首页 | 本学科首页   官方微博 | 高级检索  
     


Spectral characterization and ASTER-based lithological mapping of an ophiolite complex: A case study from Neyriz ophiolite, SW Iran
Authors:Majid H. Tangestani  Laleh Jaffari  B.B. Maruthi Sridhar
Affiliation:
  • a Department of Earth Sciences, Faculty of Sciences, Shiraz University, Shiraz, Iran
  • b Remote Sensing and GIS Center of Shiraz University, Shiraz, Iran
  • c Department of Geology, Bowling Green University, USA
  • Abstract:The Neyriz ophiolite occurs along the Zagros suture zone in SW Iran, and is part of a 3000-km obduction belt thrusting over the edge of the Arabian continent during the late Cretaceous. This complex typically consists of altered dunites and peridotites, layered and massive gabbros, sheeted dykes and pillow lavas, and a thick sequence of radiolarites. Reflectance and emittance spectra of Neyriz ophiolite rock samples were measured in the laboratory and their spectra were used as endmembers in a spectral feature fitting (SFF) algorithm. Laboratory spectral reflectance measurements of field samples showed that in the visible through shortwave infrared (VNIR-SWIR) wavelength region the ultramafic and gabbroic rocks are characterized by ferrous-iron and Fe, Mgsingle bondOH spectral features, and the pillow lavas and radiolarites are characterized by spectral features of ferric-iron and Alsingle bondOH. The laboratory spectral emittance spectra also revealed a wide wavelength range of Sisingle bondO spectral features for the ophiolite rock units. After continuum removal of the spectra, the SFF classification method was applied to the VNIR + SWIR 9-band stack, and to the 11-band data set of SWIR and TIR data sets of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor, using field spectra as training sets for evaluating the potential of these data sets in discriminating ophiolite rock units. Output results were compared with the geological map of the area and field observations, and were assessed by the use of confusion matrices. The assessment showed, in terms of kappa coefficient, that the SFF classification method with continuum removal applied to the SWIR data achieved excellent results, which were distinctively better than those obtained using VNIR + SWIR data and TIR data alone.
    Keywords:Ophiolite   ASTER   Iran   Spectral feature fitting   Spectral feature
    本文献已被 ScienceDirect 等数据库收录!
    设为首页 | 免责声明 | 关于勤云 | 加入收藏

    Copyright©北京勤云科技发展有限公司  京ICP备09084417号