Gornye nauki i tekhnologii = Mining Science and Technology (Russia)

Advanced search

The Method of Detection of Clay Minerals and Iron Oxide Based on Landsat Multispectral Images (as Exemplified in the Territory of Thai Nguyen Province, Vietnam)

Full Text:


Landsat multispectral images have been successfully used for discovering some mineral deposits in different regions of the world. Some minerals, including clay minerals and iron oxide, can be detected by multispectral surveys due to their spectral characteristics. This paper presents the results of the application of principal component analysis and Crosta technique for detecting accumulations of clay minerals and iron oxide based on a Landsat 8 Oli multispectral image of Thai Nguyen Province, north of Vietnam. The obtained results have demonstrated the feasibility and suitability of prompt detecting mineral deposits based on the remote sensing data. The image processing methods and facilities tested in this study can be used to create maps of distribution of clay minerals and iron oxide for effective and expedient prospecting and exploration for minerals.

About the Authors

Le Hung Trinh
Le Quy Don Technical University.
Viet Nam
Ha Noi city.

V. R. Zabloskii
2Moscow State University of Geodesy and Cartography.
Russian Federation


1. Oparin V. N., Potapov V. P., Ginliyatullina O. L., On comprehensive assessment of environmental condition based on data of earth remote sensing in regions with high man-induced impact: Physical and technical issues of mining, 2014, No. 6, pp. 199-209. (in Russ.)

2. Usikov V. I., Lipina L. N. Evaluation of geoecological situation in the area of Maly Khingan based on data of remote sensing of the earth's surface: Physical and technical issues of mining, 2018, No. 2, pp. 154-160. (in Russ.)

3. Abrams M. J. Remote sensing of porphyry copper in Southern Arizona, Economic Geology, 1983, No. 78, pp.591-604.

4. Alasta A. F. Using remote sensing data to indentify iron deposits in central western Libya, International conference on Emerging trends in Computer and Image processing, Bangkok, 2011, pp. 56-61.

5. Crosta A. P., Moore J. M. Enhancement of LANDSAT Thematic Mapper imagery for residual soil map¬ping in SW Minas Gerais State Brazil: a prospecting case history in greenstone belt terrain, Proceedings of the 9th Thematic Conference on Remote Sensing for Exploration Geology, Calgary (Ann Arbor, MI: Environmental Re¬search Institute of Michigan), 1989, pp. 1173-1187.

6. Clark R. N., Swayze G. A., Wise R., Livo K. E., Hoefen T. M., Kokaly R. F., Sutley S. J. USGS Digital Spectral library, USGS Open file Rep, 1989.

7. Dematte J. A. M., Fiorio P. R., Ben-Dor E. Estimation of soil properties by orbital and laboratory reflec¬tance means and its relation with soil classification, The Open Remote Sensing Journal, 2009, Vol. 2, pp.12-23.

8. Dogan H.D. (2012). Mineral composite assessment of Kelkit River Basin in Turkey by means of remote sensing, Journal Earth System Science, Vol. 118(6), pp.701-710.

9. Fongaro C., Dematte J., Rizzo R., Safanelli J., Mendes W., Dotto A., Vicente L., Franceschini M., Ustin S. Improvement of Clay and Sand Quantification Based on a Novel Approach with a Focus on Multispectral Satellite Images, Remote Sensing, 2018, 10, 1555; doi:10.3390/rs10101555.

10. Fraster S. J., Green A. A. A software defoliant for geological analysis of band ratio, International journal of remote sensing, 1997, Vol.8, pp. 525-532.

11. Goetz A. F., Rock F. H., Rowan B. N. Remote sensing for exploration: An overview, Economic Geolo¬gy, 1983, Vol. 78, 573-590.

12. Hunt G. R., Ashley R. P. Spectra of altered rocks in the visible and near infrared, Economic Geology, 1979, Vol. 74, pp. 1613-1629.

13. Kaufman H. Mineral exploration along the Agaba-Levant structure by use of TM-data concepts, pro¬cessing and results, International Journal of Remote Sensing, 1988, 9:1630-1658.

14. Khaleghi M., Ranjbar H. Alteration mapping for exploration of porphyry copper mineralization in Sar- duiyed area, Kerman province, Iran using ASTER SWIR data, Australian Journal of Basic and Applied Sciences, 2011, 5(8), pp. 61-69.

15. Loughlin W. P. Principal component analysis for alteration mapping, Photogrammetric Engineering and Remote Sensing, 1991, 57(g), pp. 1163-1169

16. Mia M. B., Fujimitsu Y. Mapping hydrothermal altered mineral deposits using LANDSAT 7 ETM+ im¬age in and around Kuju volcano, Kyushu, Japan, Journal Earth System Science, 2012, Vol. 121(4), pp.1049-1057.

17. Pour A. B., Hashim M. Integrating PALSAR and ASTER data for mineral deposits exploration in tropi¬cal environments: a case study from Central Belt, Peninsular Malaysia, International Journal of Image and Data Fusion, 2015, 6(2), pp. 170-188.

18. Pour A. B., Park T., Park Y., Hong J., Zoheir B., Pradhan B., Ayoobi I., Hashim M. Application of Mul¬ti-Sensor Satellite Data for Exploration of Zn-Pb Sulfide Mineralization in the Franklinian Basin, North Green¬land, Remote Sensing, 2018, 10(8), 1186; doi:10.3390/rs10081186.

19. Singh A., Harrison A. Standarlized principal components, International Journal of Remote Sensing, 6(6), 1985, pp.883-896.

20. Sridhar B. B., Vincent R. K. Mapping and estimation of phosphorus and copper concentrations in Fly Ash spill area using LANDSAT TM data, Photogrammetric Engineering and Remote Sensing, 2009, Vol. 75(9), pp.1030-1033.

21. Trinh L. H. Application of remote sensing technique to detect and map iron oxide, clay minerals and fer¬rous minerals in Thai Nguyen province, Горные науки и технологии, 2016, Vol. 1, 60 - 66.

22. Trinh L. H. Application of band ratio method to detect iron oxide, clay minerals and ferrous minerals, Mining Industry Journal, 2014, Vol. 4, pp. 19-24.

23. Van der Meer F. D., van der Werff H. M. A., van Ruitenbeek F. J. A. Potential of ESA’s Sentinel-2 for geological applications, Remote Sensing of Environment, 2014, 148, 124-133

24. Vietnam national coal-mineral industries holding corporation limited (Vinacomin). Available at: www

25. The official website of GloVis. Available at:


For citations:

Trinh L., Zabloskii V.R. The Method of Detection of Clay Minerals and Iron Oxide Based on Landsat Multispectral Images (as Exemplified in the Territory of Thai Nguyen Province, Vietnam). Gornye nauki i tekhnologii = Mining Science and Technology (Russia). 2019;4(1):65-75.

Views: 711

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

ISSN 2500-0632 (Online)