Jitendra Pandey - Mine Fire Research Group, CSIR – Central Institute of Mining and Fuel Research, Dhanbad, India
Dheeraj Kumar - Department of Mining Engineering, Indian Institute of Technology (ISM), Dhanbad, India
Sumit Chaudhari - Department of Environmental Engineering, Indian Institute of Technology (BHU), Varansai, India
Ajay Khalkho - Mine Fire Research Group, CSIR – Central Institute of Mining and Fuel Research, Dhanbad, India
Jai Pandey - Mine Fire Research Group, CSIR – Central Institute of Mining and Fuel Research, Dhanbad, India

Detection and mapping of the Jharia coal mine fire through the integration of satellite-based observed data with ground thermography data have been used and described in this work. This assimilation has been achieved using three types of data set viz., Landsat satellite images, topographical area map, and ground temperature survey of different fire-affected sites of Jharia Coalfields (JCF). Thermal anomaly, as observed from the satellite imagery, is one of the most important characteristics of the coal fire detection process. It has been used as a prime indicator for the fire area's extent and intensity. Ground thermographic measurement has also been conducted to further substantiate the thermal anomaly. The obtained amalgamated data is plotted on topographical maps of different sites of JCF. The study reveals that around ۷۰% of the total coal mines of JCF are in grip of either surface fire or sub-surface fire or both surface and sub-surface fire. About ۹۳% of fires detected in the year ۱۹۸۸ were shifted to new locations or in a dormant condition, whereas the remaining about ۷% of fires were still burning at the same locations mostly due to the shifting of these fires from the upper coal seam to the lower coal seam or vice versa. The temperature detected by satellite data was ۱۰ to ۱۵ times lower than the actual fire condition measured on the ground during field observation. The study concludes that the detection of several years long-standing fire conditions historical satellite data will be the best option to delineate the fire condition.

Coal Mine Fire, remote sensing, Thermal Data, Thermography and Fire Dynamics