Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment

Geosciences

MohammedA. K. El-Ghali¹  Khaled Alzebdah²  Sobhi Nasir³  Sankaran Rajendran³  Mohammed Al-Battashi⁴  Ali Salim Al-Rajhi⁴ 

[1] Department of Earth Sciences, Sultan Qaboos University, Al-Khod, 123 Muscat, Oman;Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Al-Khod, 123 Muscat, Oman;Earth Science Research Centre, Sultan Qaboos University, Al-Khod, 123 Muscat, Oman;Public Authority for Mining, Directorate of General of Minerals, Ministry of Commerce and Industry, P.O. Box: 2088, Muscat, Oman;

关键词: spectral signatures;    remote sensing;    ASTER;    Landsat (ETM+);    exotic limestone;    industrial rock;    mapping;    Oman;   

DOI  :  10.3390/geosciences8040145

来源: DOAJ

【 摘 要 】

This study demonstrates the capability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor data to remotely map industrial carbonate rocks known as the ‘Oman exotics’ of the Sultanate of Oman. We measured reflectance spectra of marble using a PIMA™ spectrometer and studied their spectral absorptions distinguishing calcite from spectral absorptions of dolomite of the same region. The spectral band 8 of ASTER is processed by simple decorrelation stretch image processing method to map the exotic limestone rock of the Nakhl region, Oman. Results showed that carbonate rocks displayed distinctive tonal variation on the image. A comparative study with the spectral band 7 of Landsat 7 (ETM+) does not discriminate the calcite-bearing marbles and associated carbonate formations in the studied area. ASTER data were also processed by the application of the Maximum Likelihood Classification (MLC), Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) image classification algorithms. The results were assessed by the production of a confusion matrix. The study shows the capability of visible near infrared (VNIR) and shortwave infrared (SWIR) spectral bands of the ASTER sensor and potential of the image processing methods to remotely identify industrial carbonate rocks and we recommend this technique to similar regions of the world.

【 授权许可】

Unknown