Estimating the depth of underground coal fires using data integration techniques

Abstract

Underground coal fires in China cause serious environmental problems, in addition to the loss of valuable coal resources. The present study aims at developing a quick and practical method to estimate the depth of coal fires using data integration techniques. In coal fields which have underground coal fires, the subsurface fires are associated with surface thermal anomalies. Airborne thermal infrared scanner data and colour infrared photographs were used in this study to depict the coal fire front and the outcrop of coal seams, respectively. A Digital Elevation Model (DEM) of the study area was produced from topographic maps at 1:25 000 scale. Finally, taking into account the spreading direction of the coal fires and the relationships between thermal anomalies, relief factors and the occurrence of coal seams, the depths of the coal fires were obtained automatically by means of integration of remote sensing data and GIS techniques. This helped to target the fire fighting operations and made them more cost effective.