Prospectivity mapping of Pb–Zn SEDEX mineralization using remote-sensing data in the Behabad area, Central Iran

• Published in: International journal of remote sensing 2013-01, Vol.34 (4), p.1164-1179
• Main Authors: Molan, Yusuf Eshqi, Behnia, Pouran
• Format: Article
• Language: English
• Subjects: Advanced Spaceborne Thermal Emission and Reflection Radiometer; Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; color; Earth sciences; Earth, ocean, space; Exact sciences and technology; filters; Fundamental and applied biological sciences. Psychology; fuzzy logic; General aspects. Techniques; heat; Internal geophysics; iron oxides; Landsat; Metal geology; Metallic and non-metallic deposits; mineral content; mineralization; remote sensing; shale; spatial data; surveys; Teledetection and vegetation maps; X-ray diffraction
• ISSN: 1366-5901; 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2012.718460

Based on the characteristics of sedimentary exhalative (SEDEX) Pb–Zn deposits in the Central Iran Structural Zone, the following regional-scale geological criteria appear to be useful for prospectivity mapping of Pb–Zn mineralization in the study area: (1) presence and/or proximity to jarosite-, alunite-, and illite-bearing shales as the host rock; (2) presence of alteration iron oxide minerals; (3) proximity to – faults/lineaments; and (4) proximity to monzodioritic intrusive bodies with chlorite alteration minerals as the heat source. Spectral feature fitting (SFF) was applied to ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data to map the alteration minerals using the reference spectra from the United States Geological Survey (USGS) library. X-ray diffraction analyses of samples taken from the shale and monzodioritic intrusive bodies were used to define the mineral content of these rocks. The geological map and field data were used to assess the alteration maps generated from the SFF method. Landsat ETM+ (Enhanced Thematic Mapper Plus) data were used to interpret faults/lineaments in the study area. Directional filters applied on the Landsat ETM+ 7-4-1 (red–green–blue (RGB)) colour composite image produced better images for visual interpretation of faults and lineaments. A fuzzy logic approach was used as a geographical information system-based geodata integration technique to predict the occurrence of SEDEX Pb–Zn deposits in the study area. The best predictive map generated from integration of input data defines 10% of the study area as having potential for Pb–Zn mineralization.