• Other language title
    تلفيق داده هاي مكاني و تكنيك هاي دورسنجي در شناسايي و تفكيك ذخاير سرخ لايه مس بوانات (شمال شرق شيراز، ايران)
  • Title of article

    Spatial Data and Remote Sensing Techniques Integration to Detection and Slicing of Bavanat Red Bed Copper Deposits (NE Shiraz, Iran)

  • Author/Authors

    Noori Khankahdani, K. Department of Geology - Islamic Azad University Shiraz Branch, Shiraz, Iran

  • Pages
    12
  • From page
    337
  • To page
    348
  • 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 data and 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
  • Journal title
    Journal of Sciences Islamic Republic of Iran
  • Serial Year
    2020
  • Record number

    2525185