Mapping Vulnerable Areas of the Lolodorf Uranium Deposit in Southern Cameroon using Remote Sensing and Gravimetry
L. Gba Empime
Higher Institute of Agriculture, Forestry, Water and Environment, University of Ebolowa, Ebolowa, Cameroon.
H. L. Ekoro Nkoungou *
Higher Technical Teacher’s Training College of Ebolowa, University of Ebolowa, Ebolowa,Cameroon.
M. A. Edima A. Kitiby
Higher Technical Teacher’s Training College of Ebolowa, University of Ebolowa, Ebolowa,Cameroon.
S. A. Zogo Tsala
Higher Technical Teacher’s Training College of Ebolowa, University of Ebolowa, Ebolowa,Cameroon.
P. Eba’a Owoutou
Higher Technical Teacher’s Training College of Ebolowa, University of Ebolowa, Ebolowa,Cameroon.
M. Bikoro Bi-Alou
Higher Institute of Agriculture, Forestry, Water and Environment, University of Ebolowa, Ebolowa, Cameroon.
*Author to whom correspondence should be addressed.
Abstract
The Lolodorf uranium deposit in southern Cameroon occurs within a region where respiratory and mental health concerns have been reported, creating a need to identify areas that warrant detailed environmental investigation. This study mapped potentially vulnerable areas by integrating remote-sensing, gravimetric, and health-related spatial indicators. Clay-mineralisation and vegetation indices were derived from Landsat data, while shallow lineament density was obtained from remote-sensing analysis. Deep structural features were delineated from gravity data through Bouguer and residual anomaly processing, spectral analysis, Euler deconvolution, and horizontal-gradient magnitude. The resulting thematic layers, together with the spatial distribution of pulmonary disease prevalence, were weighted and combined using the Full Information Maximum Likelihood approach. The integrated map identified five vulnerability classes, with the highest values concentrated around Lolodorf and extending towards Bingambo and Bipindi. These areas were characterised by high clay-mineralisation index values, low vegetation-index values, and increased densities of deep and shallow lineaments. Comparison with reported radon and thoron occurrence at Awanda and Bikoué showed spatial agreement with the mapped vulnerable zone. The findings indicate that the combined geospatial approach can support the preliminary prioritisation of locations for field-based radiological measurements, soil and water sampling, indoor radon and thoron surveys, and epidemiological investigation. The resulting map should be regarded as a screening tool rather than evidence of a causal relationship between uranium occurrence and reported disease.
Keywords: Lolodorf uranium deposit, remote sensing, gravimetry, radon, thoron, clay mineralisation, normalised vegetation index, lineament density, vulnerability mapping