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新疆老君庙煤矿火区地表温度反演及时空变化分析 被引量:1

Space-time variation analysis and monitoring of the land surface temperature of coal fire area in Laojunmiao,Xinjiang
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摘要 通过Landsat TM5和Landsat 8/OLI分别选取新疆老君庙煤矿区2006年7月26日、2010年7月21日和2015年7月20日份过境的遥感影像,运用单窗算法反演研究区地表温度(LST)并进行煤火区时空变化监测,得出:LST最大值在2015年,为46.19℃;最小值在2006年,为26.47℃,各年均温度呈现递增趋势。2006年和2010年LST变异系数小于0.1,属低变异;2015年为0.12,属中变异,随时间变化受人类影响逐渐加剧。各年LST变化幅度分别为5.38℃、8.37℃和14.88℃,说明受到某些地表因素变化的影响,LST分布差异性逐年增大。监测各年煤火区时空变化得出:2006年地下火区面积为0.53hm2,2010年为1.44hm2,2015年为6.57hm2。2006~2015年地下火区面积年均增长率为25.72%,且增速逐年加快,长此下去,煤炭资源损失将会更加严重。 This article is witnessed to retrieve the land surface temperature (LST) in Laojunmiao coal fire area in Xinjiang by using the Monowindow method with images of Landsat 5 and 8/OLI taken in July 26th,2006 ,July 21 th, 2010 and July 20th, 2015, respectively. The results showed that the highest value of LST was 46.19 ℃ in 2015,while the lowest of that was 26.47 ℃ in 2006. The mean LST had increasing trend. Variation coefficients of 2006 and 2010 were lower than 0. 1 belonged slight variation, while that of 2015 was 0. 12 belonged moderate variation showing that LST was subjected to human disturbance over time. The variation ranges of each year was 5.38 ℃ ,8.37 ℃ and 14.88 ℃ ,respectively,indicating that LST distribution was changed over time that affected by the changes of some factors. The result of monitoring coal fire was that the increasing rate of underground fire area between 2006 and 2015 was 25.72%,which was intensifying year after year. If things continue this way,coal lost issues will be more serious.
作者 唐梦迎 丁建丽 夏楠 TANG Mengying1,2 , DING Jianli1,2 , XIA Nan1,2(1. College of Resource and Environment Science, Xinjiang University, Urumqi 830046, China; Ministry of Education Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, Chin)
出处 《中国矿业》 北大核心 2018年第5期164-167,共4页 China Mining Magazine
基金 自治区科技支疆项目资助(编号:201591101) 自治区重点实验室专项基金项目资助(编号:2016D03001 2014KL005) 国家自然科学基金项目资助(编号:U1303381 41261090)
关键词 煤田火区 地表温度 遥感监测 时空分析 coal fire land surface temperature (LST) remote sensing monitoringl space-timeanalysis
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