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Abstract
Application of Remote Sensing in Mineral Exploration
John Gingerich
Golder Associated Ltd
Canada
John.Gingerich@rogers.com
Mahasa Roostaii , Claude A Durocher , Maryam Dehghani
Abstract
Recently, remote sensing technology represents useful information in mineral exploration. Since satellite images provide data in different regions of electromagnetic spectrum, they can be widely used in geological applications. The main goal of this paper is to demonstrate the superiority of the remote sensing technology in mineral exploration in Khoy-Oshnavieh area located in the north-west of Iran. Several kinds of remote sensing data were used to prepare different information layers which play important roles in mineral exploration. The most important layers are structures of the study area as well as alteration. The study mainly focuses on techniques used to process different remote sensing data to extract the information layers. These data were ETM+, ASTER and RADARDAT. Different kinds of alteration such as clay and iron-oxide can be extracted using ETM+ and ASTER which are multi-spectral images. After preprocessing step including the radiometric and geometric correction, several processing tools such as Crosta, selective principal component analysis and band ratio techniques were applied to introduce the areas with the most probability of alteration. Because of spectral overlaps between altered areas and some other objects in the image, different masks were applied to refine the alteration layer. These masks were produced using different methods such as image classification. The remained noise in the alteration layer was eliminated using visual interpretation. Moreover, different types of structures such as rings and lineaments may help us to find the areas with the probability of mineralization. Hence, in order to extract the large-scale structures of the study region, the RADARSAT image in standard mode was used on which different highpass filters were applied. The final structure layer was prepared using visual interpretation. The alteration and structure information with the other information layers such as geology maps, geophysics and geochemistry data were then used to produce the primary exploration model in GIS. Two different models included fuzzy logic and weight of evidence, were tested to find the promised areas. The best results were achieved by giving higher weights to the remote sensing layers. The quality of the results was evaluated by checking the field. They showed the high reliability of the remote sensing data in mineral exploration.
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