Elsevier

CATENA

Volume 140, May 2016, Pages 15-23
CATENA

Distribution of duricrusted bauxites and laterites on the Bamiléké plateau (West Cameroon): Constraints from GIS mapping and geochemistry

https://doi.org/10.1016/j.catena.2016.01.010Get rights and content

Highlights

  • Bauxite occurrence was predicted with a GIS Boolean modeling.

  • Geomorphic and geologic criteria evidenced a potential bauxitic area of 381 km2.

  • Field and geochemical validation provided 56.2 km2 of effective bauxitic land surfaces.

  • Alumina varies from 46 to 66 wt.% (upper surface), to less than 44 wt.% (lower surface).

  • Multistage mapping might be promising for larger scale investigations.

Abstract

Estimation of the mineral resources potential is an important issue for most of developing countries. The spatial distribution of bauxites and lateritic land surfaces on the Bamiléké plateau (West Cameroon) has been investigated with a Boolean modeling process into a GIS environment on the basis of geological constraints such as elevation, rock and soil types, and landscape morphology. Field observation and SRTM (Shuttle Radar Topographic Mission) data allowed the differentiation of two lateritic land surfaces separated by a minimum altitude difference of about 60 m. These surfaces constrained by favorable rock types, slope steepness and soil types provided a potential lateritic bauxitic area of 381 km2 (17.2% of the total study site). Field validation and the integration of legacy spatial data resulted in an area of 60.1 km2 for potential bauxitic ores, i.e. obviously duricrusted bauxitic surfaces (with 47.8 km2 in the upper surface and 12.3 km2 in the lower surface). Alumina contents obtained from duricrust samples were analyzed by geostatistical methods and classical kriging interpolation to discriminate between bauxitic and ferruginous laterites. This highlighted a geochemical trend from higher alumina values on the upper surface (40–66 wt.%) to lower values on the lower surface (13–44 wt.%). Finally, our study documents two duricrusted lateritic surfaces arranged in a staircase manner and having different geochemical characteristics. The total bauxitic-rich surface is distributed in five spots throughout the study area and covers 56.2 km2, while ferruginous laterites occupy a spot of 3.9 km2. GIS mapping approach of lateritic land surfaces, accounting for reliable constraints, might be promising for larger scale investigations of mineral resources in Cameroon.

Introduction

Many Third World Countries rely mainly on their natural resources to sustain their economic development. In Cameroon, the exploitation of mineral resources has traditionally been a significant component of the economy (Ntép Gweth, 2009). However, precise knowledge on the potential of these resources is generally limited by a lack of geo-exploration tool required for their reliable and comprehensive assessment and classification at the national-wide level. In this country, the most widespread ore deposits are lateritic bauxites, representing the 6th reserve in the world. Bauxites occur in the Adamaoua and Western regions, and have been previously studied by many authors (Hiéronymus, 1973, Momo Nouazi et al., 2012, Morin, 1985, Nicolas and Eno Belinga, 1969, Nyobe, 1987) using classical approaches of field survey and laboratory analyses. Today, GIS and remote sensing tools permit more accurate mapping of such resources by integrating favorable geological constraints in a GIS-based model.

Our study aimed at satisfying the practical need for supporting bauxite exploration in Cameroon with up-to-date maps, by defining the relation between bauxitic deposits and their geological environment. For this purpose, we used a GIS-modeling approach, based on a well-established procedure, which was previously tested in several studies on mineral potential assessment (Boroushaki and Malczewski, 2008, Carranza et al., 1999, Cheng and Agterberg, 1999, Guha et al., 2013, Harris et al., 2008, Robinove, 1989, Thole et al., 1979, Varnes, 1974, Zadeh, 1965). The approach deals with GIS-based geologically constrained mineral potential mapping, a multistage strategy for delineating mineralized zones (Reeves et al., 1990). Multivariate and multisource geo-exploration datasets were combined to enhance favorable geologic features indicative of mineral deposit (Bonham-Carter, 1994, Hodgson, 1990). Using the Boolean model of Varnes (1974) and Robinove (1989), our interest is to know whether the spatial criteria linked to the genetic environment and landscape distribution of bauxites can be used to define predictive map of bauxite occurrence for further field exploration and geochemical survey.

Section snippets

Physiography of the study area

The study site lies between longitudes 09°56′–10°20′E, and latitudes 05°18′–5°45′N and covers an area of 2209 km2 within the Bamiléké plateau extending between 09°44′–10°33′E, and 04°10′–05°56′N in West Cameroon (Fig. 1a and b). The Bamiléké plateau covers the southern part of the West Cameroon highland (Fig. 1a) between the Bamoun plateau in the east, the Grassfields in the north and the Mbô plain in the south and west (Fig. 1b). The climate is sub-equatorial, influenced by high altitudes, with

Conceptual model of bauxite occurrence

A conceptual and exploration model for evaluating the bauxite potential of the Bamiléké plateau was built based on geological criteria (Carranza, 2002, De Araújo and Macedo, 2002, Hodgson, 1990, Reeves et al., 1990). We used the Boolean model for examining the spatial relation of geological features, which is based on a reclassification of the input maps into only two classes (Bonham-Carter, 1994, Carranza et al., 2008, Harris et al., 2001, Robinove, 1989, Thiart and De Wit, 2000, Varnes, 1974

Favorable rock types

Volcanic rocks cover a surface of 1406 km2 accounting for 64% of the study area (Fig. 3a), and comprise basalts (64%), trachytes (28%) and ignimbrites (6%), which have been formed since 19 My (Marzoli et al., 1999, Nkouathio et al., 2008). All these volcanic rocks currently show evidence of deep weathering process (Tematio et al., 2004). Phonolite dykes and volcanic ashes cover a limited area (~ 1%) of the study site. These recent volcanic rocks range from 4 My for phonolites (Nkouathio et al., 2008

Spatial features evidence and predictive map of duricrusted bauxites

The Boolean model applied in this study results in a predictive map of the bauxite potential covering 17.2% of the total study area, that matches previously investigated bauxitic areas on the Bamiléké plateau (Hiéronymus, 1973, Momo Nouazi et al., 2012, Morin, 1985, Nyobe, 1987). Beyond the 17.2% bauxite potential from the predictive map, the total confirmed bauxitic area of the Bamiléké plateau only covers about 3% of the total investigated area (56.1 km2). This reduced bauxitic surface can be

Summary and conclusion

This study has suitably combined spatial multisource data to define potential bauxitic laterite distribution on the Bamiléké plateau, and evaluate the usefulness of including field observations, and geochemical data processed by statistical method for improving the assessment of bauxitic potential. Genetic criteria and regolith mapping were successfully used to predict and precisely delineate areas of bauxite occurrence, thereby highlighting a total bauxitic-rich surface of 56.2 km2. The alumina

Acknowledgment

The financial support for geochemical data of this study was provided by the Service de Coopération et d'Action Culturelle de la France au Cameroun (SCAC) (815364G). The geochemical analysis has been carried out at the Centre Européen de Recherche et d'Enseignement des Géosciences de l'Environnement (CEREGE), Aix Marseille University, OSU Pytheas, France.

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