THERMAL REMOTE SENSING METHOD IN DETECT AND MONITORING SUBSURFACE COAL FIRE IN KHANH HOA COAL MINE, THAI NGUYEN PROVINCE

Authors

  • Trịnh Lê Hùng Học viện Kỹ thuật Quân sự

Abstract

The Khanh Hoa coal mine is a surface coal mine in the Thai Nguyen province, which is one of the largest deposits of coal in the Vietnam. In recent years due to many reasons such as backward mining techniques and unauthorized mining caused subsurface coal fire in this area. Coal fire is a dangerous phenomenon which affects the environment seriously by releasing toxic fumes which causes forest fires, and subsidence of infrastructure surface. This article presents study on the application of LANDSAT multi – temporal thermal infrared images, which help to detect coal fire. The results obtained in this study can be used to monitor fire zones so as to give warnings and solutions to prevent coal fire.

Author Biography

Trịnh Lê Hùng, Học viện Kỹ thuật Quân sự

Tiến sĩ chuyên ngành Viễn thám, trường Đại học tổng hợp Trắc địa và Bản đồ Moscow

References

REFERENCES

Luu Duc Hai, Nguyen Thi Hoang Lien (2009). Renewable energy policies for sustainable development in Vietnam, VNU Journal of Sciences, Earth Sciences, Vol. 25, Issue 3, 133 – 142.

Prakash, A., Gupta, R. P. (1999). Surface fires in Jharia Coalfield, India - their distribution and estimation of area and temperature from TM data, International Journal of Remote Sensing, 20, pp. 1935-1946.

Chen Y., Li J., Yang B., Zhang S. (2007). Detection of coal fire location and change based on multi – temporal thermal remotele sensed data and field measurements, International Journal of Remote Sensing, Vol. 28, Issue 15, pp. 3173 – 3179.

Cracknell A.P., Mansor S.B. (1992). Detection of sub – surface coal fires using LANDSAT thematic mapper data, International Archives of Photogrammetry and Remote Sensing, Vol. 29, pp. 750 – 753.

Prasun K., Kuntala L., Kanika S. (2005). Application of remote sensing to dentify coal fires in the Raniganj coalbelt, India, Internatinoal journal of Applied earth observation and Geoinformation, 117, 8 pp.

Mishra R.K. et al (2014). Study of coal fire dynamics of Jharia coalfield using satellite data, International journal of Geomatics and Geosciences, Vol. 4, No. 3, 477 – 484.

Mishra R.K. et al (2012). Estimation of air pollution concentration over Jharia coalfield based on satellite imagery of atmospheric aerosol, International journal of Geomatics and Geosciences, Vol. 2, No. 3, 723 – 729.

Hongyuan Huo et al. (2014). Detection of coal fire dynamics and propagation direction from multi-temporal nighttime Landsat SWIR and TIR data: A case study on the Rujigou coalfield, Northwest China, Remote sensing, 6, 1234 – 1259.

Gautam R.S. et al. (2008). An efficient contextual algorithm to detect subsurface fires with NOAA/AVHRR data, IEEE Geoscience and Remote sensing, Vol. 46, Issue 7, 2005 – 2015.

Zhang J., Wagner W., Prakash A., Mehl H., Voidt S. (2004). Detecting coal fires using remote sensing techniques, International journal of Remote sensing, 25, 3193 – 3220.

Voigt S. et al. (2004). Integrating satellite remote sensing techniques for detection and analtsis of uncontrolled coal seam fire in North China, International journal of coal geology, 59, 121 – 136.

Valor E., Caselles V. (1996). Mapping land surface emissivity from NDVI. Application to European African and South American areas, Remote sensing of Environment, 57, pp. 167 – 184.

Van de Griend A.A., Owen M. (1993). On the relationship between thermal emissivity and the normalized difference vegetation index for natural surface, International journal of remote sensing, 14, pp. 1119 – 1131.

National Aeronautics and Space Administration (NASA), LANDSAT Science data user’s Handbook.

Published

2017-06-02

Issue

Section

Journal of Earth Science and Environment