Abstract
Coal fires are common and serious phenomena in most coal-producing countries in the world. Coal fires not only burn valuable non-renewable coal reserves but also severely affect the local and global environment. The Rujigou coalfield in Shizuishan City, Ningxia, NW China, is well known for being a storehouse of anthracite coal. This coalfield is also known for having more coal fires than most other coalfields in China. In this study, an attempt was made to study the dynamics of coal fires in the Rujigou coalfield, from 2001 to 2007, using multi-temporal nighttime Landsat data. The multi-temporal nighttime short wave infrared (SWIR) data sets based on a fixed thresholding technique were used to detect and monitor the surface coal fires and the nighttime enhanced thematic mapper (ETM+) thermal infrared (TIR) data sets, based on a dynamic thresholding technique, were used to identify the thermal anomalies related to subsurface coal fires. By validating the coal fires identified in the nighttime satellite data and the coal fires extracted from daytime satellite data with the coal fire map (CFM) manufactured by field survey, we found that the results from the daytime satellite data had higher omission and commission errors than the results from the nighttime satellite data. Then, two aspects of coal fire dynamics were analyzed: first, a quantitative analysis of the spatial changes in the extent of coal fires was conducted and the results showed that, from 2001 to 2007, the spatial extent of coal fires increased greatly to an annual average area of 0.167 km2; second, the spreading direction and propagation of coal fires was analyzed and predicted from 2001 to 2007, and these results showed that the coal fires generally spread towards the north or northeast, but also spread in some places toward the east.
Highlights
Coal fires, called coal seam fires, are caused by the spontaneous combustion of coal during coal oxidation [1]
The dynamic thresholding technique, an automated method based on statistical parameters, was used to detect and monitor the subsurface coal fires based on the Landsat ETM+ thermal band 6 data because subsurface coal fires usually have lower temperatures than surface coal fires, and the fixed thresholding technique was developed to identify and monitor the surface coal fires based on the Landsat ETM+ short wave infrared (SWIR) band 7 images because the nighttime ETM+ SWIR data sets are insensitive to solar irradiance and have a broad sensitivity of
Using the dynamic thresholding technique, the relation of the thermal anomalies to subsurface coal fires was delineated using the land surface temperature (LST) retrieved from multi-temporal ETM+ thermal band 6 data (Figure 5)
Summary
Called coal seam fires, are caused by the spontaneous combustion of coal during coal oxidation [1]. Schmal et al (1985) noted that the potential of spontaneous combustion of coal may enhance its ability to react with oxygen at ambient temperatures [2]; at the same time, this reaction is exothermic because it is accompanied by the absorption of oxygen at the surface of the coal field, which may increase the “threshold” temperature, which is between 230 °C and 280 °C. At this temperature, coal reaches its “ignition” or “flash” point and starts to burn, resulting in a coal fire. Coal fires emit large amounts of greenhouse gases (GHGs) and toxic gases, including CO2, CH4, NOX, N2O, CO, and SO2, which cause severe environmental problems, e.g., land degradation, global warming, and air pollution [11,12,13,14]
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