Use of PPI and n-dimensional visualizer in identifying and classifying the purest spectral pixels and curves by ASTER data (case study: southwest Ardestan, Isfahan)

Document Type : Original Article

Author

Amin Institute of Higher Education, Department of Geography, Foolad Shahr, Isfahan, Iran

Abstract

Many commonly used spectral image analysis techniques are based on the fact that remotely sensed imagery is sampled with numerous spectral bands at narrow bandwidths, making it possible to construct a spectrum for each pixel in the image. For identify and classify the most pure pixels and spectral curves, the n-dimensional visualizer is used after performing the Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The group of pixels in the corners of the scatter plot can be separated from other cloud data and selected as end-members corresponding to a particular type of minerals, rocks, or any individual phenomenon. Referring to the actual location of these pixels in the image, the end-member spectrum is extracted. Therefore, this process was performed after calibration of Internal Average Relative Reflection (IARR) on the ASTER dataset in southwest Ardestan, Isfahan. The geological units of the study area mainly consist of clay units (such as shale), carbonate rocks (calcite) and vegetation. This process resulted in the extraction of three end-member including illite, calcite and the green vegetation from the image.

Keywords

References

برای بدست آوردن طیف خالص پیکسل تصویر، شاخص خلوص پیکسل و مجسم کننده n- بعدی روش های مناسبی هستند. این فرایند منجر به استخراج سه عضو انتهایی از تصویر منطقه مورد نظر گردید. عضو انتهایی اول در باند ۶، ۸ و ۹ جذب نشان می دهد که مشابه طیف ایلیت است. این طیف به عنوان نماینده طیف کانی های رسی بویژه شیل در منطقه مورد مطالعه است. عضو انتهایی دوم در باند ۸ جذب اصلی و در باند ۵ جذب بسیار ضعیفی نشان می دهد که شباهت بسیاری به طیف کلسیت دارد. عضو انتهایی سوم در باند ۲ جذب و باند ۳ بازتاب قوی نشان می دهد که طیف گیاه سبزینه دار است. طیف های بدست آمده را می توان بعنوان طیف مرجع برای انجام پردازش های مختلف طیفی مانند SAM، LSU و ... مورد استفاده قرار داد.
 
4. مراجع
 
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5- ENVI V. 4.0 Tutorial
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8- Tavakkoli, H.; Cheraghi, Y. (2011). "Enhancement of Lithological units and green vegetations in southwest of Ardestan-Esfahan by relative absorption band depth method". 29th Symposium on Geosciences, 17-18 Feb., Tehran, Iran.

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History

  • Receive Date: 06 January 2020
  • Accept Date: 17 September 2020

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