

Arguments concerning the cost — effectiveness of the various methods have to be considered, particularly now that the cost-to-the-user of acquiring remote sensing data is increasing towards its true cost.

In the practical situation, it is most often the case for a particular study area that only partial data sets are available, whether of remote sensing data, geophysical surveys, geochemical surveys or whatever, and that data quality (e.g. survey specifications) varies from one part of a study area to another. Logically, decison — making and concept-building for exploration strategies combines the interpretation of ALL relevant data — with due regard to data quality — to produce an earth-model that can be tested (by investment) in the next exploration phase. This parallels the approach of theory- building in pure science. But, as in pure science, theories (models) can only be proved wrong, not right.