Monitoring Subsurface Coal Fires in Jharia Coalfield Using Observations
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Monitoring subsurface coal fires in Jharia coalfield using observations of land subsidence from differential interferometric synthetic aperture radar (DInSAR) Nishant Gupta, Tajdarul H Syed∗ and Ashiihrii Athiphro Department of Applied Geology, Indian School of Mines, Dhanbad, India. ∗Corresponding author. e-mail: [email protected] Coal fires in the Jharia coalfield pose a serious threat to India’s vital resource of primary coking coal and the regional environment. In order to undertake effective preventative measures, it is critical to detect the occurrence of subsurface coal fires and to monitor the extent of the existing ones. In this study, Differential Interferometric Synthetic Aperature Radar (DInSAR) technique has been utilized to monitor subsurface coal fires in the Jharia coalfield. Results showed that majority of the coal fire-related subsidence were concentrated on the eastern and western boundaries of the coalfield. The magnitude of subsidence observed was classified into high (10–27.8 mm), low (0–10 mm) and upliftment (−10–0 mm). The results were strongly supported by in situ observations and satellite-based thermal imagery analysis. Major subsidence was observed in the areas with repeated sightings of coal fire. Further, the study highlighted on the capability of the methodology for predicting potential coal fire zones on the basis of land surface subsidence only. The results from this study have major implications for demarcating the hazardous coal fire areas as well as effective implementation of public safety measures. 1. Introduction with coal fires add to the growing concern of haz- ardous impact on the masses residing in the study Accounting for nearly 70% of India’s energy pro- area. Thus the monitoring of coal fires, because of duction, coal remains a key contributor to the its socio-economic importance and environmental economic development of the country. The Jharia impacts, present an interesting challenge to scien- coalfield of eastern India is the primary producer tists and policy-makers alike. Concerns over the of high grade coking coal, which is a critical com- degrading health and safety of the local popula- ponent of India’s major steel industry. However, tion justify a detailed assessment of the extent in spite of its economic importance, Jharia coal- and direction of propagation of coal fires. Such field has been burning underground for nearly a an assessment will also contribute towards the century and hosts the maximum number of uncon- identification and implementation of the essential trollable surface and subsurface coal fires in India preventive measures. (Chatterjee et al. 2006). Jharia coal fires lead Previously, Bhattacharya et al. (1991)and to considerable loss of valuable, non-renewable, Mukherjee et al. (1991) utilized airborne thermal reserve of prime coking coal in addition to hav- data for the identification of coal fires and their ing adverse effects on the regional environment depth of occurrence, in the Jharia coalfield, using (Chatterjee 2006). Land subsidence associated linear heat flow equation. The efficacy of thermal Keywords. Coal fire; Jharia coalfield; DInSAR; thermal remote sensing. J. Earth Syst. Sci. 122, No. 5, October 2013, pp. 1249–1258 c Indian Academy of Sciences 1249 1250 Nishant Gupta et al. data from spaceborne Landsat-5 Thematic Map- (Wegmuller et al. 1999; Tom´as et al. 2005). How- per (TM) for the detection of coal fires in the ever, the DInSAR technique is limited by the fact Jharia coalfield was first established by Reddy et al. that it does not provide statistics of deformation (1993) and Saraf et al. (1995). Then on, Thermal rate at individual points within the interferogram Infra-Red (TIR) and Short Wavelength Infra-Red as is the case with the recently developed Persis- (SWIR) bands of Landsat-5 TM have been effec- tent Scatterer InSAR (PSInSAR) technique. The tively used to identify surface and subsurface coal PSInSAR technique allows highly accurate mea- fires (Prakash et al. 1997) and to calculate the sub- surements of deformation that occurs at individual, pixel area and temperature (Prakash and Gupta phase-dependent radar targets called permanent or 1999). In order to differentiate between surface and persistent scatterers (PS) (Jiang et al. 2011). subsurface coal fires and to study its lateral prop- Previously, DInSAR technique has been exten- agation, Chatterjee (2006) implemented the tech- sively used for analysing temporal and spatial nique of pixel integrated temperature modelling on characteristics of land subsidence due to various Landsat TM thermal IR images. Additional coal geophysical phenomena (e.g., Carnec et al. 1996; fire studies utilizing thermal bands were carried Galloway et al. 1998; Amelung et al. 1999; out by Chatterjee et al. (2007) (using images from Chatterjee et al. 2006). In the recent past, DIn- Landsat-5 TM and Landsat-7 ETM+), Gautam SAR technique has been used for the assessment of et al. (2008) (using NOAA/AVHRR) and Martha land subsidence caused by mining activities (e.g., et al. (2010) (using images from ASTER). Most Colesanti et al. 2005; Herrera et al. 2007; Jung recently, Mishra et al. (2011), empirically, esti- et al. 2007). While Prakash et al. (2001)andVoigt mated a scaled variation between the temperature et al. (2004) devised an integrated approach with of surface and subsurface coal fires obtained from the combination of optical, thermal and microwave the thermal band of Landsat ETM+ data and data, Jiang et al. (2011) utilized advanced InSAR in situ temperature observations using thermal techniques to study coal fires. The current study imaging camera. presents the most recent and comprehensive assess- In the past, Synthetic Aperture Radar (SAR) ment of land surface subsidence caused by coal fire interferometry (InSAR) has been effectively utilized in the Jharia coalfield of India. The methodology to monitor subsidence caused by various natu- involved the implementation of repeat pass DIn- ral and anthropogenic factors (such as earthquake SAR to make precise measurements of vertical land (e.g., Pathier et al. 2006), mining activities (e.g., subsidence primarily attributed to underlying coal Herrera et al. 2007) and groundwater withdrawal fires. Here we validated the DInSAR-based subsi- (e.g., Motagh et al. 2008)). This technique presents dence measurements with independent results from a method to obtain highly precise measurements thermal imagery and in situ observations. The of surface displacement, most prominently in the study, further hypothesized that areas with dis- vertical direction. InSAR involves the computa- cernible vertical subsidence but without any ther- tion of an interferogram using SAR image pairs mal signature or in situ sighting of coal fire are of the same area acquired at different times. In potentially hazardous zones with high probability this study an advanced InSAR technique based on of subsurface coal fire occurrence. small perpendicular and temporal baseline, two- pass Differential Interferometric SAR (DInSAR) was used. DInSAR provides information on two- 2. Study area dimensional deformation in the line of sight (LOS) of radar by calculating a differential interferogram Jharia coalfield, one of the leading coal producing for the image pair acquired during repeat pass of belts in India, is bounded by the latitudes 23◦39– the radar over the same area at different times 23◦50N and longitudes 86◦05–86◦30E and located (Massonnet and Feigl 1998). DInSAR provides within the state of Jharkhand (figure 1a). The a cost effective way of obtaining information on sickle shaped coalfield (figure 1b) contains the only two-dimensional deformation, with wide and con- remaining reserve of prime coking coal in India and tinuous spatial coverage, when compared to Dif- occupies an area of approximately 450 km2.Major ferential Global Positioning System (DGPS) and portions of this coalfield is operated by Bharat other instrumental methods, which are only able Coking Coal Limited (BCCL 2008). Geologically to measure ground deformation at discrete points. the rocks of the study area, belonging to the While the spatial coverage of levelling techniques Gondwana Supergroup, range in age from Upper is comparable to that of DInSAR, the bench- Carboniferous to Lower Cretaceous age, lie uncon- mark density is significantly lower than that formably over the older Archaean rocks. In Jharia of DInSAR. Apart from being cost intensive, coalfield, the major coal bearing formation is the levelling surveys are significantly constrained in Barakar Formation consisting of bands of coarse- both space and time when compared to DInSAR to-medium grey and white sandstones, shales and Monitoring subsurface coal fires in Jharia coalfield 1251 70°0'0"E 75°0'0"E 80°0'0"E 85°0'0"E 90°0'0"E 35°0'0"N 35°0'0"N 30°0'0"N 30°0'0"N 25°0'0"N 25°0'0"N (a) 70°0'0"E 75°0'0"E 80°0'0"E 85°0'0"E 90°0'0"E (b) Figure 1. (a) Location map of Jharia coalfield in the overall Indian perspective. (b) Magnified view of the study area represented by a false colour composite (FCC) illustrating the Jharia coalfield with some of the major collieries affected by coal fires. 1252 Nishant Gupta et al. coal seams. Tectonically, this area consists of NE– two SAR images with similar imaging geome- SW-trending faults with exposures of lamprophyre tries, acquired at different times, for the same and dolerite dykes in a criss-cross manner (Saraf area. These two images are precisely coregistered et al. 1995). Figure 1(b) shows a false colour com- before the phase difference is computed for each posite (FCC) image of the study area prepared pixel. Interferograms used in this study were pro- using Landsat ETM+ bands 7, 5 and 3 (RGB). duced using the Repeat Orbit Interferometry Pack- The FCC (figure 1b) prepared shows coal bands age (ROI PAC), which was developed at Jet and coal dumps in the shades of brown to brownish Propulsion Laboratory and the California Insti- black colour.