AIRBORNE RADIOMETRIC DATA - A TOOL FOR RECONNAISSANCE GEOLOGICAL MAPPING USING A GIS

Airborne gamma ray spectrometer data collected by the Geological Surve y of Canada, gridded to a pixel resolution of 125 metres, is used to c reate digital images that show the spatial distributions of gamma ray spectrometer (radiometric) data: equivalent Uranium (eU), equivalent T horium (eTh), and Potassium (%K). These radioelement images are curren tly used by the Geological Survey to assist in geological mapping and mineral exploration. Data interpretation is traditionally made visuall y from hardcopy of pseudo-colored single-channel images, or in three-c hannel color composite images. Visual interpretation can be augmented by using an unsupervised classification procedure on the radioelement data. The resulting clusters are displayed as an image, and interprete d by digitally overlaying the digitized geological map. This brings ou t the similarities and differences be-tween units determined from fiel d mapping and units based on radioelement response. Images of the thre e radioelement channels were input to a migrating-means cluster analys is on an image processing system. The resulting classified image was i mported into a GIS. Other data sets in the GIS included table-digitize d bed rock and surficial geology maps and a binary map showing the pre sence of water bodies, derived from a density sliced Landsat Thematic Mapper band 5 image. Lakes and bogs, as well as regions covered by par ticular surficial units, were combined into a new binary image used to mask out regions where the radioelement response was unrelated to out crop. The classified radioelement image was then compared with the geo logical map using two-map overlay and area analysis cross-tabulation t echniques. The cross-tabulation clearly identifies those geological un its that have a distinctive radioelement response. By reclassifying th e map overlay, by imposing a color coding scheme that enhances bedrock geology classes, the relationship between the bedrock geology and rad ioelement response is enhanced. The degree of correlation between the two cartographic images is site dependent, rather than global, as migh t be expected. The correlation is not simply on the basis of the avera ge radioelement values, but also on the shape, texture, and extent of the radioelement clusters. Areas where the two maps differ indicate zo nes of possible interest for field verification of published field map s for the purposes of mineral exploration. Despite the relatively low spatial resolution of the gamma ray spectrometer data, the areas studi ed show quite strong spatial associations between the radioelement clu sters and bedrock units. The overlay technique was helpful in isolatin g inconsistencies between the two classified maps, suggesting sites fo r further localized field mapping.