شناسایی و تفکیک منطقه‌های با خلوص بالای کانی کلسیت در واحدهای کربناتی با استفاده از داده‌های چندطیفی استر و سنتینل 2 (بررسی موردی شمال غرب شهرکرد)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه شهرکرد

2 دانشگاه بیرجند

چکیده

امروزه بررسی­های زمین‌شناسی و شناسایی مواد معدنی با استفاده از فن­آوری سنجش از دور، جایگاه ویژه­ای در تعیین موقعیت کانسارها دارد و می­تواند در بخش پی­جویی اولیه به کار رود. در این پژوهش، واحدهای کربناتی با خلوص کلسیت بالا با استفاده از داده­های چندطیفی استر و سنتینل 2 شناسایی و تفکیک شدند. برای درستی­سنجی و تطبیق نتایج، پیمایش صحرایی انجام شد و نمونه­های سنگی برداشت شده تجزیه شیمیایی به روش طیف­سنجی فلئورسانس پرتوی X (XRF) و تجزیه کانی­شناسی به روش پراش پرتوی  X (XRD) شدند. نتایج نشان داد که خلوص کانی کلسیت (CaCO3) در واحد کربناتی شناسایی شده 22/97 درصد است. با پردازش داده­های استر، قدرت تفکیک مکانی نوارهای مرئی و فروسرخ موج کوتاه با استفاده از داده کمکی سنتینل 2، به 10 متر بهبود یافت. سپس ترکیب نواری 831 و همچنین الگوریتم‌های حذف پیوستار (CR)، فیلتر تطبیق یافته (MF) و نقشه برداری زاویه طیفی (SAM) در کنار شاخص طیفی کلسیت (CI) برای تشخیص کانی کلسیت اعمال شد. با مقایسه نتایج الگوریتم­ها، تصویر برآمده از الگوریتم MF به خاطر شباهتی که به تصویر شاخص طیفی کلسیت داشت در رده­بندی به روش SAM استفاده شد و سرانجام نقشه پراکنش کلسیت ایجاد گردید. نتایج به دست آمده از مقایسه میزان تفکیک کانی کلسیت در روش SAM با شاخص طیفی کلسیت نشان داد که در این رده بندی، 66/83 درصد از منطقه­های کلسیت­دار بدرستی به این کانی تعلق گرفته است. از این رو با استفاده از شاخص­ها و روش­های رده­بندی بر پایه رفتار طیفی، می­توان مواد معدنی را با دقت قابل قبول و کمترین هزینه شناسایی کرد.

کلیدواژه‌ها


عنوان مقاله [English]

Recognation and separation of high purity calcite mineral regions in carbonate units using Aster multispectral data and Sentinel 2 (case study northwest of Shahrekord)

نویسندگان [English]

  • Bozorgmehr Bozorgmehr 1
  • Esmaiil Moradian 1
  • hamidreza Reyahi Bakhtiari 1
  • Alireza Davoudian 1
  • Mohsen Karim 2
  • nahid Shabanian 1
1
2
چکیده [English]

Remote sensing has found a special technique and effective in the geological studies and mineral identification for the determination of minerals in the primary detection. The purpose of this study is to recognize the high purity calcite mineral regions in carbonate units using Aster and sentinel 2 images. Sampling of rocks and laboratory analysis using XRF and XRD for verification. The results showed that 97.22% the purity of calcite mineral (CaCO3) is recognized in carbonate unit. The Sentinel 2 auxiliary data improved the spatial resolution of Aster visible and infrared shortwave bands to 10m. As well as CR, MF and SAM algorithms were calculated beside the calcite spectral index (CI) and RGB:831 image for calcite mineralization. By comparing the results of the algorithms, MF image had resembled to calcite spectral index image, so it was used in SAM method and calcite classification map was calculated. The results of comparing showed that calcite minerals categorized in the SAM method with the calcite index, 83.66% of calcite areas was correctly assigned to this mineral. Therefore, using spectral indexes and classification methods, minerals can be identified with the lowest cost and acceptable accuracy.
 

کلیدواژه‌ها [English]

  • Aster images
  • detection
  • Cclcite mineral (CaCO3)
  • spectral angle mapper
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