Integrated image processing and GIS-based techniques using knowledge-driven approaches to produce potential radioactivity map for the uraniferous granite of Egypt

Interpretation of remote sensing data for allocating of lithologic units and for mapping of radioactive zones, supplies a valuable utility to produce Potential Radioactivity Map for the uraniferous granite. The study applied a digital image processing technique including interpretation and manipulation of Geophysical Airborne gamma-ray spectrometry data and The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor image data of Terra satellite over a case study well-known radioactive area of El-Missikat, El-Eridya and Kab Amiri areas in the Central Eastern Desert, Egypt. The possible forms of digital image manipulation are categorised into the following procedures: Minimum Noise Fraction (MNF) rotation, colour composite, band ratios, Principle Component Analysis (PCA), decorrelation stretching and Iterative Self-Organising Data Analysis Technique Algorithm (Isodata) unsupervised classification. Matched Filter (MF) classification was performed on the data to map a chosen well- known alteration mineral association with the uranium occurrences from USGS library. Each of these constructed images with the surveyed Airborne spectrometry data (equivalent uranium) has been given a suitable weight to be integrated using Geographic Information System (GIS) tools to delineate the most promising potential radioactive zones. Moreover, the other comparatively and quantitatively goal of the study was to evaluate the performance of various knowledge-driven mineral probability modelling.