A Research on Coalfield Fire Detection in Daliuta Mining Area at Inner Mongolia Based on Hyperspectral Thermal Infrared Remote Sensing

摘要

Daliuta mining coal fires at Inner Mongolia were not reported at present in remote sensing. However, they still pose a serious threat to the surroundings. In order to extract combustion range of the coal mine, we used the wintertime thermal airborne infrared hyperspectral images of TASI acquired in 2016 to detect the coal fire of Daliuta mining. The synchronous in situ measured temperature was used to establish space-to-ground regression equation with the image temperature for retrieving land surface temperature. Extracted coal fire through the reasonable threshold by the processed image data, identified a region where the surface temperatures was -0.5 °C to 300 °C. MODTRAN4 code was used to estimate the upward and downward radiation and transmission of the atmosphere. On this basis, the non-coal fire anomaly areas, such as the cooling water of power plant, heat buildings, chimney, were separated from the coal fire heat anomaly areas by the characteristic difference of the emissivity spectrum in the objectives. The results show that the bands 1-16 of TASI are suitable for infrared inversion temperature for the coalfield fire. There was a linear relationship between synchronous in situ observation temperature and the image temperature, and the determination coefficient R2 was 0.9938. The extracted coal fire anomaly range is able to provide some decision support for underground coal fire extinguishing. A detailed fire map of shallow coal areas can help to prioritize fire fighting operations in order to avoid the chance of starting a new coal fire.