This study evaluates the potential for mineral prospectivity mapping (MPM) within the Kerkesha area, southwestern Eritrea using remote sensing and geochemical data analysis. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data was used for mapping zones of hydrothermal alteration, while assessment of geologic structures is based on automated extraction of lineaments from a digital elevation model. Integration of these alteration and structural dataset with surface geochemical data were used in identifying pathfinder elements associated with Au-Cu-Zn mineralization as well as evaluating and delineating anomalous mineralization regions in this relatively underexplored region of Arabia Nubia Shield (ANS). Specifically, the modeling approach for the extraction and the interpretation of mineralization-related spectral footprints uses selective principal component analysis (SPCA), while the lineament features, which were extracted from different digital terrain models, were integrated with the soil geochemical data and modeled by principal component analysis (PCA). The results reveal a northeast-southwest trend of lineaments, delineate zones of hydrothermal alteration which indicate presence of multi-deposit type mineralization, and identify pathfinder elements. In addition, Au-Cu-Zn anomalous zones are extracted by one class support vector machine (OCSVM) and performances of such classification is validated by Kruskal-Wallis and Pearson's Chi-square tests. The results show significance in differences between the anomalous and non-anomalous zones and existence of a relationship between known mineral deposits and predicted anomalies. The proposed MPM shows promising results for robust automated delineation and understanding of mineralization processes.

Geochemical Anomaly and Mineral Prospectivity Mapping in GIS documents and explains, in three parts, geochemical anomaly and mineral prospectivity mapping by using a geographic information system (GIS). Part I reviews and couples the concepts of (a) mapping geochemical anomalies and mineral prospectivity and (b) spatial data models, management and operations in a GIS. Part II demonstrates GIS-aided and GIS-based techniques for analysis of robust thresholds in mapping of geochemical anomalies. Part III explains GIS-aided and GIS-based techniques for spatial data analysis and geo-information sybthesis for conceptual and predictive modeling of mineral prospectivity. Because methods of geochemical anomaly mapping and mineral potential mapping are highly specialized yet diverse, the book explains only methods in which GIS plays an important role. The book avoids using language and functional organization of particular commercial GIS software, but explains, where necessary, GIS functionality and spatial data structures appropriate to problems in geochemical anomaly mapping and mineral potential mapping. Because GIS-based methods of spatial data analysis and spatial data integration are quantitative, which can be complicated to non-numerate readers, the book simplifies explanations of mathematical concepts and their applications so that the methods demonstrated would be useful to professional geoscientists, to mineral explorationists and to research students in fields that involve analysis and integration of maps or spatial datasets. The book provides adequate illustrations for more thorough explanation of the various concepts. Explains GIS functionality and spatial data structures appropriate regardless of the particular GIS software in use Simplifies explanation of mathematical concepts and application Illustrated for more thorough explanation of concepts

Incorporating recent advances made in remote sensing technology, this text draws attention to ways in which remote sensing may minimize the environmental impact of exploration and improve cost-effectiveness. Topics include image processing, geographic information systems, current and future sensing

Using numerous operational and research-oriented examples, this text seeks to explain how the human eye and brain can extract and use remotely sensed data in the fields of applied geology and mineral exploration.