Abstract Medium-resolution Landsat5 TM (thematic Mapper) and Landsat7 ETM+ (Enhanced thematic Mapper) satellite data were used to investigate multitemporal land-cover changes in the Wuda and Ruqigou-Gulaben coal basins of China between 1987 and 2002. The surficial distribution of coal as detected by remote sensing may be an important indicator of mining activity. Coal that is exposed on the surface may appear as seams in openpit mines; the coal also may occur in storage and waste piles, as refuse at the entrance to a mine, or as coal dust covering areas adjacent to the exposed coal. Because both coal basins are affected by coal fires, monitoring surficial features, including the expansion of coal, is crucial for evaluating the risk for a coal fire. This risk increases where new, often private, mines develop. Remote-sensing data reveal that the increasing number of exposures of coal in the Wuda and Ruqigou-Gulaben coal basins between 1987 and 2002 is correlative with an increase in mining activity there and the associated surficial coal dust adjacent to mining-transport networks. The data also reveal an increase in small-scale private coal mines, especially in the eastern part of the Wuda Coalfield. Such mines often suffer from inadequate mining and environmental regulations and are at high risk for coal fires. Satellite-based detection and in situ verification of new coal fires during field campaigns in 2003 and 2005 confirmed that land-cover analysis is useful for the identification of potential locations for coal fires. The changes that were observed in all other land cover in the Wuda and Ruqigou-Gulaben coal basins represent the more general dominant spatial dynamics in the two regions.

Abstract Remote-sensing imagery is often used for detecting and monitoring coal fires. The Landsat7 Enhanced thematic Mapper Plus (ETM+) sensor and its predecessors of the Landsat family were frequently utilized for that purpose. With Landsat5 quickly approaching the end of its lifetime and the partial malfunction of Landsat7 in 2003, other potential sensors, including Moderate Resolution Imaging Spectrora-diometer (MODIS), merit investigation. One kilometer MODIS data were successfully acquired and analyzed to detect coal fires in China during one summer and two winter night scenes. Band ratios of MODIS bands 20/32 enhanced subpixel-sized hot spots over background values, and an automated thermal anomaly algorithm was an asset in extracting potential coal-fire locations. for areas with known subsurface fires, between 0% and 17% were correctly detected in the three images. Areas with surface fires had success rates of 42% to 49%. These results indicate that MODIS is potentially useful for monitoring large areas for newly developing surface coal fires. Most subsurface coal fires, however, remain undetected.