Investigation of Alteration Deposit Zones of Porphyry Copper Ore Using Multispectral Satellite Imagery (Aster, Landsat-8 and Sentinel-2) and Ground Controls (Case study: MasjedDaghi copper deposit - NW Iran)

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:

The design of Remote Sensing algorithms and the development of various methods of processing satellite images to identify porphyry copper deposits are among the important topics of studies in the field of mineral resource evaluation and their optimal exploitation. To this end, the determination of alteration zones provides a suitable tool for designing acceptable exploratory patterns. In this research with an almost comprehensive strategy and using the determination of alterations related to porphyry copper deposit based on Lowell and Gilbert model with three different strategies (visual, spectral and statistical processing) as well as the extraction of linements in the case area The study suggested the concentration range of the mineral for drilling. The study area in this article is Masjed Daghi porphyry copper deposit in the northeast of East Azerbaijan province, which consists of multispectral satellite images of ASTER, OLI of Landsat-8 and Sentinel-2 sensors for various processes including band ratio combinations, principal component analysis and pixel and subpixels basics spectral processing methods including SAM and MTMF, and statistical processing using the logical operator algorithm. Finally, by fuzzy and combining the layers of satellite image processing with geometric structures of the region (linements) which were extracted on Sentinel-2 data in two automatic and semi-automatic methods, the results were analyzed in GIS space and by comparing the presented results with the analysis of ground samples, the accuracy and conformity of the target areas were confirmed. User and producer accuracy for the area with the first priority were 78.54% and 78.36%, respectively, which are more appropriate criteria for introducing the area of ​​the drilling center.

Language:
Persian
Published:
Iranian Journal of Remote Sencing & GIS, Volume:14 Issue: 3, 2022
Pages:
47 to 74
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