自适应边缘阈值法的煤火探测研究
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摘要
为了探测内蒙古乌达煤田的煤火位置,针对国产CBERS-04卫星的热红外波段提出一种自适应边缘阈值算法。该算法通过高斯滤波算法过滤热图像噪声,利用Sobel算子和提取的高温区域生成高温边缘,将高温边缘像素温度值的平均值作为温度分割阈值识别并提取煤火区。通过外业调查的火区验证提取的火区,发现二者的位置重叠度高达81.3%。对比同一日夜晚ASTER卫星和CBERS-04卫星所提取火区发现二者的位置重叠度为81.0%。这些结果均表明自适应边缘阈值煤火识别算法具有较高的煤火识别精度。
In order to detect positions of coal fires in Wuda coal field,Inner Mongolia,an adaptive-edge threshold algorithm(AETA)is proposed aiming at the thermal infrared band from domestic CBERS-04 remote sensing satellite.AETA first filters the noises of an image using Gaussian filter algorithm,generates high-temperature edge combined Sobel operator with extracted high-temperature regions,averages the pixel values located in high-temperature edge,and applies this mean of temperatures as temperature-segmented threshold to identify and extract coal fire areas.By comparing field-investigated fire areas with extracted fire areas,we find that the overlap ratio of both areas reaches 81.3%.Additionally,the two fire areas recognized by ASTER satellite and CBERS-04 satellite at night on the same day show the overlap ratio of both fire areas is 81.0%.These results demonstrate that AETA algorithm can provide the higher precision for coal fires detection.
In order to detect positions of coal fires in Wuda coal field,Inner Mongolia,an adaptive-edge threshold algorithm(AETA)is proposed aiming at the thermal infrared band from domestic CBERS-04 remote sensing satellite.AETA first filters the noises of an image using Gaussian filter algorithm,generates high-temperature edge combined Sobel operator with extracted high-temperature regions,averages the pixel values located in high-temperature edge,and applies this mean of temperatures as temperature-segmented threshold to identify and extract coal fire areas.By comparing field-investigated fire areas with extracted fire areas,we find that the overlap ratio of both areas reaches 81.3%.Additionally,the two fire areas recognized by ASTER satellite and CBERS-04 satellite at night on the same day show the overlap ratio of both fire areas is 81.0%.These results demonstrate that AETA algorithm can provide the higher precision for coal fires detection.
引文
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[3] SHAO Z,WANG D,WANG Y,et al.Theory and application of magnetic and self-potential methods in the detection of the Heshituoluogai coal fire,China[J].Journal of Applied Geophysics,2014,4(1):64-74.
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[5]李峰,梁汉东,赵小平,等.内蒙古乌达煤田煤火治理效果的遥感监测与评估[J].国土资源遥感,2017,29(3):217-223.LI Feng,LIANG Handong,ZHAO Xiaoping,et al.Remote sensing monitoring and assessment of fire-fighting effects in Wuda coal field,Inner Mongolia[J].Remote Sensing for Land and Resources,2017,29(3):217-223.
[6] ZHOU L,ZHANG D,WANG J,et al.Mapping land subsidence related to underground coal fires in the Wuda coalfield(Northern China)using a small stack of ALOS PALSAR differential interferograms[J].Remote Sensing,2013,5(3):1152-1176.
[7] LI F,YANG W,LIU X,et al.Using high-resolution UAVborne thermal infrared imagery to detect coal fires in Majiliang mine,Datong coalfield,Northern China[J].Remote Sensing Letters,2018,9(1):71-80.
[8]李峰,梁汉东,王哲,等.矿区煤火遥感监测技术的研究进展[J].煤矿安全,2016,47(12):191-198.LI Feng,LIANG Handong,WANG Zhe,et al.Coal fire in coal mine research progress based on remote sensing monitoring technologies[J].Safety in Coal Mines,2016,47(12):191-198.
[9] DU X,CAO D,MISHRA D,et al.Self-adaptive gradientbased thresholding method for coal fire detection using ASTER thermal infrared data,Part I;MethodoLogy and Decadal Change Detection[J].Remote Sensing,2015,7(6):6576-6610.
[10] JIANG W,JIA K,CHEN Z,et al.Using spatiotemporal remote sensing data to assess the status and effectiveness of the underground coal fire suppression efforts during 2000-2015in Wuda,China[J].Journal of Cleaner Production,2017,142:565-577.
[11]杨国防,赵英俊,田新光,等.大柳塔矿区煤火高光谱热红外定量探测研究[J].煤炭工程,2016,48(12):103-106.YANG Guofang,ZHAO Yingjun,TIAN Xinguang,et al.Coalfield fire quantitative detection in Daliuta mining area based on hyperspectral thermal infrared remote sensing[J].Coal Engineering,2016,48(12):103-106.
[12] HUO H,NI Z,GAO C,et al.A study of coal fire propagation with remotely sensed thermal infrared data[J].Remote Sensing,2015,7(3):3088-3113.
[13] KUENZER C,ZHANG J,LI J,et al.Detecting unknown coal fires:synergy of automated coal fire risk area delineation and improved thermal anomaly extraction[J].International Journal of Remote Sensing,2007,28(20):4561-4585.
[14] ROY P,GUHA A,KUMAR K V.An approach of surface coal fire detection from ASTER and Landsat-8thermal data:Jharia coal field,India[J].International Journal of Applied Earth Observation&Geoinformation,2015,39:120-127.
[15]李峰,梁汉东,赵小平,等.基于ASTER影像的乌达火区遥感监测研究[J].煤矿安全,2016,47(11):15-18.LI Feng,LIANG Handong,ZHAO Xiaoping,et al.Remote sensing monitoring research for coal fire in Wuda using ASTER images[J].Safety in Coal Mines,2016,47(11):15-18.