Abstract
Surface and sub-surface coal seam fires are detected by estimating Land Surface Temperature (LST). The LST of an area depends on several factors such as, seasonal variation, nature of soil, urban settlements, etc. Temperatures of several areas of Dhanbad region of Eastern India are affected by the presence of surface and sub-surface coal seam fires. Coal seam fire detection has several challenges. Specially in summer season, thermal anomalies provide false classifications of such fires. It has been observed that during summer season, water bodies have high temperatures, and thus affecting the performance of detection of fires. This paper proposes a novel method to detect surface and subsurface fires in summer from satellite data by removing the high temperature water bodies.
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Notes
- 1.
Recall is defined as \(t_p/(t_p+f_n\)) where \(t_p\), and \(f_n\) are true positives, and false negatives, respectively.
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Mukherjee, J., Mukherjee, J., Chakravarty, D. (2018). Detection of Coal Seam Fires in Summer Seasons from Landsat 8 OLI/TIRS in Dhanbad. In: Rameshan, R., Arora, C., Dutta Roy, S. (eds) Computer Vision, Pattern Recognition, Image Processing, and Graphics. NCVPRIPG 2017. Communications in Computer and Information Science, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-0020-2_46
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