@article { author = {Noori Khankahdani, Kamal}, title = {Spatial Data and Remote Sensing Techniques Integration to Detection and Slicing of Bavanat Red Bed Copper Deposits (NE Shiraz, Iran)}, journal = {Journal of Sciences, Islamic Republic of Iran}, volume = {31}, number = {4}, pages = {337-348}, year = {2020}, publisher = {University of Tehran}, issn = {1016-1104}, eissn = {2345-6914}, doi = {10.22059/jsciences.2020.290628.1007455}, abstract = {Bavanat red bed copper deposits (Jolani area) are located in south Sanandaj-Sirjan metamorphic belt and approximately 15 km NW of Bavanat. In terms of lithology, these deposits include purple to red siltstone(PSS) which are also seen among the layers of green sandstone(GS). Copper mineralization such as malachite is observed in the GS unit at the surface. Both PSS and GS units have Jurassic age. The current study, has used Landsat 8 and SPOT 5 images for RS processing. This study indicated that RGB=432 color composite in SPOT 5 image has the best contrast for enhancement and detection of PSS and GS units. Only the Landsat 8 fused image has been able to enhance and detect the GS unit. Also, based on band ratio technique, RGB=(b6/b2), (b5/b3), (b7/b1) color composite for Landsat 8 data, has the best contrast for PSS and GS units. PCA method shows that RGB=PC4, PC2, PC1 for Spot 5 dataand RGB=PC1, PC2, PC3 for Landsat 8 data have the best contrast for enhancement and detection of the Bavanat red bed copper deposits. In this study, different methods of supervised classification such as SAM, SID and SVM were reviewed. Among these methods, SVM technique has the best layout for SPOT 5 image. This important layout as a basic geological map, can be very useful in additional exploration studies on the Bavanat red bed deposits.}, keywords = {Bavanat,Red Bed Copper Deposits,Spatial and RS Data}, url = {https://jsciences.ut.ac.ir/article_78694.html}, eprint = {https://jsciences.ut.ac.ir/article_78694_3a32c31964501c6bddba431fa1b7dace.pdf} }