Geological Mapping for Gold Exploration in Butihinda Muyinga Area, Northeastern Burundi using Remote Sensing and GIS

International Journal of Geoinformatics and Geological Science
© 2025 by SSRG - IJGGS Journal
Volume 12 Issue 1
Year of Publication : 2025
Authors : Jean de Dieu Izerimana, Anthony Temidayo Bolarinwa, Seconde Ntiharirizwa
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Jean de Dieu Izerimana, Anthony Temidayo Bolarinwa, Seconde Ntiharirizwa, "Geological Mapping for Gold Exploration in Butihinda Muyinga Area, Northeastern Burundi using Remote Sensing and GIS," SSRG International Journal of Geoinformatics and Geological Science, vol. 12,  no. 1, pp. 10-22, 2025. Crossref, https://doi.org/10.14445/23939206/IJGGS-V12I1P102

Abstract:

Geological mapping of gold deposits in Butihinda-Muyinga is an indispensable stage to recognizing gold potential in the region. Gold mineralization in the region of Butihinda-Muyinga is linked to iron oxides formed from the oxidation of sulfide minerals. Remote sensing via Landsat-8 imagery is used to support initial gold exploration activities. Different image processing techniques such as Red Green Blue (RGB) combination, band ratios, and Principal Component Analysis (PCA) are implemented to identify geological features indicative of gold mineralization. Gold mineralization in this area is associated with iron oxide minerals. The main aim is to identify these minerals via remote sensing and Geographical Information System (GIS) techniques. The findings show that selective PCA is the most effective technique for mapping pixels containing spectral signatures of hydroxyl and iron oxide minerals. The processed imagery successfully distinguishes urban areas, iron and hydroxyl-rich zones, and clay rich areas. The dominant NNE-SSW structural trends identified in the imagery are considered highly promising for gold mineralization. They are validated through field observations, which revealed a clear correlation between the remote sensed data and field geological mapping.

Keywords:

Band ratio, Gold mineralization, Landsat-8, Principal Component Analysis (PCA), Remote sensing.

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