Detection of coal mine fire in Jharia Coal Field using Landsat-7 ETM+ data
Research Highlights
► Detection and mapping of Jharia Coal Field fire by Landsat-7 ETM+ (2006) data. ► Establish a relation between the infrared camera and satellite image temperature. ► Derived correlation equation find out the temperature of unapproachable fire places.
Introduction
The surface and subsurface coal fire in the vicinity of combustion places was being assessed through traditional borehole technique. Temperature of in-depth fire was detected putting a thermocouple or thermometer attached with cable in the borehole (Sinha and Singh, 2005). Radioactive and resistivity methods are part of Geophysical method. In radioactive method, radioactive element emits α (alpha) particle which can be measured. Concentration of α particles are directly proportional to the temperature, i.e., high temperature means high concentration of α particles and true for the reciprocal. In the resistivity method, electrical resistance of the burnt rock is measured through few electric poles and compared with standard resistance value of that rock (Gangopadhyay, 2003). Thermo-compositional studies, temperature and gas analysis are carried out to determine the presence and intensity of fire in mines (Sinha and Singh, 2005). Thermo-graphic technique for thermal images shows each and every pixel temperature values taken on the ground using thermal infrared camera. The coal fire detection to delineate coal fire areas is possible on the basis of temperature difference (Zhang et al., 2005). The airborne remote sensing techniques use black/white and color photography in detecting coal mine fires.Space borne remote sensing works with data from a variety of radar and high resolution satellites such as NOAA, Landsat TM/ETM+, SPOT, CBERS, IKONOS and Quickbird as well as a number of Indian and Russian satellites (Guan, 2005).
Remote sensing technique is being used since early 1960's for studying coal mine fire with airborne thermal scanner. Voigt et. al. (2004) described an integrated satellite remote sensing approach for detection and monitoring of near surface coal seam fires by observing subtle land surface changes induced by the fires. In Jharia Coal Field, Prakash et al. (1997) used the Landsat-5 Thematic Mapper (TM) band 6 night-time data to identify surface and subsurface fires. Based on a dual band approach for TM data, Prakash and Gupta (1999) evolved a method for calculating the area of surface fires. Prakash and Vekerdy (2004) designed a unique processing and analysis tool to detect, map and monitor coal mine fire in time. These tools also help to generate maps showing fire depth, fire risk and priority for fire fighting. The land cover mapping with pixel based and objects oriented image analysis of coal fire was applied in China using the Landsat-7 ETM+ and ASTER data. The overall accuracy was obtained as 70% and 80% for pixel based and object oriented image analysis approach respectively (Yan, 2003). The propagation and location of surface coal fire of JCF was assessed on field based modeling of pixel integrated temperature for differentiating surface and subsurface fire pixel in Landsat TM thermal infrared 1996, 1992 data (Chatterjee, 2006). On the basis of a fire dynamics study of JCF the spatial coverage of surface and subsurface coal fires was found to change from 0.42 and 2.06 km2 in 1992 to 0.33 and 1.36 km2 in 1996 and 0.08 and 1.60 km2 in 2001 respectively (Chatterjee et al., 2007). Kuenzer et al. (2007) derived an algorithm for multispectral remote sensing data to delineate the coal fire area. This algorithm is applicable for Landsat, ASTER and MODIS data. Gautam (2008) used National Oceanic and atmospheric Administration (NOAA) and Advance Very High Resolution Radiometer (AVHRR) data to detect the surface hot spot of JCF region by developing an algorithm to find out the subsurface hot spot with operational satellite data. The thermal anomalies of satellite image were verified through ground temperature survey, distinguished the anomalies between coal fire, domestic and industrial fire. The disparity between temperature observed on the surface and that measured from the satellite is because of the dimension of the fire zone and atmospheric absorptions. The study was carried out using Landsat TM band 6 data in Raniganj Coal Field, West Bengal, India, by Martha et al. (2005).
Present paper is an attempt to study the coal mine fire hot spots and establish correlation between satellite Landsat-7 ETM+ thermal infrared data of 29th March 2006 and ground data taken from thermal camera of JCF of March, 2009. The surface and subsurface mine fires are detected based on: (i) surface temperature measurement and, (ii) changes in spatial extent of fire-affected areas. The ETM+ imagery band 6 data is used for detection and demarcation of mine fire with spatial resolution of 60 m. It has improved the ability of coal fire detection in unapproachable areas. Ground validation of these data was carried out by comparing the data observed from field by using infrared image of the thermal scanning camera. Global Positioning System (GPS) has been used to find out the co-ordinates of fire spots whose thermal images have been taken. The ERDAS 9.1 software has been used to process the satellite image.
Section snippets
Study area
Coal seams were consumed by coal mine fire for several decades and centuries in major coal-producing countries including China, USA, India and Indonesia (Stracher and Taylor, 2004). In India major coal fires are located in Jharia, Raniganj, Singrauli and Singareni coal fields. The most complex coal fire spread over JCF has been selected for the study which is confined between latitudes 23°38' N and 23°50' N and longitudes 86°07' E and 86°30' E (Fig. 1). The maximum extent of the coal field is
Temperature calculation from Landsat-7 (ETM+) data
The earth observation satellite Landsat-7 Enhanced Thematic Mapper (ETM+) was launched on April 15, 1999, from Vandenburg Air Forces CA, U.S.A. Landsat-7, which is in sun-synchronous orbit about 705 km above the earth collects data in a swath of 185 km. Its revisit interval is 16 days. The ETM+ bands 1 through 5 and 7 are 30 × 30 m spatial resolution. The thermal infrared band 6 (10.40–12.50 μm) and band 8 (panchromatic) have spatial resolution of 60 × 60 m and 15 × 15m respectively. It produces two
Validation of satellite data
Validation is required for proper assessment of image data. The GPS points were used as ground control points to optimize the result of image as well as geometric correction and registration and some of them helped to locate the position of coal fire area. The ground temperature of the fire affected area was obtained by infrared image of the thermal imagine camera. GPS was used for confirming the geospatial position for processing of radiometric correction; image transformation and infrared
Results and analysis
Coal mine fire map was prepared using satellite image data of the year 2006. The highest temperatures found in satellite image are 77.16 °C and 51.54 °C in low and high gain respectively.
The coal mine fire map reveals that the coal fire is distributed mostly in the eastern part of the JCF (Fig. 3). Two major coal fire zones are present in the eastern part of JCF, one is Lodna–Tisra-Bhulanbarari-Kujama–Jellagora and other is Kusunda – Kendudih area. The western fire zone on the other hand is
Conclusion
The Landsat-7 ETM+ data was used to derive the coal mine fire map and classified into surface and subsurface fires. By using Landsat-7 ETM+ band 6 thermal data, the surface coal fire could be detected more satisfactorily. The above study revealed that the eastern part of JCF was more affected due to coal mine fire in comparison to western part. The collieries affected by coal mine fire were Lodna, Bagdigi, North Tisra, Bhulanbarari, Kujama, Jiyalgarha, Bansjora, Kusunda, and Kendudih in eastern
Acknowledgement
The authors acknowledge all staff of the Mine Fire Division, CIMFR, for their necessary help. The authors are grateful to the Director of CIMFR, Barwa Road Dhanbad for his kind permission to publish the paper. The views expressed in this paper are of authors not necessarily of CIMFR.
References (20)
Coal fire mapping from satellite thermal IR data: A case example in Jharia Coal Field, Jharkhand, India
ISPRS Journal of Photogrametry and remote sensing
(2006)The Jharia mine fire controlled technical assistance project: An analysis
International Journal of Coal Geology
(2004)- et al.
Design and implementation of a dedicated prototype GIS for coal fire investigations in North China
International Journal of Coal Geology
(2004) - et al.
Coal fire burning out of control around the world: Thermodynamic recipe for environmental catastrophe
International Journal of Coal Geology
(2004) - et al.
Integrating satellite remote sensing techniques for detection and analysis of uncontrolled coal seam fire in North China
International Journal of Coal Geology
(2004) - et al.
Dynamics of coal fire in Jharia Coal Field, Jharkhand, India during the 1990s as observed from space
Current Science
(2007) - Gangopadhyay, P. K., 2003. Coalfire detection and Monitoring in Wuda North China: A multi- spectral and multi-sensor...
- et al.
An efficient contextual algoirthm to detect subsurface fires with NOAA/AVHRR data
IEEE transactions on geo-science and remote sensing
(2008) - Guan Haiyan, 2005. Spontaneous coal seam fires, The Chinese Perspective. ERSEC Ecological Book Series 4, International...
Cited by (63)
A synergetic approach for quantification and analysis of coal fires in Jharia Coalfield, India
2023, Physics and Chemistry of the EarthCharacteristics of CO, CO<inf>2</inf> generation and reactive group conversion in isothermal smoldering combustion of coal
2023, FuelCitation Excerpt :Yet coalfield fires persist around the world, which seriously hinders the development of the coal industry [3,4]. It is well known that the Jharia in India, Helan Mountains in China, and Centralia in America have suffered from coal fires for over half a century [5,6]. Underground coal mine often face difficulties with inadequate ventilation, which can result in inadequate heat dissipation and increased temperature of the coal body, which is known as spontaneous combustion [7,8].
Coal fire identification and state assessment by integrating multitemporal thermal infrared and InSAR remote sensing data: A case study of Midong District, Urumqi, China
2022, ISPRS Journal of Photogrammetry and Remote SensingExperimental and theoretical study of the effect of particle size on the forward propagation of smoldering coal
2022, FuelCitation Excerpt :This leads to underground coal fires that can last for months or even years. Famously, both Jharia in India and Centralia in the United States have suffered from underground coal fires for more than half a century [3,4]. The smoldering combustion process depends on the heat, which is released by the heterogeneous surface reaction between the solid and oxygen, to maintain propagation.
Spatio-temporal variation and propagation direction of coal fire in Jharia Coalfield, India by satellite-based multi-temporal night-time land surface temperature imaging
2021, International Journal of Mining Science and TechnologyCitation Excerpt :The space-based remote sensing technology has the potential to the monitoring of coal fire over a large area at a regular time interval and is affordable as well. The studies conducted in the past have reported to delineate coal fire in the JCF using space-based coarser as well as medium spatial resolution thermal infrared (TIR) data [1,11–16]. However, coarser spatial resolution TIR data of space-borne sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) is not recommended for quantitative analysis of coal fires [13].
Role of H<sup>+</sup>, HF, SO<inf>4</inf><sup>2−</sup> and kaolin in fixing Hg of coal fire sponge
2021, Science of the Total Environment