Detection of regions with copper potential in Qzldash area of Khoy city by Hyperion images

In Recent decades، many of different science experts such as geology and mine have intentioned to Remote sensing technology as one of the most important instruments of information receiver. Access to hyper spectral data is one of the main evolutions in Remote sensing technology. The main feature of Remote sensing technology is its application in identifying of minerals that this is great help in detection of minerals. Existing narrow and high spectral bands of hyper spectral images provide possible of Geologic and mineralogy studying of area with better results. Pay attention to existed maps of mineral distribution have been provided by classic method، so new sensor such as Hyperion have provided new capabilities in planning and providing of Biophysical and Biochemistry features. Ghezel Dash area is in geography longitudes 44° 28´ – 44° 41´ and geography latitude 38° 43´ – 39° 06´ that is in 68 KM of Khoy city Northwest in west Azerbaijan. Used Satellite image in this research is Hyperion sensor of EO-1 satellite with 242 spectral bands. Satellite image of Landsat 7، ETM sensor، band of 8 has been used for geometric correction of Hyperion sensor images. In this research، after necessary preprocessing including geometric and radiometric corrections on Hyperion images were used SAM and SID Algorithm for detection of minerals. Spectral angular mapper (SAM) is an automated method of algebraic that calculates Similarity of the spectra between the spectrum of a pixel and the reference spectrum. The similarity between the two spectra is expressed as theirs mean angle. Spectral Information Divergence (SID) is a probabilistic method that calculates Spectral similarity between two pixel vectors based on difference in the probability distribution obtained from their spectral signatures. The smaller divergence is more the probability of similarity of pixels. In this research Spectral Library of America Geological Survey (USGS) was used for matching of unknown spectrum. Then، resample was performed by hyper spectral data of Hyperion with 142 bands. Minerals map was detected after running the algorithm SAM and SID by spectral signatures of USGS spectral library and Hyperion images spectra with the aim of detecting minerals. Results indicate that Chalcopyrite، Pyrite and Bornite have the maximum value in both methods respectively but their amounts are different in two algorithms. In these maps، secondary minerals such as Malachite and Azurite are very slight. In order to assess the accuracy of these algorithms، were compared the results of these two algorithms with the maps that have been produced in this region. Results indicate that maps of SAM and SID methods have accuracy of 85 and 76 percent respectively. Comparing maps produced by the algorithms used in this study with available maps Indicates that The minerals present in the study area Map of West Azarbaijan province confirmed of Industries and Mines and minerals malachite and azurite are the Geological Organization report was not confirmed. Based on the results of the present study and evaluate the overall accuracy، Spectral Information Divergence method (SID) can be used as an efficient method in classification of area based on exited minerals for detection of metal mines. The results of this research correspond whit the results of Amer et al (2012) that had used classification methods of SAM and SID for Classification of alteration zones associated with gold.