Abstract

 

The Advanced space-borne thermal emission and reflection radiometer (ASTER) remote sensing data has suitable spectral and spatial properties for detailed lithological mapping. ASTER data is highly effective for lithological mapping in arid and semi-arid regions where geologic structures are extensively exposed. This study has applied spectral transform approaches, consisting of principal component analysis (PCA), band ratio (BR) and minimum noise fraction (MNF) for lithological mapping. As a case study, Abdashtophiolite rock complex located in south eastern Iran has been chosen for applying the image processing techniques to ASTER level 1B data. Prior to image processing, the ASTER data were also subjected to image pre-processing. The results show that PCA images identified the ophiolitic rocks consisting ofamphibolites, undifferentiated pridotite, color melange including ophiolitic component, volcanic rocks, radiolarian cherts, and plagic limestone associated with Eocene sedimentary rocks. ASTER BRs (2+4)/3, (5+7)/6, (7+9)/8) were found best in discriminating the ophiolitic rock units. The MNF transformed data detected rock units more recognizable than PCA and BR techniques.

 

 

 

 

 

 

 

 

 

 

Key words: Advanced space-borne thermal emission and reflection radiometer (ASTER), lithological mapping, ophiolite complex.

Abbreviation

ASTER, Advanced space-borne thermal emission and reflection radiometer; EOS AM-1, earth observing system AM-1; VNIR, visible and near infrared radiation; SWIR, shortwave infrared radiation; TIR, thermal infrared radiation; PCA, principal component analysis; BR, band ratio; MNF, minimum noise fraction; ERSDAC, earth and remote sensing data analysis centre; DN, digital number.