Xinjiang in China is one of the areas worst affected by coal fires.Coal fires cannot only waste a large amount of natural resources and cause serious economic losses,but they also cause huge damage to the atmosphere,t...Xinjiang in China is one of the areas worst affected by coal fires.Coal fires cannot only waste a large amount of natural resources and cause serious economic losses,but they also cause huge damage to the atmosphere,the soil,the surrounding geology,and the environment.Therefore,there is an urgent need to effectively explore remote sensing based detection of coal fires for timely understanding of their latest development trend.In this study,in order to investigate the distribution of coal fires in an accurate and reliable manner,we exploited both Landsat-8 optical data and Sentinel-1A synthetic aperture radar(SAR)images,using the generalized single-channel algorithm and the InSAR time-series analysis approach,respectively,for coal fire detection in the southern part of the Fukang region of Xinjiang,China.The generalized single-channel algorithm was used for land surface temperature information extraction.Meanwhile,the timeseries InSAR analysis technology was employed for estimating the surface micro deformation information,which was then used for building a band-pass filter.The suspected coal fire locations could then be established by a band-pass filtering operation on the obtained surface temperature map.Finally,the locations of the suspected coal fires were validated by the use of field survey data.The results indicate that the integration of thermal infrared remote sensing and radar interferometry technologies is an efficient investigation approach for coal fire detection in a large-scale region,which would provide the necessary spatial information support for the survey and control of coal fires.展开更多
目前基于能量枢纽(energy hub,EH)的区域综合能源系统的优化运行缺乏对EH内热电联产(combined heat and power,CHP)机组热电比可调的考虑,且在此类场景中参与需求侧响应的负荷种类单一。针对此状况,构建双层优化模型,建立EH机组内部能...目前基于能量枢纽(energy hub,EH)的区域综合能源系统的优化运行缺乏对EH内热电联产(combined heat and power,CHP)机组热电比可调的考虑,且在此类场景中参与需求侧响应的负荷种类单一。针对此状况,构建双层优化模型,建立EH机组内部能效特性与外部能源分配的联系,实现内部机组高效运行和外部能源经济分配。模型通过卡罗需-库恩-塔克条件(Karush-Kuhn-Tucker Conditions,KKT)将双层优化转换为单层优化,并用确定性优化软件求解。算例结果表明,EH双层优化运行模型可减少用能成本,提高用能效率。通过调节CHP热电比,同时利用广义弹性负荷参与响应,可以减小CHP热电比与区域内热电负荷比之间差距,从而提高CHP供能比例,实现区域综合能源系统高效经济运行。展开更多
基金This work was supported by the National Natural Science Foundation of China(No.41874044)the Jiangsu Province Foundation of Brand Specialty Construction Projects in College and University(No.PPZY2015B144).The authors also gratefully acknowledge the European Space Agency for providing the Sentinel-1A SAR data and the US Geological Survey for providing the Landsat-8 data and the DEM data.The authors would also like to thank NASA for the auxiliary atmospheric data.
文摘Xinjiang in China is one of the areas worst affected by coal fires.Coal fires cannot only waste a large amount of natural resources and cause serious economic losses,but they also cause huge damage to the atmosphere,the soil,the surrounding geology,and the environment.Therefore,there is an urgent need to effectively explore remote sensing based detection of coal fires for timely understanding of their latest development trend.In this study,in order to investigate the distribution of coal fires in an accurate and reliable manner,we exploited both Landsat-8 optical data and Sentinel-1A synthetic aperture radar(SAR)images,using the generalized single-channel algorithm and the InSAR time-series analysis approach,respectively,for coal fire detection in the southern part of the Fukang region of Xinjiang,China.The generalized single-channel algorithm was used for land surface temperature information extraction.Meanwhile,the timeseries InSAR analysis technology was employed for estimating the surface micro deformation information,which was then used for building a band-pass filter.The suspected coal fire locations could then be established by a band-pass filtering operation on the obtained surface temperature map.Finally,the locations of the suspected coal fires were validated by the use of field survey data.The results indicate that the integration of thermal infrared remote sensing and radar interferometry technologies is an efficient investigation approach for coal fire detection in a large-scale region,which would provide the necessary spatial information support for the survey and control of coal fires.
