Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods
Lithological mapping using satellite images, particularly the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data help in effectively defining the best initial targets for regional exploration. ASTER data allow for the discrimination of rock units in the broader region. This...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-01-01
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| Series: | Geology, Ecology, and Landscapes |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/24749508.2019.1585657 |
| _version_ | 1818996591160197120 |
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| author | Ali Rezaei Hossein Hassani Parviz Moarefvand Abbas Golmohammadi |
| author_facet | Ali Rezaei Hossein Hassani Parviz Moarefvand Abbas Golmohammadi |
| author_sort | Ali Rezaei |
| collection | DOAJ |
| description | Lithological mapping using satellite images, particularly the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data help in effectively defining the best initial targets for regional exploration. ASTER data allow for the discrimination of rock units in the broader region. This research work is focused on the use of remote sensing techniques for geological mapping using ASTER satellite image and generating a geological map of Sangan region. The study area is located in southeast of Khorasan-e-Razavi province and at the eastern edge of the Khaf-Kashmar-Bardskan Volcano-Plutonic Metallogenic Belt in northeast Iran. Band ratio (BR), spectral angle mapper (SAM) and support vector machines (SVMs) methods were used for classifying the main lithologic units in Sangan region. The results of BR, SAM and SVM techniques were quantitatively compared with geological boundaries mapped in the field showing an accuracy of nearly 79 %. SVMs method, in comparison to conventional methods of classification, was known to provide superior results. As the final result of this research, integration of remote sensing and field investigations led to generating high accuracy geological map in the Sangan region. Application of the methods has invaluable implications for geological mapping and mineral exploration in inaccessible regions. |
| first_indexed | 2024-12-20T21:32:10Z |
| format | Article |
| id | doaj.art-44ca05347d5d40d5a230da529c71c804 |
| institution | Directory Open Access Journal |
| issn | 2474-9508 |
| language | English |
| last_indexed | 2024-12-20T21:32:10Z |
| publishDate | 2020-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geology, Ecology, and Landscapes |
| spelling | doaj.art-44ca05347d5d40d5a230da529c71c8042022-12-21T19:26:01ZengTaylor & Francis GroupGeology, Ecology, and Landscapes2474-95082020-01-0141597010.1080/24749508.2019.15856571585657Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methodsAli Rezaei0Hossein Hassani1Parviz Moarefvand2Abbas Golmohammadi3Amirkabir University of TechnologyAmirkabir University of TechnologyAmirkabir University of TechnologyGeological Survey and Mineral Exploration of IranLithological mapping using satellite images, particularly the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data help in effectively defining the best initial targets for regional exploration. ASTER data allow for the discrimination of rock units in the broader region. This research work is focused on the use of remote sensing techniques for geological mapping using ASTER satellite image and generating a geological map of Sangan region. The study area is located in southeast of Khorasan-e-Razavi province and at the eastern edge of the Khaf-Kashmar-Bardskan Volcano-Plutonic Metallogenic Belt in northeast Iran. Band ratio (BR), spectral angle mapper (SAM) and support vector machines (SVMs) methods were used for classifying the main lithologic units in Sangan region. The results of BR, SAM and SVM techniques were quantitatively compared with geological boundaries mapped in the field showing an accuracy of nearly 79 %. SVMs method, in comparison to conventional methods of classification, was known to provide superior results. As the final result of this research, integration of remote sensing and field investigations led to generating high accuracy geological map in the Sangan region. Application of the methods has invaluable implications for geological mapping and mineral exploration in inaccessible regions.http://dx.doi.org/10.1080/24749508.2019.1585657lithological mappingasterband ratiospectral angle mappersupport vector machinesangan |
| spellingShingle | Ali Rezaei Hossein Hassani Parviz Moarefvand Abbas Golmohammadi Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods Geology, Ecology, and Landscapes lithological mapping aster band ratio spectral angle mapper support vector machine sangan |
| title | Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods |
| title_full | Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods |
| title_fullStr | Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods |
| title_full_unstemmed | Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods |
| title_short | Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods |
| title_sort | lithological mapping in sangan region in northeast iran using aster satellite data and image processing methods |
| topic | lithological mapping aster band ratio spectral angle mapper support vector machine sangan |
| url | http://dx.doi.org/10.1080/24749508.2019.1585657 |
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