Published

2024-02-28

Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model

Levantamiento de mapas de alteraciones hidrotermales y lineamientos asociados al interior de Kaiama, norte central de Nigeria, con información del satélite Landsat 8 Operational Land Imager y Modelos Digitales de Elevación

DOI:

https://doi.org/10.15446/esrj.v27n4.107002

Keywords:

Band Ratio, Principal Component Analysis, False Colour Composite, Landsat 8 OLI, Kaiama (en)
Reducción de Bandas, Análisis de Componentes Principales, Falso Color Compuesto, Landsat 8 OLI, Kaiama (es)

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Authors

  • Aliyu Umaru Pan African University of Life and Earth Sciences (including health and agriculture)
  • Olugbenga Okunlola University of Ibadan
  • Umaru Adamu Danbatta Ahmadu Bello University
  • Olisa Olusegun G. Olabisi Onabanjo University

This research focuses on the geological investigation of Kaiama region, which is characterized by a diverse range of rock formations, including mylonites, porphyritic granites, gneiss, schist, phyllites, and pink granites. The study employs remote sensing techniques, utilizing Landsat 8 OLI data and Digital Elevation Models, to systematically map the spatial distribution of hydrothermal alterations and tectonic structures associated with mineralization in the Kaiama area. Various image processing methods such as Color Composites, Band Rationing, and Principal Component Analysis (PCA) were employed to extract valuable information from the collected datasets. Utilizing Sabins band ratios (4/2, 6/7, and 6/5), we categorized alterations associated with iron oxides, clay minerals, and ferrous minerals. PCA was applied to refine the identification of alteration zones, using two distinct sets of images: H-image (comprising bands 2, 4, 5, and 7) and F-image (comprising bands 2, 5, 6, and 7), which represented iron-oxide and hydroxyl mineral deposits, respectively. The synthesis of H, F, and H+F images in RGB format provided an optimal representation of the spatial distribution of hydrothermal alterations, exhibiting a strong positive correlation with known mining regions for gold, copper, wolframite, and tantalite within the study area. Furthermore, a comprehensive analysis of regional lineaments revealed a consistent NNE-SSW to NE-SW correlation, suggesting a predominant control on mineralization trends. This study advocates for adopting remote sensing techniques, specifically Landsat 8 data and DEM, as an effective approach for mapping hydrothermal alterations and identifying key structural controls associated with mineralization. 

 

Este trabajo se enfoca en la investigación geológica de la región de Kaiama, la cual se caracteriza por un rango diverso de formaciones rocosas que incluyen milonitas, granitos porfiríticos, gneises, esquistos, filitas y granitos rosa. El trabajo emplea técnicas de teledetección, con información del satélite Landsat 8 OLI y Modelos Digitales de Elevación, para levantar un mapa de la distribución espacial de las alteraciones hidrotermales y las estructuras tectónicas asociadas con la mineralización del área de Kaiama. Se emplearon varios métodos de procesamiento de imágenes como Falso Color Compuesto, Reducción de Bandas, y Análisis de Componentes Principales para determinar la información importante del conjunto de datos recolectados. Los autores utilizaron los ratios de la banda de Sabins (4/2, 6/7, y 6/5) para categorizar las alteraciones asociadas con los óxidos de hierro, los minerales arcillosos y los minerales ferrosos. El Análisis de Componentes Principales se aplicó para refinar la identificación de las zonas de alteración a través de dos configuraciones de imágenes: Imagen H (que comprende las bandas 2, 4, 5 y 7) e Imagen F (que comprende las bandas 2, 5, 6 y 7), los cuales representan los depósitos de óxidos de hierro y de minerales hidróxidos. La combinación de las imágenes H, F, y H+F en el formato RGB proveyó una representación óptima de la distribución espacial de las alteraciones hidrotermales y mostró una fuerte correlación positiva con regiones mineras caracterizadas de oro, cobre, wolframita y tantalita en el área de estudio. Además, un análisis extenso de los lineamientos regionales revelaron una correlación consistente NNE-SSO hacia NE-SO, lo que sugiere un control predominante en las tendencias de mineralización. Este estudio propone la adopción de técnicas de teledetección, especificamente el uso de información del satélite Landsat 8 y Modelos Digitales de Elevación, como un acercamiento efectivo para levantar mapas de alteraciones hidrotermales e identificar las claves de control estructurales asociadas con la mineralización. 

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How to Cite

APA

Umaru, A., Okunlola, O., Adamu Danbatta, U. and Olusegun G., O. (2024). Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model. Earth Sciences Research Journal, 27(4), 367–379. https://doi.org/10.15446/esrj.v27n4.107002

ACM

[1]
Umaru, A., Okunlola, O., Adamu Danbatta, U. and Olusegun G., O. 2024. Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model. Earth Sciences Research Journal. 27, 4 (Feb. 2024), 367–379. DOI:https://doi.org/10.15446/esrj.v27n4.107002.

ACS

(1)
Umaru, A.; Okunlola, O.; Adamu Danbatta, U.; Olusegun G., O. Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model. Earth sci. res. j. 2024, 27, 367-379.

ABNT

UMARU, A.; OKUNLOLA, O.; ADAMU DANBATTA, U.; OLUSEGUN G., O. Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model. Earth Sciences Research Journal, [S. l.], v. 27, n. 4, p. 367–379, 2024. DOI: 10.15446/esrj.v27n4.107002. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/107002. Acesso em: 25 apr. 2025.

Chicago

Umaru, Aliyu, Olugbenga Okunlola, Umaru Adamu Danbatta, and Olisa Olusegun G. 2024. “Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model”. Earth Sciences Research Journal 27 (4):367-79. https://doi.org/10.15446/esrj.v27n4.107002.

Harvard

Umaru, A., Okunlola, O., Adamu Danbatta, U. and Olusegun G., O. (2024) “Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model”, Earth Sciences Research Journal, 27(4), pp. 367–379. doi: 10.15446/esrj.v27n4.107002.

IEEE

[1]
A. Umaru, O. Okunlola, U. Adamu Danbatta, and O. Olusegun G., “Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model”, Earth sci. res. j., vol. 27, no. 4, pp. 367–379, Feb. 2024.

MLA

Umaru, A., O. Okunlola, U. Adamu Danbatta, and O. Olusegun G. “Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model”. Earth Sciences Research Journal, vol. 27, no. 4, Feb. 2024, pp. 367-79, doi:10.15446/esrj.v27n4.107002.

Turabian

Umaru, Aliyu, Olugbenga Okunlola, Umaru Adamu Danbatta, and Olisa Olusegun G. “Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model”. Earth Sciences Research Journal 27, no. 4 (February 28, 2024): 367–379. Accessed April 25, 2025. https://revistas.unal.edu.co/index.php/esrj/article/view/107002.

Vancouver

1.
Umaru A, Okunlola O, Adamu Danbatta U, Olusegun G. O. Mapping hydrothermal alterations and associated lineaments within Kaiama, north-central Nigeria, using Landsat 8 Operational Land Imager Data and Digital Elevation Model. Earth sci. res. j. [Internet]. 2024 Feb. 28 [cited 2025 Apr. 25];27(4):367-79. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/107002

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