Lithological Mapping in the Eastern Part of the Central Iranian Volcanic Belt Using Combined ASTER and IRS data
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RESEARCH ARTICLE
Lithological Mapping in the Eastern Part of the Central Iranian Volcanic Belt Using Combined ASTER and IRS data Seyed Mohammad Hadi Hadigheh & Hojjatollah Ranjbar
Received: 25 September 2012 / Accepted: 22 April 2013 # Indian Society of Remote Sensing 2013
Abstract The study area is located in the eastern part of the central Iranian volcanic belt. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Indian Remote Sensing Satellite (IRS ) pan images were used for applying several image classification methods for lithological mapping. ASTER visible-near infrared and shortwave infrared bands were sharpened using IRS pan image. We used classification methods such as Maximum likelihood, Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) in order to evaluate the usefulness of these methods for geological mapping. The classification results showed that MLC has the best accuracy and the classified image closely resembles the previously prepared geology map of the area. Keywords Indian remote sensing satellite . ASTER . Supervised classification . Accuracy assessment
S. M. H. Hadigheh (*) Kusha-Maadan Consulting Engineering Company, Palestine Ave, Shiraz, Iran e-mail: [email protected] H. Ranjbar Department of Mining Engineering, Shahid Bahonar, University of Kerman, Kerman, Iran e-mail: [email protected]
Introduction New sensors and technologies for data processing in remote sensing are providing capabilities for mapping and monitoring the geological features as never before. Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER), provides a pyramid structure of resolution from 15 m (usually in the visible bands) to 90 m or more (usually in the thermal bands). Although these images are spectrally of higher resolution, but in cases where intending mapping a medium or large scale, the spatial resolution is not satisfactory. The spatial resolution can be improved using an image with a higher resolution. From another point of view, the remote sensing community is now experiencing an automation of remote sensing analysis, providing intelligent, quick response, and highprecision results, including data classification and event alarms (Ninomiya et al. 2005). In this paper, classification of ASTER data that was sharpened with IRS data, is investigated. The main goal of this study is to compare the different methods of image classification in order to determine the efficiency of different classification methods in lithological mapping. The Study Area is located in the southeast of South Khorasan Province in Iran (Fig. 1). This study area has an approximately 215 km2 that lies in 1:250000 scale geological sheet of Chah-Vak (Geological survey of Iran 1993). Given the poor vegetation cover and plenty of rock exposures, the area is suitable for applying remote sensing data for geological studies.
J Indian Soc Remote Sens
Fig. 1 Location map of the study area
The Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) sensor obtains mu
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