Application of remote sensing in mapping hydrothermally altered zones in a highly vegetative area - A case study of Lolgorien, Narok County, Kenya

Sammy O Ombiro; Akinade S Olatunji; Eliud M Mathu; Taiwo R Ajayi

doi:10.17485/IJST/v14i9.68

Article

Application of remote sensing in mapping hydrothermally altered zones in a highly vegetative area - A case study of Lolgorien, Narok County, Kenya

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v14i9.68

Year: 2021, Volume: 14, Issue: 9, Pages: 810-825

Original Article

Application of remote sensing in mapping hydrothermally altered zones in a highly vegetative area - A case study of Lolgorien, Narok County, Kenya

Sammy O Ombiro^1*, Akinade S Olatunji², Eliud M Mathu³, Taiwo R Ajayi²

¹Pan African University, Life and Earth Sciences Institute, University of Ibadan, Nigeria
²Department of Geology, University of Ibadan, Nigeria
³Department of Geology and Meteorology, South Eastern Kenya University, Kenya

*Corresponding Author
Email: [email protected]

Received Date:13 January 2021, Accepted Date:28 February 2021, Published Date:23 March 2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objective: To map areas of possible hydrothermal alteration using remote sensing technology; To map geological structures controlling mineralisation using remote sensing; To carryout field mapping to ground truth the features identified by remote sensed data. Methods: Landsat 8 Operational Land Imager (OLI) and Shuttle Radar Topography Mission (SRTM) remote sensed images were downloaded from USGS website. Landsat images were processed using band ratios, band composites, principal component analysis techniques in ArcGIS to map areas of possible hydrothermal alteration. SRTM image was analysed using hillshade analysis technique in ArcGIS to map geological structural features controlling mineralisation. Findings: The study found that in several areas especially Southern, South Eastern, Central and North Western part of Lolgorien, there is a possibility of hydrothermal alteration as spectral signatures associated with iron oxide and clay minerals were identified. It was also found that areas with possibility of hydrothermal alteration are also associated with relatively large number of lineaments. It was also found that Southern and South-Eastern part of Lolgorien are also associated with numerous artisanal mines proving the fact that indeed gold mineralisation may be found in these places. However, due to thick vegetation cover, mapping of different types of lithological units found in Lolgorien was not possible. Novelty/Application: The application of remote sensed technology helped in identification of new areas of possible mineralisation such as Central and North-Western parts of Lolgorien which despite having similar geological properties (in terms of lineament density and hydrothermal alteration) have never been exploited for gold or other minerals.

Keywords: Hydrothermal alteration; Landsat 8 (OLI); SRTM; Iron oxide; clay minerals; remote sensing

References

Kotnise G, Chennabasappa S. Application of remote sensing techniques in identification of lithological rock units in southern extension of Kolar Schist Belt from Chigargunta. International Journal of Innovative Science, Engineering & Technology. 2015;2(11).
Drews-Armitage SP, Romberger SB, Whitney CG. Clay alteration and gold deposition in the Genesis and Blue Star deposits, Eureka County, Nevada. Economic Geology. 1996;91(8):1383–1393. Available from: https://dx.doi.org/10.2113/gsecongeo.91.8.1383
Mahboob MA, Genc B, Celik T, Ali S, Atif I. Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data from Landsat. Journal of the Southern African Institute of Mining and Metallurgy. 2019;119(3):249–89. Available from: https://dx.doi.org/10.17159/2411-9717/2019/v119n3a7
Amara BN, Aissa DE, Maouche S, Braham M, Machane D, Guessoum N. Hydrothermal alteration mapping and structural features in the Guelma basin (Northeastern Algeria): contribution of Landsat-8 data. Arabian Journal of Geosciences. 2019;12(3):94. Available from: https://dx.doi.org/10.1007/s12517-019-4224-4
Eldosouky AM, Abdelkareem M, Elkhateeb SO. Integration of remote sensing and aeromagnetic data for mapping structural features and hydrothermal alteration zones in Wadi Allaqi area, South Eastern Desert of Egypt. Journal of African Earth Sciences. 2017;130:28–37. Available from: https://dx.doi.org/10.1016/j.jafrearsci.2017.03.006
Pour AB, Hashim M. Hydrothermal alteration mapping from Landsat-8 data, Sar Cheshmeh copper mining district, south-eastern Islamic Republic of Iran. Journal of Taibah University for Science. 2015;9(2):155–166. Available from: https://doi.org/10.1016/j.jafrearsci.2017.03.006
Liu L, Li Y, Zhou J, Han L, Xu X. Gold-copper deposits in Wushitala, Southern Tianshan, Northwest China: Application of ASTER data for mineral exploration. Geological Journal. 2018;53:362–371. Available from: https://doi.org/10.1002/gj.2989
Durand J. The impact of gold mining on the Witwatersrand on the rivers and karst system of Gauteng and North West Province, South Africa. Journal of African Earth Sciences. 2012;68:24–43. Available from: https://doi.org/10.1016/j.jafrearsci.2012.03.013
Sutton MW. Use of remote sensing and GIS in a risk assessment of gold and uranium mine residue deposits and identification of vulnerable land use . 2013.
Sutton M, Weiersbye I, Galpin J, Heller D, Fourie A, Tibbett M. A GIS-based history of gold mine residue deposits and risk assessment of post-mining land uses on the Witwatersrand Basin, South Africa. In: Mine Closure 2006. (pp. 667-678) 2006.
Pour AB, Sekandari M, Rahmani O, Crispini L, Läufer A, Park Y, et al. Identification of Phyllosilicates in the Antarctic Environment Using ASTER Satellite Data: Case Study from the Mesa Range, Campbell and Priestley Glaciers, Northern Victoria Land. Remote Sensing. 2020;13(1). Available from: https://dx.doi.org/10.3390/rs13010038
Pour AB, Park Y, Crispini L, Läufer A, Hong JK, Park TYS, et al. Mapping Listvenite Occurrences in the Damage Zones of Northern Victoria Land, Antarctica Using ASTER Satellite Remote Sensing Data. Remote Sensing. 2019;11(12). Available from: https://dx.doi.org/10.3390/rs11121408
Sekandari M, Masoumi I, Pour AB, Muslim AM, Rahmani O, Hashim M, et al. Application of Landsat-8, Sentinel-2, ASTER and WorldView-3 Spectral Imagery for Exploration of Carbonate-Hosted Pb-Zn Deposits in the Central Iranian Terrane (CIT) Remote Sensing. 2020;12:1239. Available from: https://dx.doi.org/10.3390/rs12081239
Bolouki SM, Ramazi HR, Maghsoudi A, Pour AB, Sohrabi G. A Remote Sensing-Based Application of Bayesian Networks for Epithermal Gold Potential Mapping in Ahar-Arasbaran Area, NW Iran. Remote Sensing. 2019;12. Available from: https://dx.doi.org/10.3390/rs12010105
Pour, Park, Park, Hong, Muslim, Läufer, et al. Landsat-8, Advanced Spaceborne Thermal Emission and Reflection Radiometer, and WorldView-3 Multispectral Satellite Imagery for Prospecting Copper-Gold Mineralization in the Northeastern Inglefield Mobile Belt (IMB), Northwest Greenland. Remote Sensing. 2019;11(20). Available from: https://dx.doi.org/10.3390/rs11202430
Zoheir B, El-Wahed MA, Pour AB, Abdelnasser A. Orogenic Gold in Transpression and Transtension Zones: Field and Remote Sensing Studies of the Barramiya–Mueilha Sector, Egypt. Remote Sensing. 2019;11(18):2122. Available from: https://dx.doi.org/10.3390/rs11182122
Zoheir B, Emam A, Abdel-Wahed M, Soliman N. Multispectral and Radar Data for the Setting of Gold Mineralization in the South Eastern Desert, Egypt. Remote Sensing. 2019;11(12). Available from: https://dx.doi.org/10.3390/rs11121450
Ichang’i D, Maclean W. The Archean volcanic facies in the Migori segment. J Afr Earth Sci. 1991;13(3/4):277–290.
Shackleton R. Geology of the Migori gold belt. Geol Surv Kenya. 1946;10.
Akech NO, Omuombo CA, Masibo M. General geology of Kenya. Developments in Earth Surface Processes. Elsevier. 2013. Available from: https://doi.org/10.1016/B978-0-444-59559-1.00001-3
Rmdc F. Mapping hydrothermal gold mineralization using Landsat 8 data. A case of study in Chaves license, Portugal. Portugal: Departamento de Geociências, Ambiente e Ordenamento do Território. 2015.
Mwaniki MW, Moeller MS, Schellmann G. A comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in mapping geology and visualising lineaments: A case study of central region Kenya. In: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. (Vol. XL-7/W3, pp. 897-903) Copernicus GmbH. 2015. 10.5194/isprsarchives-xl-7-w3-897-2015
Han T, Nelson J. Mapping hydrothermally altered rocks with Landsat 8 imagery : A case study in the KSM and Snow field zones , northwestern British Columbia. In: Geological Fieldwork 2014, British Columbia Ministry of Energy and Mines, British Columbia Geological Survey Paper. (Vol. 2015, pp. 103-112) 2015.
Goetz A. Three decades of hyperspectral remote sensing of the Earth: A personal view. Remote Sensing of Environment. 2009;113:5–16. Available from: https://doi.org/10.1016/j.rse.2007.12.014
Carranza EJM, Hale M. Mineral imaging with Landsat Thematic Mapper data for hydrothermal alteration mapping in heavily vegetated terrane. International Journal of Remote Sensing. 2002;23:4827–4852. Available from: https://dx.doi.org/10.1080/01431160110115014
Ali A, Pour A. Lithological mapping and hydrothermal alteration using Landsat 8 data: a case study in ariab mining district, red sea hills, Sudan. International Journal of Basic and Applied Sciences. 2014;3(3). Available from: https://dx.doi.org/10.14419/ijbas.v3i3.2821
Burton-Johnson A, Black M, Fretwell PT, Kaluza-Gilbert J. An automated methodology for differentiating rock from snow, clouds and seain Antarctica from Landsat 8 imagery: a new rock outcrop map and areaestimation for the entire Antarctic continent. The Cryosphere. 2016;10(4):1665–1677. Available from: https://dx.doi.org/10.5194/tc-10-1665-2016
Banerjee K, Jain MK, Jeyaseelan AT, Panda S. Landsat 8 OLI Data for Identification of Hydrothermal Alteration Zone in Singhbhum Shear Zone using Successive Band Depth Difference Technique–A New Image Processing Approach. Current Science. 2019;116(10). Available from: https://dx.doi.org/10.18520/cs/v116/i10/1639-1647

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© 2021 Ombiro et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)