Design of Geological Sketch Map in a Forested Area Using the Advanced Optical Remote Sensing Techniques and the Petrography: Kambele and Surroundings Example (Batouri Gold District, Eastern Cameroon)

Bissegue Jean Claude^{1, 2,} , Ravindra Nath Tiwari², Namit Kumar Jha² and Tchameni Rigobert¹

¹Department of Earth Sciences, Faculty of Science, University of Ngaoundéré P.O. Box 454 Ngaoundéré, Cameroon

²Geoinformatics Department, NETRA institute of Geoinformatics Management and Technologies Foundation, Dwarka Mor, New Delhi-110059, India

Cite this paper:
Bissegue Jean Claude, Ravindra Nath Tiwari, Namit Kumar Jha and Tchameni Rigobert. Design of Geological Sketch Map in a Forested Area Using the Advanced Optical Remote Sensing Techniques and the Petrography: Kambele and Surroundings Example (Batouri Gold District, Eastern Cameroon). Journal of Geosciences and Geomatics. 2024; 12(3):55-61. doi: 10.12691/jgg-12-3-1

Abstract

The objective of this study is to design the geological sketch map of the Kambele sector and surrounding areas using object-oriented classification (OOC) and field observation data. Kambele is a vast mining field located in the center of the Batouri gold district in Eastern Cameroon. The method for lithological mapping consisted of the segmentation and supervised classification of the Landsat 8/9 OLI image, then the directional filtering of the SRTM image for the extraction of Faults. The derived data were then cross-referenced with field observation points in GIS Software. The major result includes the geological map of Kambele; this will contribute to improve the geological and mining information of the sector.

Keywords:
Kambele advanced remote sensing Petrography forested areas applied geomatics sketch map

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References:

[1]	Scanvic, J.Y., Delpont G., King C., 1985. Structural and Geobotanical Contribution of Remote Sensing to Exploration of Hidden Deposits in Brittany (France). BRGM, Service Géologique National, Rapport Final du projet CEE MSM 037F, 151p.
[2]	Forster, R.P., Piper, D.P., 1993. Archaean lode gold deposits in Africa: crustal setting, metallogenesis and cratonization. Ore Geology Reviews, 8, 303–347.
[3]	Gazel, J., Gérard, G., 1954. Carte géologique de reconnaissance du Cameroun au 1/500 000, feulle Batouri-Est avec notice explicative. Memoire. Direction Mines Géologie, Yaoundé, Cameroon.
[4]	African Aura Mining, 2009. Batouri gold project, Cameroon. African Aura Resource (UK) Ltd., London. http://www.african-aura.com/s/Batouri.asp Accessed on March 7, 2009.
[5]	Suh, C. E., Lehmann, B., Mafany, G. T., 2006. Geology and geochemical aspects of lode gold mineralization at Dimako-Mboscorro, SE Cameroon. Geochemistry: Exploration, Environment, Analysis 6(4), 295-309.
[6]	Tremblay, M., 1975. Report on gold properties in Eastern Cameroon. – Records, Ministry of Mines, W ater and Energy, Cameroon, 45 pp.
[7]	Ducrot, D., 2005. Méthodes d’analyse et d’interprétation d’images de télédétection multisources. Extraction de caractéristiques du paysage, Mémoire d’Habilitation à Diriger des Recherches, INP Toulouse, 216 p.
[8]	Ségal, D.B., 1983. Use of Landsat multispectral scanner data for definition of limonic exposures in heavily vegeted ereas. Econ. Geology number 4, vol. 78.
[9]	Warner, T.A., Levandowski, D.W., Bel R., Cetin H., 1994. Rule-based geobotanical classification of topographic, aeromagnetic, and remotely sensed vegetation community data. Remote Sens Environ. 50(1):41–51.
[10]	Castleman, K.R., 1996. Digital image processing. Prentice-Hall, New Jersey.
[11]	Tucker, C. J., 1977. Use of near infrared/red radiance ratios for estimating vegetation biomass and physical status. Proceedings of 11th International Symposium on Remote Sensing of Environment, AnnArbor, Mi., vol. 1, ERIM, p.493-496.
[12]	Kerdiles, H., Grondona, M., 1995. NOAA-AVHRR NDVI descomposition and subpixel classification using linear mixing in the Argentinean Pampa. International Journal of Remote Sensing 1995, vol.16, no. 7, 1303-132.
[13]	Faivre, R., Fischer, A., 1997. Predicting crop reflectances using satellite data observing mixed pixels Journal of Agricultural, Biological and Environmental Statistics 2, 87-107.
[14]	Pekkarinen, A., 2002. A method for the segmentation of very high spatial resolution images of forested landscapes, International Journal of Remote sensing, vol. 23, no. 14, pp. 2817 - 2836.
[15]	Hofmann, P., 2001. Detecting informal settlements from IKONOS data using methods of object oriented image analysis – An example from Cape Town (South Africa), Remote Sensing of Urban Areas, JURGENS, pp. 41-42.
[16]	Pettorelli, N., Vik J.O., Mysterud, A., Gaillard, J.M., Tucker C.J., Stenseth N.C., 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol Evol 20(9): 503–510.
[17]	Bissegue, J.C., 2021. Cartographie géologique du district aurifère de l’Arrondissement de Batouri (Est Cameroun): apport des outils de la géomatique pour la prospection de l’or. Mémoire thèse de doctorat Ph/D, Univ. Ngaoundéré, Cameroun, 2021, 260p.
[18]	Lefèvre, M.J., 1983. Télédétection d’anomalies géobotaniques appliquées à la recherche minière BRGM-GDTA. Thèse d’Etat. Univ. P. Sabatier; Toulouse.
[19]	Rock, B. N., Hoshizaki, T., Miller, J. R., 1988. Comparison of In Situ and airborne spectral measurements of blue shift associated with forest decline. Remote Sensing of Environment, vol. 24, p. 109-127.
[20]	Assaah, V. A., 2010. Lode gold mineralisation in the neoproterozoic granitoids of Batourisoutheastern Cameroon. Clausthal univ. of technology, 202p.