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Detecting of Lithological Units by Using Terrestrial Spectral Data and Remote Sensing Image

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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 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.

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References

  • Abrams, M., & Hook, S. (1998). ASTER user handbook (1st ed.). Pasadena: NASA/Jet Propulsion Laboratory.

    Google Scholar 

  • Abdeen, M. M., Allison, T. K., Abdelsalam, M. G., & Stern, R. J. (2001). Application of ASTER band-ratio images for geological mapping in arid regions; the Neoproterozoic Allaqi Suture, Egypt. Geological Society of America Annual Meeting, Abstracts with Programs, Boston, USA, November 5-8, Abstract with Program Geological Society of America, 3, 289.

  • Başıbüyük, Z. (2006). Eosen Volkaniklerinin Hidrotermal Alterasyon Mineralojisi-Petrografisi ve Jeokimyası: Zara-İmranlı-Suşehri-Şerefiye Dörtgen’inden Bir Örnek (Sivas Kuzeydoğusu, İç-Doğu Anadolu, Türkiye). PhD, Cumhuriyet University, Sivas, Turkey.

  • Bedell, R. L. (2001). Geological mapping with ASTER satellite: new global satellite data that is a significant leap in remote sensing geologic and alteration mapping. Geological Society of Nevada, 33, 329–334.

    Google Scholar 

  • Blewitt, G. (1993). Advances in GPS technology for geodynamics invetigations: 1978-1992, contributions of space geodesy to geodynamics. Technology, 25, 195–213.

  • Bolongaro-Crevenna, A., Torres-Rodriguez, V., Sorani, V., Frame, D., & Ortiz, M. A. (2005). Geomorphometric analysis for characterizing landforms in Morelos State, Mexico. Geomorphology, 67, 407–422.

    Article  Google Scholar 

  • Cho, M. A., Mathieu, R., & Debba, P. (2009). Multıple endmember spectral-angle-mapper (SAM) analysis improves discrimination of Savanna tree species. Geoscience and Remote Sensing, 48, 4133–4142.

    Google Scholar 

  • De Carvalho, O. A., & Meneses, P. R. (2000). Spectral Correlation Mapper (SCM); An Improvement on the Spectral Angle Mapper (SAM). Summaries of the 9 th JPL Airborne Earth Science Workshop, JPL Publ. 00–18, p. 9.

  • Dickinson, K. J. M.,  Mark, A. F., & Dawkins, B. (1993). Ecology of lianoid/epiphytic communities in coastal podocarp rain forest, Haast Ecological District, New Zealand. Journal of Biogeography, 20(6), 687–705.

  • Gürsoy, Ö., Kaya, Ş., & Çakır, Z. (2013). Uydu Görüntüleri İle Yersel Spektral Ölçme Verilerinin Entegrasyonu. Huten, 6(1), 45–51.

    Google Scholar 

  • Iwasaki, A., & Tonooka, H. (2005). Validation of a crosstalk correction algorithm for ASTER/SIWR. IEEE Transactions on Geoscience and Remote Sensing, 43, 2747–2751.

    Article  Google Scholar 

  • Iwasaki, A., Fujisada, H., Akao, H., Shindou, O., & Akagi, S. (2001). Enhancement of spectral separation performance for ASTER/SWIR. Proceedings of SPIE The International Society for Optical Engineering, 4486, 42–50.

    Google Scholar 

  • Hewson, R. D., Cudahy, T. J., Mizuhiko, S., Ueda, K., & Mauger, A. J. (2005). Seamless geological map generation using ASTER in the Broken Hill-Curnamona province of Australia. Remote Sensing of Environment, 99, 159–172.

    Article  Google Scholar 

  • Kalinowski, A., Oliver, S. (2004). ASTER mineral index processing manual. Remote Sensing Applications. Geoscience Australia.

  • Kalkancı, Ş. (1974). Etüde geologique et petrochimique du sud de la region de Suşehri. Geochronologie du masif syenitique de Kösedağ (Sivas Turquie). PhD, L’universite de Grenoble, Paris, France.

  • Kaya, Ş. (2013). Analysis of an active fault geometry using satellite sensor and DEM data: Gaziköy-Saros Segment (NAFZ). International Journal of Geosciences, 4, 919–926.

    Article  Google Scholar 

  • Kaya, Ş., Müftüoğlu, O., & Tüysüz, O. (2004). Tracing the geometry of an active fault using remote sensing and digital elevation model: Ganos Segment, North Anatolian Fault Zone, Turkey. International Journal of Remote Sensing, 25, 3843–3855.

    Article  Google Scholar 

  • Kruse, F. A., & Perry, S. (2013). Mineral mapping using simulated worldview-3 short-wave-infrared imagery. Remote Sensing, 5, 2688–2703.

    Article  Google Scholar 

  • Kruse, F. A. (2011). Mapping surface mineralogy using imaging spectrometry. Geomorphology, 137, 41–56.

    Article  Google Scholar 

  • Kruse, F. A., & Hauff, P. L. (1992). Remote sensing clay mineral investigations for geologic applications using visible/near-infrared imaging spectroscopy. Science Geologiques, 89, 43–51.

    Google Scholar 

  • Kruse, F. A., Lefkoff, A. B., Boardman, J. B., & Heidebrecht, K. B. (1993). The Spectral Image Processing System (SIPS) - interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment, Special issue on AVIRIS, 44:145–163.

  • Massironi, M., Bertoldi, L., Calafa, P., Visonà, D., Bistacchi, A., Giardino, C., & Schiavo, A. (2008). Interpretation and processing of ASTER data for geological mapping and granitoids detection in the Saghro massif (eastern Anti-Atlas, Morocco). Geosphere, 4, 736–759.

    Article  Google Scholar 

  • McCubbin, I., Green, R., Lang, H., & Roberts, D. (1998). Mapping surface mineralogy using imaging spectrometry, Geomorphology. AZ. Summaries of the 8th JPL Airborne Earth Science Workshop. 1:269–272

  • Okada, K., & Ishii, M. (1993). Mineral and lithological mapping using thermal infrared remotely sensed data from ASTER simulator. International Geosciences and Remote Sensing Symposium Better Understanding of Earth Environment, 93, 126–128.

    Google Scholar 

  • Rowan, L. C., Mars, J. C., & Simpson, C. J. (2005). Lithologic mapping of the Mordor, NT, Australia ultramafic complex by using the advanced spaceborne thermal emission and reflection radiometer (ASTER). Remote Sensing of Environment, 99, 105–126.

    Article  Google Scholar 

  • Roberts, D. A., Yamaguchi, Y., & Lyon, R. J. P. (1985). Calibration of Airborne imaging spectrometer data to percent reflectance using field spectral measurements: in Proceedings, Nineteenth International Symposium on remote sensing of environment. Ann Arbor, Michigan. 21–25.

  • Salisbury, J. W., Walter, L. S., Vergo, N., & D’Aria, D. M. (1991). Infrared (2.1–25 micrometers) spectra of minerals. Johns Hopkins University Press. p. 294.

  • Sertel, E., Robock, A., & Örmeci, C. (2009). Impacts of land cover data quality on regional climate. International Journal of Clinical Oncology, 30, 2118–2128.

    Google Scholar 

  • Thome, K., Biggar, S., & Slater, P. (2001). Effects of assumed solar spectral irradiance on intercomparisons of earth-observing sensors. Proceedings of SPIE, 4540, 260–269.

    Article  Google Scholar 

  • Uysal, Ş., Bedi, Y., Kurt, İ., & Kılınç, F. (1995). Koyulhisar (Sivas) dolayının jeolojisi. MTA Rapor No: 9838, 120 s (Unpressed).

  • Van der Meer, F., Vasquez-Torres, M., & Van Dijk, P. M. (1997). Spectral characterization of ophiolite lithologies in the troodos ophiolite complex of cyprus and its potential in prospecting for massive sulphide deposits. International Journal of Remote Sensing, 18, 1245–1257.

    Article  Google Scholar 

  • Velosky, J. C., Stern, R. J., & Johnson, P. R. (2003). Geological control of massive sulfide mineralization in the Neoproterozoic Wadi Bidah shear zone, southwestern Saudi Arabia, inferences from orbital remote sensing and field studies. Precambrian Research, 123, 235–247.

    Article  Google Scholar 

  • Vicente, L. E., & Filho, C. R. S. (2011). Identification of mineral components in tropical soils using reflectance spectroscopy and advanced spaceborne thermal emission and reflection radiometer (ASTER) data. Remote Sensing of Environment, 115, 1824–1836.

    Article  Google Scholar 

  • Yılmaz, A., Okay, A., & Bilgiç, T. (1985). Yukarı Kelkit Çayı yöresi ve güneyinin temel jeoloji özellikleri ve sonuçları. MTA Rapor No: 7777, 124 s.

  • Yuhas, R. H., Goetz, A. F. H., & Boardman, J. W. (1992). Discrimination among semi-arid landscape endmembres using the spectral angle mapper (SAM) algorithm Summaries of the 3rd annu. JPL Airborne Geosci. Workshop, pp. 147–149

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Acknowledgments

We extend our gratitude to Assoc. Prof. Dr. Ziyadin Çakır, Assoc. Prof. Dr. Gursel SUNAL and Assoc. Prof. Dr. Gultekin TOPUZ for their efforts in thin sectioning and petrographic analysis of the rock samples used in this study. We also extend our gratitude CUBAP that provided the M-371 and M-523 numbered projects and data.

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Authors and Affiliations

  1. Department of Geomatics, Sivas Cumhuriyet University, Sivas, Turkey

    Önder Gürsoy

  2. Department of Geomatics, Istanbul Technical University, Istanbul, Turkey

    Şinasi Kaya

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  1. Önder Gürsoy
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  2. Şinasi Kaya
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Correspondence to Önder Gürsoy.

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Gürsoy, Ö., Kaya, Ş. Detecting of Lithological Units by Using Terrestrial Spectral Data and Remote Sensing Image. J Indian Soc Remote Sens 45, 259–269 (2017). https://doi.org/10.1007/s12524-016-0586-1

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  • DOI: https://doi.org/10.1007/s12524-016-0586-1

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