Detecting of Lithological Units by Using Terrestrial Spectral Data and Remote Sensing Image
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RESEARCH ARTICLE
Detecting of Lithological Units by Using Terrestrial Spectral Data and Remote Sensing Image Önder Gürsoy 1 & Şinasi Kaya 2
Received: 17 April 2015 / Accepted: 15 April 2016 # Indian Society of Remote Sensing 2016
Abstract The objective of the study was to carry out an automatic classification of the lithological units of interest using the integration of remote sensing image, in which various objects are spread on, and terrestrial spectral measurement data. Only endmembers of interest are classified using spectral classification methods such as Spectral Angle Mapper. Following the identification of the types of rock and minerals, integration of remote sensing images and spectral measurement data enable spectral classification. In this study, Short Wave Infrared detector images of Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite and spectroradiometer measurements were used. The study area, Gölova with its geological diversity is located in the Kelkit Valley section of the North Anatolian Fault Zone in Northeast of Turkey. Seventeen rock samples were collected and their coordinates were recorded. The samples were categorized via spectral measurements on their thin sections through petrographic analyses. Marble and Meta lava with different lithological were selected as endmembers. SAM was used as the classification method that enables the analysis of the endmember with the threshold value of 0.009 radian for marble and 0.010 radian for metalava. SAM analysis was compared by visual analysis to principle component analysis, decorrelation stretch, band ratio (R: 4/7, G: 4/1, B (2/3) x (4/3)) and band combination analysis (R: 9, G: 4 and B: 5). This study demonstrates that the SAM method can be successfully used in both the integration of remote sensing image
* Önder Gürsoy [email protected]
1
Department of Geomatics, Sivas Cumhuriyet University, Sivas, Turkey
2
Department of Geomatics, Istanbul Technical University, Istanbul, Turkey
and terrestrial spectral measurement data in lithological classification. Both the endmembers of metalava and marbles were detected in the SAM results at the GPS coordinates noted down whilst collecting the rock samples for accuracy assessment. Keywords ASTER . Lithological mapping . Spectral measurement
Introduction Remote sensing technology has been rapidly improving in geology thanks to its widely developing sensors. All objects that can be identified via remote sensing sensors have unique spectral signatures. Molecular vibrational features between wavelengths of ~1.0 and 2.5 μm are observed in the SWIR region. Mineral absorption features can be detected easily in the SWIR by gathering these unique spectral signatures. Definitions of landforms are usually based on the basis of homogeneous terrain characteristics and result from the actions of common geological processes over time (Bolongaro-Crevenna et al. 2005; Kruse 2011; Kruse and Perry 2013). Key spectral features of minerals, vegetation, man-made materials, snow and ice, water
