Journal of Earth Science

, Volume 30, Issue 5, pp 1010–1019 | Cite as

Spatial Distribution Prediction of Laterite Bauxite in Bolaven Plateau Using GIS

  • Yuan Ouyang
  • Hanhu LiuEmail author
  • Xiao Wang
  • Shusheng Liu
  • Jinghua Zhang
  • Hui Gao
Seismology, Mathematical and Remote Sensing Geology


Mineral resources are the most important natural resources for developing countries. Bauxite is an indispensable mineral resource for industrial production. Potential assessment of bauxite is an important issue in Indochina Peninsula. In this paper, the factors affecting the mineralization of the lateritic bauxite are analyzed. The collected spatial data are processed and the information is extracted to obtain the spatial extent of favorable constraints. Then, the spatial distribution of potential bauxites on the Bolaven Plateau has been investigated with a Boolean modeling process in GIS environment on the basis of some constraints such as rock, elevation, topographical features and vegetation coverage. Finally, based on the hydrogeological conditions and alteration information of Fe3+ and OH-, the bauxite mapping has been carried out. There are twenty bauxite metallogenic areas delineated, with a total area of 750 km2, which is 5% of the entire study area. This has greatly reduced the scope of the field investigation. Seven of the twenty predicted areas were validated in the field and six of them were found to have bauxite mineralization. Using the methods proposed in this study, the potential bauxite for the entire Bolaven Plateau could be achieved much more cheaply than the traditional methods. This study also provides a good idea for the prediction of laterite bauxite in the other regions of the Indochina Peninsula.

Key words

Bolaven Plateau GIS laterite bauxite Boolean model geochemistry remote sensing 


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This work was supported by the China Geological Survey (No. 121201010000150013) and the National Natural Science Foundation of China (No. 41102225). The final publication is available at Springer via

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Copyright information

© China University of Geosciences (Wuhan) and Springer-Verlag GmbH Germany, Part of Springer Nature 2019

Authors and Affiliations

  1. 1.Chengdu CenterChina Geological SurveyChengduChina
  2. 2.Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and ResourcesChengdu University of TechnologyChengduChina

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