عنوان مقاله :
اكتشاف نواحي داراي مس در منطقه قزلداش شهرستان خوي با استفاده از تصاوير هايپريون
عنوان فرعي :
Exploration of the Potential Copper Areas in Khoy City, Ghezel Dash, Using Hyperion Images
پديد آورندگان :
بلواسي، مهدي نويسنده كارشناسي ارشد سنجش از دور و GIS، دانشكده جغرافيا، دانشگاه تبريز , , اصغري سراسكانرود، صياد نويسنده asghari, sayad , زينالي، بتول نويسنده استاديار گروه اقليمشناسي، دانشكده ادبيات و علوم انساني، دانشگاه محقق اردبيلي , , صاحبي وايقان، سعيده نويسنده دانشجوي كارشناسي ارشد سنجش از دور و GIS، دانشكده جغرافيا، دانشگاه خوارزمي ,
اطلاعات موجودي :
فصلنامه سال 1394 شماره 92
كليدواژه :
نقشهبردار زاويهاي طيفي , هايپريون , واگرايي اطلاعات طيفي , سنجش از دور ابرطيفي
چكيده فارسي :
در سالهاي اخير با رشد سريع فناوري سنجش از دور در زمينه سنجندههاي ابرطيفي، افزايش قابليت تصويربرداري در صدها باند فراهم شده است. بهمنظور شناسايي و اكتشاف كانيهاي هر منطقه با بهرهگيري از رفتارهاي طيفي منحصربهفرد كانيها، آشكارسازي طيفي بهوسيله اين نوع از سنجندهها كه روشي نو محسوب ميشود، در اكتشاف معدن و زمينشناسي استفاده شده است. بنابراين، در اين تحقيق از تصاوير هايپريون ماهواره EO-1 براي شناسايي نواحي داراي مس در منطقه قزلداش شهرستان خوي واقع در شمال غرب ايران استفاده شد. در اين پژوهش، پس از پيشپردازشهاي لازم بر روي تصوير، كانيهاي مس در منطقه پژوهش كه در عمليات ميداني در تحقيقات پيشين استخراج شده بود، مشخص شد. سپس براي تطبيق امضاي طيفي اين كانيها با امضاي طيفي موجود در كتابخانه طيفي USGS از نمونهگيري مجدد استفاده شد. در نهايت، با بهكارگيري الگوريتمهاي SAM و SID نقشهها استخراج و با نقشههاي موجود مقايسه شد. نتايج نشان داد كه كارايي الگوريتم SAM با صحت كلي 85 درصد و ضريب كاپاي 80 درصد از الگوريتم SID با صحت كلي 76 درصد و ضريب كاپاي 68 درصد بيشتر است. همچنين، ميتوان از تصاوير ابرطيفي هايپريون با استفاده از الگوريتم SAM در شناسايي نواحي داراي فلز مس استفاده كرد.
چكيده لاتين :
Introduction
In recent decades, a large variety of science experts, including geology and mine scientists, have considered remote sensing technology as one of the most important instruments to receive information. Access to hyper spectral data is one of the main evolutions in the remote sensing technology. The main feature of the technology is its application in identification of minerals and detection of the minerals. Existing narrow and spectral bands of hyper spectral images provide the possible for geologic and mineralogy examination of an area. Paying attention to existing maps of the mineral distribution has been provided by classic method. Therefore, new sensor such as Hyperion has provided new capabilities in planning of biophysical and biochemistry features.
Materials and Methods
Ghezel Dash area is located in longitudes 44° 28´ – 44° 41´ and latitude 38° 43´ – 39° 06´ that is in 68 Km of Khoy City, Northwestern part of West Azerbaijan. The Satellite image employed in this research is Hyperion sensor of EO-1 satellite with 242 spectral bands. Satellite images of Landsat 7, ETM sensor, band 8 has also been used for geometric correction of the Hyperion sensor images. In this research, after necessary preprocessing including geometric and radiometric corrections on Hyperion images was performed, we used SAM and Spectral Information Divergence (SID) Algorithms 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 their mean angle. The SID is a probabilistic method that calculates spectral similarity between two pixel vectors based on the difference in the probability distribution obtained from their spectral signatures. The smaller the divergence,the more is the probability of similarity of pixels.
Results and Discussion
In this research Spectral Library of United States 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 algorithms of SAM and SID by spectral signatures of USGS spectral library andHyperion images spectrato detect minerals. Results of this research 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, the results of these two algorithms were compared with the maps produced in this region. The results indicate that the maps of SAM and SID methods have accuracy of 85 and 76 percent, respectively.
Conclusion
Comparison of the maps produced by the algorithms used in this study with available maps indicates that the minerals are present in the study area. Map of West Azarbaijan province confirmed the effects of industries and mines. The minerals of malachite and azurite were not confirmed in the Geological Organization report. Based on the results of the present study and evaluation of the overall accuracy, Spectral Information Divergence method (SID) can be used as an efficient method in classification based on exitedminerals for detection of metal mines. The results of this research also is consistent with the results of Amer et al. (2012) that had usedclassification methods of SAM and SID for classification of alteration zones associated with gold.
عنوان نشريه :
پژوهش هاي جغرافياي طبيعي
عنوان نشريه :
پژوهش هاي جغرافياي طبيعي
اطلاعات موجودي :
فصلنامه با شماره پیاپی 92 سال 1394
كلمات كليدي :
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