 Abstract: Coal fires, also known as subsurface fires or hot spots are all-inclusive issues in coal mines everywhere throughout the globe. Aimless mining over a period of past 100 years has prompted large scale damages to the ecosystem of the earth. For example, debasement in nature of water, soil, air, vegetation dissemination and variations in land topography have caused degradation. Research is needed to be more attentive on developing the prospective use of the satellite image analysis for hot spot detection because ground-based hot spots monitoring is time-taking, complex, cumbrous and very expensive. In this paper, a two-stage model has been developed to extract the hot spot delineated boundaries in Jharia coal field (JCF) region. In the first stage, contextual thresholding (CT) technique has been used to classify the hot spot and non-hot spot regions. After thorough processing, hot spots regions have been retrieved and for performance evaluation sensitivity and specificity are calculated, which suggest that hot spots were detected accurately in successful and efficient way. In second stage, the Canny edge detection algorithm is applied to detect the edges of the hot spot regions and then the binary image is generated, which is later converted into a vector image. Finally Hough transform is implemented on the obtained vector images for delineating hot spot boundaries. In future, delineated hot spot boundaries may be used to obtain the expansion or shrinking information of hot spot regions and it can be used for area estimation also. . His research interests include digital imageprocessing, optical and microwave satellite image processing, image classification, data fusion, time series analysis, and SAR data analysis for land cover classification.Mohammad Usama received his M. Sc.