Lineament Mapping Using RS and GIS Techniques at Mbateka, SE Cameroon: Implication for Mineralization

  • Melvin Tamnta NforbaEmail author
  • Linus Api
  • Nelvice Berinyuy
  • Salomon César Nguemhe Fils
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


The application of remote sensing and GIS technology has shown a great promise, over the years, and offered opportunities for improving identification of areas that are likely to be locations of lineament and mapping. Based on the ability to identify geological features, Landsat ETM-7 satellite data images were used and band-5 was found as the most suitable for lineament delineation. Parameters such as drainage patterns, previously mapped faults, lineaments, and lithological contact layers were used in this study, to produce a fault potential prediction map using the overlay model technique. The generated fault density map classifies the study area into 5 potential zones, thus, very low, low, moderate, high, and very high potential zones. 33 faults, which may represent new faults in the area of investigation were obtained from the correlation between fault segments and faults data collected from field work. NW–SE is the general orientation of the fractures and N100-1100E was the major trend obtained from fault analyses. Poly-phase ductile-brittle structures such as shear zone and faults in the study area were confirmed by our findings. Iron mineralization in the area is controlled by those structures since they form pathways for mineralizing fluids.


Landsat ETM-7 images Lineaments Mineralisation Mbetaka 


  1. 1.
    Abdullah, A., Nassr, S., Ghaleeb, A.: Remote sensing and geographic information system for fault segments mapping a study from Taiz Area, Yemen. J. Geol. Res., 1–16 (2013).
  2. 2.
    Karimi, B., Karimi, H.A.: An automated method for the detection of topographic patterns at tectonic boundaries. In: The Ninth International Conferences on Pervasive Patterns and Applications, pp. 72–77 (2017)Google Scholar
  3. 3.
    Papadaki, E.S., Mertikas, S.P., Apostolos, Sarris A.: Identification of lineaments with possible structural origin using ASTER images and DEM derived products in Western Crete, Greece. EARSeL eProceedings 10, 9–26 (2011)Google Scholar
  4. 4.
    Cracknell, A.P., Hayes, L.: Introduction to Remote Sensing. Taylor & Francis Press, London (1991)Google Scholar
  5. 5.
    Edet, A.E., Teme, S.C., Okereke, C.S., Esu, E.O.: Application of remote sensing data to groundwater exploration: a case study of the cross river state, Southeastern Nigeria. Hydrogeol. J. 6, 394–404 (1998)CrossRefGoogle Scholar
  6. 6.
    Solomon, S., Ghebreab, W.: Lineament characterization and their tectonic significance using landsat TM data and field studies in the central highlands of Eritrea. J. Afr. Earth Sci. 46(4), 371–378 (2006)CrossRefGoogle Scholar
  7. 7.
    Mogaji, K.A., Aboyeji, O.S., Omosuyi, G.O.: Mapping of lineaments for groundwater targeting in the basement complex region of Ondo State, Nigeria, using remote sensing and geographic information system (GIS) techniques. Int. J. Water Resour. Environ. Eng. 3(7), 150–160 (2011).
  8. 8.
    Ndéléc, A., Nsifa, E.N: Le complexe du Ntem (Sud-Cameroun): une serie tonalitique rondhematique archeene typique. In: Schandelmeier, H., Matheis, G. (eds.) Current Research African Earth Sciences, pp. 3–6. Berlin (1987)Google Scholar
  9. 9.
    Vicat, J.P., Lips, B., Pouclet, A., Léger, J.M., Willems, L.: Phénomènes pseudo-karstiques dans les roches plutoniques et métamorphiques du Sud du Cameroun. Karstologia 29, 17–22 (1997)CrossRefGoogle Scholar
  10. 10.
    Vicat, J.P., Gaetan, M., Pouclet, A.: Les granitoïdes de la couverture protérozoïque de la bordure nord du craton du Congo (Sud-Est du Cameroun et Sud-Ouest de la République centrafricaine), témoins d’une activité magmatique post-kibarienne à pré-panafricaine. Earth Planet. Sci. 332, 235–242 (2001)Google Scholar
  11. 11.
    Nzenti, J.P., Abaga, B., Suh, C.E., Nzolang, C.: Petrogenesis of peraluminous magmas from the Akum-Bamenda Massif, PanAfrican Fold Belt, Cameroon. Int. Geol. Rev. 53(10), 1121–1149 (2011)CrossRefGoogle Scholar
  12. 12.
    Sulaksana, N., Hamdani, A.H.: The analysis of remote sensing imagery for predicting structural geology in Berau Basin East Kalimantan. Int. J. Sci. Res. 3(4), 18–21 (2014)Google Scholar
  13. 13.
    Limaye, M.A.: Unfolding the time relationship of structural events through landsat data: a case study from Khandia formation, Champaner group, Gujarat. J. Geomatics 10(1), 24–28 (2016)Google Scholar
  14. 14.
    Wambo, J.D.T., Ganno, S., Ngambu, A.A., Negue, N.E., Ondoa, J.M., Nzenti, J.P.: Use of landsat 7 ETM+ Data for the geological structure interpretation: case study of the Ngoura-Colomines Area, Eastern Cameroon. J. Geosci. Geomatics, 4 (3), 61–72 (2016).,
  15. 15.
    Nzenti, J.P., Kapajika, B., Wörner, G., Lubala, R.T.: Synkinematic emplacement of granitoids in a Pan-African shear zone in Central Cameroon. J. Afr. Earth Sci. 45, 74–86 (2006)CrossRefGoogle Scholar
  16. 16.
    Ngako, V., Affaton, P., Nnange, J.M., Njanko, T.: Panafrican tectonic evolution in central and Southern Cameroun: transpression and transtension during sinistral shear movement. J. Afr. Earth Sci. 36, 207–214 (2003)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Melvin Tamnta Nforba
    • 1
    Email author
  • Linus Api
    • 2
  • Nelvice Berinyuy
    • 3
  • Salomon César Nguemhe Fils
    • 4
  1. 1.School of Geology and Mining EngineeringUniversity of NgaoundereMeigangaCameroon
  2. 2.Department of Geology and MiningSaint Monica University InstituteBueaCameroon
  3. 3.Economic Geology Unit, Department of GeologyUniversity of BueaBueaCameroon
  4. 4.Institute of Geological and Mining Research (IRGM)YaoundeCameroon

Personalised recommendations