| The combustion of coal field fire area will produce a large number of harmful gases,which will endanger people’s life and health,and also cause surface cracks and collapse,which will have a certain impact on the local infrastructure,and cause serious environmental,economic and safety problems.Therefore,it is of great significance to accurately identify the area of spontaneous combustion in coal field for monitoring and controlling coal fire.Many scholars have studied coal fire identification,but the commonly used magnetic,geophysical and geochemical methods are not suitable for large areas of fire due to technical limitations and high cost.In recent years,remote sensing technology has been widely applied due to its advantages of large detection range,high efficiency and economy.However,the common temperature anomaly method and surface subsidence monitoring method have a single method and means,but there are many factors causing coal fire,so the experimental results are not accurate enough.In this paper,the method of coal fire identification combining satellite thermal infrared remote sensing and radar remote sensing is applied to the identification of fire area in Ningwu coal field,Shanxi Province for the first time.Firstly,two temperature inversion algorithms,ASTER-TES and ADE-TES,were implemented based on ASTER night thermal infrared data and IDL,the secondary development platform of ENVI.The results of the two were compared and verified and the accuracy was analyzed.The range of temperature thermal anomaly was extracted by a certain threshold.Secondly,based on Sentinel-1A data,the SBAS-InSAR technology and PS-InSAR technology are implemented using SARscape module.The surface deformation of the study area is analyzed by time-series subsidence map,and then the abnormal subsidence area is obtained.Thirdly,the extracted temperature anomaly and settlement anomaly data are fused to obtain the range of suspected coal fire area.Finally,the actual coal fire range determined by the radon value of field survey is used to verify and analyze the research results.The main conclusions of this study are as follows:1)The results of the two temperature inversion algorithms ASTER-TES and ADE-TES show high consistency.The linear coefficient of random sampling is 1.019 and the correlation coefficient is 0.99718,indicating that the results of the two algorithms are highly correlated.2)Through the SBAS-InSAR technology and PS-InSAR technique comparison for the surface subsidence information,both in urban areas are showed,which is caused by human activities more,and in the study area of southwest to the northeast are continuous subsidence phenomenon,As the mining area in this location has been completed for a long time,the analysis is suspected to be the result of coal fire combustion and randomly selected as 10 points within the study area,Draw and analyze historical settlement curves.3)The verification of measured coal fire data shows that there are some defects in identifying coal fire area only using temperature information and settlement information.Due to the heat absorption of sandstone and other ground objects and the heat island effect in urban areas,the abnormal temperature range unrelated to coal fire can be extracted.In addition,surface subsidence caused by mining will also affect the accuracy of coal fire extraction using subsidence information.4)The fusion of temperature and settlement information significantly improves the accuracy of coal fire identification.The identification accuracy of this method for ningwu coalfield fire area is as high as 93.78%,43.29% and 62.23% higher than that of the single temperature anomaly method and settlement anomaly method.The combination of thermal infrared remote sensing technology and temporal InSAR technology to extract coal field fire area overcomes the defects of single remote sensing technology and gives full play to the advantages of remote sensing technology.It provides a powerful reference for accurately delineating the control scope of coal field fire area. |
