Spontaneous combustion of subsurface coal seams poses a serious threat to nonrenewable resources. Additionally it jeopardizes the integrity of the environment to a large extent. Furthermore, the voids created by the subsurface coal fire result in land subsidence and deformation, forexample, the devastating land subsidence in Jharia coal mines has been occurring since decades. An essential prerequisite for both the management and prevention of coalfield fires and the utilization of geothermal energy resources is accurate and efficient monitoring of subsurface coal fire activities. Early detection of hidden coal fires requires the collection and analytical evaluation of distribution data for factors which are inherently related to coal combustion activities. In this line, the land surface temperature estimation using thermal bands of satellite data would be considered a boon since the conventional methods of coal fire detection are quite a time-consuming and risky phenomenon. The spontaneous combustion would lead to the rise of ambient temperature that can be pretty accurately measured by the land surface temperature. Thus, the present study highlights the retrieval of the land surface temperature using the OLI and TIR bands of Landsat 8 data for the same month of two different years such as 2013 and 2017 for Chirimiri coal mines of Korea district in Chhattisgarh. The density sliced result produced has clearly depicted presence and extent of coal fire that has been burning for the last decade.