煤火燃烧会对周围地区的环境、经济和安全造成严重影响，准确识别煤田自燃引起的火区范围对于监测与治理煤火具有重要意义。相关学者分别通过提取地表热异常或地表形变信息来识别煤火范围，但由于方法及手段单一，而引起煤火发生因素众多，导致试验结果不够准确。为提高煤火识别准确性，通过实际应用研究，利用融合卫星热红外技术与雷达技术的煤火识别方法，应用于山西省宁武煤田的火区识别。首先采用ASTER–TES(Temperature-Emissivity Separation)算法对ASTER夜间热红外数据进行地表温度反演，同时利用SBAS–InSAR(Small Baseline Subset InSAR)技术对Sentinel-1数据进行地表沉降信息反演，然后通过阈值分割法提取研究区域中的高温异常区域和沉降异常区域，进而融合处理，获得疑似煤田火区范围，最后利用测氡的实地勘测方法所确定的煤火范围对试验结果进行对比验证分析。结果显示：研究提出的方法对宁武煤田火区范围的识别准确率高达93.78%，较单一的温度反演方法与沉降异常方法提高43.29%和62.23%，但有部分火区未被识别，原因在于利用地表形变识别火区的阈值难以获取。结果表明:热红外技术与雷达技术协同识别方法能够有效克服单一识别方法的不足，显著提高煤火范围的识别精度，为准确圈定火区的治理范围提供有力参考，今后应深入研究地表形变探测火区的方法特性，从而获得更加全面准确的煤火范围。

Coal fire cause serious influence on environment, economy and safety of surrounding area. It is of great significance to accurately identify the scope of coal fire caused by spontaneous combustion in coal field for monitoring and controlling coal fire. Relevant scholars identified the scope of coal fire by extracting surface thermal anomaly or surface deformation information respectively, but due to the single method and means, there are many factors causing the occurrence of coal fire, so the experimental results are not accurate enough. In order to improve the accuracy of coal fire identification, the coal fire identification method combining satellite thermal infrared technology and radar technology is applied to the fire area identification of Ningwu Coalfield in Shanxi Province through practical application research. Firstly, the ASTER–TES(Temperature-Emissivity Separation) algorithm is used to retrieve land surface Temperature from ASTER thermal infrared data at night. At the same time, surface subsidence information is inverted using The Sentinel-1 data of SBAS–InSAR(Small Baseline Subset InSAR) technology, and then the abnormal high temperature area and abnormal settlement area in the study area are extracted by threshold segmentation method, and then the range of suspected coal field fire area is obtained by fusion processing. Finally, the experimental results are compared and verified by the coal fire range determined by the field survey method of measuring radon. The results show that the accuracy of the proposed method is as high as 93.78%, which is 43.29% and 62.23% higher than that of the single temperature inversion method and the settlement anomaly method. However, some fire zones have not been identified, mainly because it is difficult to obtain the threshold of identifying fire zones using surface deformation. The results show that the cooperative identification method of thermal infrared technology and radar technology can effectively overcome the deficiency of single identification method, significantly improve the identification accuracy of coal fire range, and provide a powerful reference for accurately determining the control range of fire area. In order to obtain more comprehensive and accurate range of coal fire, it is necessary to study the characteristics of surface deformation detection method in the future.