INTEGRATION OF SATELLITE IMAGERY AND SPECTRAL MEASUREMENTS
Goal-oriented classifications can be done with the integration of remote sensing images and spectral. Using classifications, surface rocks can be distinguished from each other. In this study, Gölova region, located in the Kelkit Valley along the North Anatolian Fault Zone (NAFZ), was selected as study area for applying this technique. Aiming to collect endmember on the ASTER SWIR images based on the lithological classification of geological units, the “Spectral Angle Mapper” (SAM) method was used. The method produces maps of the spectrally predominant mineral for each pixel by comparing the angle between the image spectra and reference spectra in n-dimensional vector space. And smaller angles represent closer matches to the reference spectrum. To increase the utility of the satellite images several processes were applied to remote sensing data respectively. These are crosstalk correction, radiance calibration and atmospheric correction. In 2010, a field study was done in the Gölova region and 17 rock samples were collected from 17 different locations. Coordinates of each spectral sample point were recorded with a hand GPS (Global Positioning System). At SAM analysis, two kinds of NTRS that were numbered “b4” assigned marble and “b6” assigned metalava were collected on the ASTER SWIR images. As a result of SAM, marble and metalava rocks were detected in Gölova Region (Alan-10) at the same coordinates of the samples. Then the SAM result was compared with the geological map of the region. Consequently, marble was proved in the geological map about the coordinates of “b4.
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