In this paper, the spatio-temporal variation and propagation direction of coal fire were studied in the Jharia Coalfield (JCF), India during 2006–2015 through satellite-based night-time land surface tempera-ture (LST) imaging. The LST was retrieved from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) night-time thermal-infrared data by a robust split-window algorithm based on scene-specific regression coefficients, band-specific hybrid emissivity, and night-time atmospheric trans-mittance. The LST-profile-based coal fire detection algorithm was formulated through statistical analysis of the LST values along multiple transects across diverse coal fire locations in the JCF in order to compute date-specific threshold temperatures for separating thermally-anomalous and background pixels. This algorithm efficiently separates surface fire, subsurface fire, and thermally-anomalous transitional pixels. During the observation period, it was noticed that the coal fire area increased significantly, which resulted from new coal fire at many places owing to extensive opencast-mining operations. It was observed that the fire propagation occurred primarily along the dip direction of the coal seams. At places, lateral-propagation of limited spatial extent was also observed along the strike direction possibly due to spatial continuity of the coal seams along strike. Moreover, the opencast-mining activities carried out during 2009–2015 and the structurally weak planes facilitated the fire propagation.