Application of remote sensing to enhance, recognize and analysis of the structural characteristics of alteration-related lineations in the Bajestan area, East of Iran

Abstract:
The studied area is located at the east of Bajestan city and south west of Khorasan Razavi province. This region is at the north of the Lut Block, the largest structural block in east of Iran. Structure of this area is affected by activity of deep strike-slip faults in the boundary of the blocks. Lineaments are mapped by the means of SPOT-5 and Landsat satellite data and DEM data. Structural studies were carried out in two stages: at first, main faults were indicated, mapped and analyzed and then for more detail research, total lineaments (faults and joints) were mapped and analyzed. Verification studies were conducted with field surveys. Remote sensing studies indicate importance of applying enhancement filters like standard kernels on stereoscopic data like SPOT as an efficient tool for structural studies, especially for lineament extracting. Fractal studies and using fractures statistical parameters (based on fracture map obtained by remote sensing data (in the area in addition to determining fractal dimension, were used as complementary methods for recognition structural evolution and specifying the most probability of mineralization occurrence. Fractal, structural- statistical analyzes, field and remote sensing studies on fracture systems in the area indicate that structural elements in the studied area, most probably are related to the main strike-slip faults activities and can be considered as Riedel shear fractures in its wall of damage zone. Also the results indicate that most of the lineaments in this area are extensional fractures corresponding to both dykes emplacement and alteration zones associated with mineralization. Combining the mentioned information can play important role in identifying structural evolution processes and specifying areas with more mineralization potential.
Language:
Persian
Published:
Geosciences Scientific Quarterly Journal, Volume:26 Issue: 103, 2017
Pages:
169 to 182
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