Coal fire identification through satellite remote sensing considering the landscapes
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摘要:
我国矿区煤火问题严重，已成为破坏区域环境和能源安全的重大威胁。及时、准确地掌握煤火分布范围，厘清其时空演化规律，对于煤火区控制和治理具有重要意义。提出了一种顾及地表覆被差异的卫星遥感煤火识别方法。首先，以Landsat卫星影像为基础，利用辐射传导方程法进行大气校正，反演绝对地表温度；其次，采用支持向量机的监督分类方法，获取地表土地覆被类型，并以此为约束确定煤火热异常区域；最后，采用回归分析方法推演煤火时空分布特征，构建煤火预测模型。选取内蒙古自治区乌海市为研究区，以2018—2023年的Landsat-8/9时序卫星影像为数据源，开展煤火异常区识别和预测试验。结果表明：本文所提方法对煤火识别结果与实地核实和低空监测结果一致，预测煤火区域与卫星反演结果一致，印证了本文方法对大区域煤火“扫靶式”识别的可靠性，为矿区煤火及时发现、时空演化规律分析及修复治理提供了可靠的技术支持。
Abstract:Coal fire is a serious problem in China’s mining areas, which has become a major threat to regional environment and energy security. The timely and accurate grasp of the distribution range of coal fires and the clarification of their spatiotemporal evolution law are crucial for effective control and management in coal fire areas. In this paper, a coal fire identification method based on satellite remote sensing considering the difference of land cover is proposed. Firstly, based on Landsat satellite images, the atmospheric correction was carried out using the radiative conduction equation method to invert the absolute surface temperature. Secondly, the supervised classification method of support vector machine is used to obtain the land cover type and determine the abnormal region of coal fire. Finally, the distribution characteristics of coal fire in time and space are deduced by regression analysis method, and the coal fire prediction model is constructed. Wuhai City, Inner Mongolia Autonomous Region is selected as the research area, and the Landsat time series satellite images from 2018—2023 are used as the data source to carry out the coal fire anomaly identification and prediction experiment. The results show that the coal fire identification results of the proposed method are consistent with the field verification and low-level monitoring results, and the predicted region and coal fire degree are consistent with the satellite inversion results, which confirms the reliability of the proposed method for the “sweep target” identification of coal fires in large areas, and provides reliable technical support for the timely discovery of coal fires in mining areas, the analysis of space-time evolution laws, and the restoration and treatment of coal fires.
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图 1 乌海市试验区矿产资源分布
Figure 1. Mineral resources distribution map of experimental area of Wuhai City
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图 2 顾及地表覆被差异的卫星遥感煤火识别技术路线
注：归一化植被指数（Normalized Differnce Vegetation Index, NDVI）;植被覆盖度（Fractional Vegetation Cover, FVC）;地表温度（Land Surface Temperature, LST）
Figure 2. Technical route of coal fire identification by satellite remote sensing considering land cover difference
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图 3 2018—2023年乌海市地表绝对温度遥感反演结果
Figure 3. Absolute surface temperature remote sensing inversion results for Wuhai City from 2018 to 2023
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图 4 2018—2023年乌海市地表相对温度
Figure 4. Relative surface temperature in Wuhai City from 2018 to 2023
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图 5 2018—2023年乌海市高温异常区范围（叠加到卫星影像）
Figure 5. Range of high temperature anomalies in Wuhai City from 2018 to 2023 (superimposed on the landsat images)
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图 6 2018—2023年乌海市高温异常区范围（叠加到行政区划图）
Figure 6. Range of high temperature anomalies in Wuhai City from 2018 to 2023 (Superimposed on the administrative territorial map)
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图 8 剔除地类影响因素后2018—2023年乌海市煤火识别结果（叠加到卫星影像）
Figure 8. Results of coal fire identification in Wuhai City from 2018 to 2023 , after removing the Earth-type influencing factors(superimposed on landsat images)
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图 9 剔除地类影响因素后2018—2023年乌海市煤火识别结果（叠加到行政区划图）
Figure 9. Results of distribution of coal fire anomalies in administrative division of Wuhai City from 2018 to 2023, after excluding influence of land type (Superimposed on administrative territorial map)
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图 10 基于低空热红外遥感的矿区级卫星遥感煤火反演结果验证
Figure 10. Verification of coal fire inversion results achieved by Landsat images using the low altitude thermal infrared remote sensing as reference
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图 11 2023年1—10月乌达区煤火异常区分布
Figure 11. Distribution map of coal fire anomaly in Wuda District from January 2023 to October 2023
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图 12 乌达区煤火预测与遥感反演结果对比
Figure 12. Comparison of coal fire results achieved by regression forecasting and Landsat image identification in Wuda District
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图 13 2023年1—10月苏海图矿区煤火异常区分布
Figure 13. Distribution map of coal fire anomaly in Suhaitu mining area from January 2023 to October 2023
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图 14 苏海图煤火范围识别结果对比
Figure 14. Comparison of coal fire results achieved by regression forecasting and Landsat image identification in Suhaitu mining area
表 1 卫星数据
Table 1 Satellite data
日期 卫星 2023−01−26 Landsat8 2023−02−19 Landsat9 2023−03−31 Landsat8 2023−04−16 Landsat8 2023−05−18 Landsat8 2023−06−19 Landsat8 2023−07−05 Landsat8 2023−08−30 Landsat9 2023−09−15 Landsat9 2023−10−09 Landsat8 
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