A time series decomposition approach to detect coal fires in parts of the Gondwana coalfields of India from VIIRS data

This paper proposes an algorithm to detect coal fires using time-series Land Surface Temperature (LST) maps generated from data acquired by a wide-swath Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensor. VIIRS provides remotely sensed thermal images daily during daytime and nighttime. The proposed algorithm primarily uses the trend component extracted at pixel level from time-series LST maps by using the Seasonal Trend decomposition based on Loess (STL) model. The proposed algorithm is suitable for detecting coal fires at the regional scale. The obtained results were validated with coal fire observations collected during a field survey.