comparison of data and spectral driven methods for kaolinite-bearing area mapping in masahim volcano, using hyperion images

hyperion hyperspectral data contains a very rich source of information from the earth surface that collects 242 narrow contiguous spectral bands. achieving this source of rich information is subject to the performance of suitable image processing methods on raw satellite data. satellite image processing methods can be classified into two categories of statistical-based and spectral-based. in the statistical-based methods, processing principle is based on the distribution pattern of pixels’ dn values around mean, mode and median in dn value histogram of each band. however, in the spectral-based methods, the analysis is performed based on the spectral properties of the materials under question. in this study, we investigated both image processing methods and validated the results with field and laboratory data. field and laboratory studies included the investigation of field samples, laboratory spectroradiometry, xrd analysis and thin section studies of the rock samples. sam and pca image processing methods performed on hyperion images of the argillic zone in masahim volcanic crater as spectral and statistical-based methods, respectively. the mtmf method also was surveyed as a composite method in addition to the use of reference spectrum using statistical principles. confusion matrix prepared for the results of the three methods illustrated producer accuracy of 74.58% for sam, 25.42% for pca and 61% for mtmf results. therefore, use of spectral-based methods on hyperspectral image processing is considered as a suitable way for ground surface remote sensing studies using hyperspectral hyperion images.