The use of the NDVI, NDSI, and NDSII indices and thermal maps, combined with Landsat TM, ETM+, ASTER, and Sentinel 2 images, can help to identify and localize self-heating sites in coal-waste dumps. Nighttime images can show hot spots with high intensity as in the Makoszowy dump, for example. The advantages of the methods described here are that the satellite images used are freely available, and that they localize the hot spots by drawing information from large areas. Though the method does not require it, field temperature measurements provide a useful validation. However, several disadvantages are apparent; for example, snow-cover or nighttime images are not always available due to atmospheric disturbances and technical problems with the Landsat ETM+. The distribution and amount of snow can significantly influence the perceived location of hot spots. Furthermore, self-heating sites of small spatial extent are often difficult to detect as they are too small in relation to the pixel size of the thermal data. Finally, the detection of hot spots with low thermal intensity in shallow locations, and those on steep slopes, can be problematic, due to the limitations of the thermal sensor. As these types of hot spots commonly provide smooth values, attempts to distinguish these anomalies from the surrounding pixel values, and solar effects, can give misleading results.
The method has potential for monitoring coal-waste dumps in USCB, and wherever similar self-heating problems exist. In the future, drones with thermal infrared cameras will likely replace the more expensive aircraft and alleviate detector sensitivity problems.