大柳塔矿区煤火高光谱热红外定量探测研究

Coalfield fire quantitative detection in Daliuta mining area based on hyperspectral thermal infrared remote sensing

为了准确提取内蒙古大柳塔矿区煤火燃烧范围,基于夜间TASI航空热红外高光谱遥感数据,采用发射率归一化方法和地表同步测温数据建立空-地回归方程反演地表温度,选择合理的阈值提取煤火热异常范围。在此基础上,利用Modtran4模拟大气上行、下行辐射和透过率,并结合反演的地表温度解算地物发射率,利用地物自身发射率光谱上的特性差异,将电厂温排水、热厂房和烟囱等非煤火热异常从煤火热异常中分离,排除了干扰因素对提取地下煤火燃烧异常区范围的影响。结果表明,TASI数据1～16波段（8054.8～9679.3nm）适合煤火热红外温度反演,反演的地表温度精度满足定量探测研究,提取的煤火燃烧热异常范围准确,能够为矿区煤田灭火提供一定的决策支持。

In order to accurately extract the coal fire range in Daliuta mining area,based on night aerial thermal infrared hyperspectral remote sensing data（ TASI）, emissivity normalization method and ground synchronous temperature measurement data were adopted to establish a space-to-ground regression equation for retrieving land surface temperature.The coal fire range was extracted by the reasonable threshold. MODTRAN4 code was used to estimate the upward and downward radiation and transmission of the atmosphere. On this basis,the non-hot anomaly were separated from the area of coal heat anomaly,such as the cooling water of power plant,heat buildings,chimney,according to the difference of the emissivity spectrum characteristics. The interfering factors were eliminated on the accurate extraction of the coal fires burning effect of anomaly area. The results show that the 1 ～ 16 bands of TASI are suitable for infrared temperature inversion for the coalfield fire. The inversion precision of the surface temperature meets the study on quantitative detection,and the accurate extraction can provide support for underground coal fire extinguishing.