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Towards an Improved Approach of Clay Minerals Mapping in the Northwestern Region of Algeria.

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Title: Towards an Improved Approach of Clay Minerals Mapping in the Northwestern Region of Algeria.
Authors: Mehalli, Zoulikha1 (AUTHOR) zoulikha.mehalli@univ-usto.dz, Zigh, Ehlem1 (AUTHOR) ehlem.zigh@univ-usto.dz, Loukil, A.2 (AUTHOR) abdelhamid.loukil@univ-usto.dz, Ali Pacha, A.1 (AUTHOR) adda.alipacha@univ-usto.dz
Source: Journal of Applied Engineering Sciences. Dec2024, Vol. 14 Issue 2, p292-299. 8p.
Subjects: Image recognition (Computer vision), Classification of books, Kaolinite, Montmorillonite, Illite
Abstract: The availability of hyperspectral images has significantly facilitated clay minerals identification and mapping. Based on the Hyperion L1R hyperspectral dataset, this research aims to improve previous scientific work related to identifying and mapping clay minerals in the Djebel Meni region (northwestern of Algeria). Firstly, we enhance the dataset quality through pre-processing techniques like the removal of bad bands, radiometric calibration, and atmospheric correction. Secondly, the Spectral Information Divergence (SID) algorithm was employed by introducing endmembers derived with the Sequential Maximum Angle Convex Cone (SMACC) algorithm initially and then using Jet Propulsion Laboratory (JPL) spectral signatures of Illite, Kaolinite, and Montmorillonite. The classification results show a correspondence between areas occupied by endmembers and JPL spectral signatures, which helps in matching endmembers with specific minerals. Finally, we conducted a comparative analysis of the two classifications outcomes against a reference map. This last is generated using SID algorithm, which takes ground truth spectral signatures as input. Our proposed approach using the SID classifier has given an overall accuracy score of 97.13% and 84.17% using endmembers image and JPL library respectively. The Kappa coefficient is respectively, with endmembers image and JPL, 0.93 and 0.57. These results show that the SID classification with the endmembers image is better than the SID classification with the JPL library because extracting the endmembers from the image is more accurate than doing that from the pure minerals analyzed in the laboratory. These promising results suggest that our approach could be extended to the identification of clay minerals in diverse hyperspectral datasets. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Engineering Sciences is the property of Paradigm Publishing Services and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Towards an Improved Approach of Clay Minerals Mapping in the Northwestern Region of Algeria.
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  Data: <searchLink fieldCode="AR" term="%22Mehalli%2C+Zoulikha%22">Mehalli, Zoulikha</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zoulikha.mehalli@univ-usto.dz</i><br /><searchLink fieldCode="AR" term="%22Zigh%2C+Ehlem%22">Zigh, Ehlem</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ehlem.zigh@univ-usto.dz</i><br /><searchLink fieldCode="AR" term="%22Loukil%2C+A%2E%22">Loukil, A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> abdelhamid.loukil@univ-usto.dz</i><br /><searchLink fieldCode="AR" term="%22Ali+Pacha%2C+A%2E%22">Ali Pacha, A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> adda.alipacha@univ-usto.dz</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Engineering+Sciences%22">Journal of Applied Engineering Sciences</searchLink>. Dec2024, Vol. 14 Issue 2, p292-299. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Image+recognition+%28Computer+vision%29%22">Image recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Classification+of+books%22">Classification of books</searchLink><br /><searchLink fieldCode="DE" term="%22Kaolinite%22">Kaolinite</searchLink><br /><searchLink fieldCode="DE" term="%22Montmorillonite%22">Montmorillonite</searchLink><br /><searchLink fieldCode="DE" term="%22Illite%22">Illite</searchLink>
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  Data: The availability of hyperspectral images has significantly facilitated clay minerals identification and mapping. Based on the Hyperion L1R hyperspectral dataset, this research aims to improve previous scientific work related to identifying and mapping clay minerals in the Djebel Meni region (northwestern of Algeria). Firstly, we enhance the dataset quality through pre-processing techniques like the removal of bad bands, radiometric calibration, and atmospheric correction. Secondly, the Spectral Information Divergence (SID) algorithm was employed by introducing endmembers derived with the Sequential Maximum Angle Convex Cone (SMACC) algorithm initially and then using Jet Propulsion Laboratory (JPL) spectral signatures of Illite, Kaolinite, and Montmorillonite. The classification results show a correspondence between areas occupied by endmembers and JPL spectral signatures, which helps in matching endmembers with specific minerals. Finally, we conducted a comparative analysis of the two classifications outcomes against a reference map. This last is generated using SID algorithm, which takes ground truth spectral signatures as input. Our proposed approach using the SID classifier has given an overall accuracy score of 97.13% and 84.17% using endmembers image and JPL library respectively. The Kappa coefficient is respectively, with endmembers image and JPL, 0.93 and 0.57. These results show that the SID classification with the endmembers image is better than the SID classification with the JPL library because extracting the endmembers from the image is more accurate than doing that from the pure minerals analyzed in the laboratory. These promising results suggest that our approach could be extended to the identification of clay minerals in diverse hyperspectral datasets. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Applied Engineering Sciences is the property of Paradigm Publishing Services and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.2478/jaes-2024-0036
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        Text: English
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      – SubjectFull: Kaolinite
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      – SubjectFull: Montmorillonite
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      – TitleFull: Towards an Improved Approach of Clay Minerals Mapping in the Northwestern Region of Algeria.
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            NameFull: Mehalli, Zoulikha
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            NameFull: Zigh, Ehlem
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              Text: Dec2024
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