Remote predictive mapping can provide a base for geological mapping. This thesis investigates different methods for remotely mapping the igneous rocks and their host sedimentary rocks on Axel Heiberg Island, using the already available data sets. Axel Heiberg Island has been chosen as the platform for establishing the most suitable method of mapping igneous rocks and other geological features in the Canadian Arctic Archipelago. The igneous rocks on Axel Heiberg Island are important to understand and study because of their impact on the petroleum system and energy resources that they may contain, and because of the possibility of unravelling the debatable tectonic history of Canadian Arctic Archipelago.
To identify the geological information of the study area three remote predictive mapping approaches have been studied. The first remote predictive approach uses remote sensing techniques such as color composite and band ratio to highlight the igneous rocks on Axel Heiberg Island. The satellite sensors that have been employed to analyse the geological information on the surface of the study area are: ASTER and LANDAST satellite images. Spectral correlation technique is employed for the second and third approach. For the second mapping approach gravity and magnetic field anomalies are spectrally correlated and filtered. The filtered gravity and magnetic field anomalies provided key constrains on analysis of geological features, especially igneous rocks and salt domes. The same procedure has been used to spectrally correlate magnetic field anomalies and silica weight percentage of surface rocks derived from ASTER thermal bands.
The first remote predictive mapping technique proved to be an effective technique for initial assessment of the study area and highlighting the target geological features. Using color composite technique it was inferred that the igneous rocks in the study area have the highest
reflectance in Landsat band3 and ASTER band2. The results in the second approach were constrained by low resolution of gravity data; however the thickness trend of igneous rocks and salt domes were revealed. The third approach proved to be the most effective among the other two approaches, where result map matched well with the only available accurate geological map of the study area.