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国土资源遥感  2012, Vol. 24 Issue (4): 101-106    DOI: 10.6046/gtzyyg.2012.04.17
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
基于TM数据的地下煤火区地表温度反演与验证
姬洪亮1, 塔西甫拉提·特依拜2,3, 蔡忠勇4, 师庆东2,3, 魏军4, 夏军2,3
1. 新疆维吾尔自治区交通规划勘察设计研究院,乌鲁木齐 830006;
2. 新疆大学资源与环境科学学院,乌鲁木齐 830046;
3. 新疆大学绿洲生态教育部重点实验室, 乌鲁木齐 830046;
4. 新疆煤田灭火工程局,乌鲁木齐 830000
The Inversion and Verification of Land Surface Temperature for Coal Fire Areas Based on TM Data
JI Hong-liang1, TASHPOLAT稵iyip2,3, CAI Zhong-yong4, SHI Qing-dong2,3, WEI Jun4, XIA Jun2,3
1. Xinjiang Transportation Planning Surveying and Design Institute, Urumqi 830006, China;
2. College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China;
3. Key Laboratory of Oasis Ecology Under Ministry of Education, Xinjiang University, Urumqi 830046, China;
4. Xinjiang Coal Field Fire-fighting Engineering Bureau, Urumqi 830000, China
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摘要 以新疆维吾尔自治区水西沟火区为例,利用与Landsat 5卫星2011年7月31日过境同时段的红外辐射计地表温度观测数据,通过多种方法获取了像元尺度的地表温度实测值,并对基于TM数据反演地表温度的单窗算法、普适性单通道算法和Weng算法得到的地下煤火区地表温度进行对比分析与验证。结果表明,3种遥感反演算法得到的水西沟地下煤火区地表温度的空间分布趋势一致,其中,单窗算法与普适性单通道算法较为接近,研究区整体的平均地表温度差值为1.60℃。与地面实测数据相比,3种反演算法结果均低于地表温度实测值。其中,普适性单通道算法与地面实测值一致性最好,决定系数R2为0.886,均方差为1.48℃,其反演结果符合地下煤火区温度的空间分布规律,高温异常区范围明显; 反演结果符合要求,在地下煤火区地表温度获取中具有一定的适用性,为提升新疆地下煤火区的动态监测与评价能力选择了有效方法。
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孟鹏
胡勇
巩彩兰
栗琳
关键词 劈窗算法地表温度热红外通道MODTRAN    
Abstract:With the coal fire area of the Shuixigou mine in Xinjiang as an example and on the basis of observation data of infrared radiometer at the same time of passing aviation of Landsat 5 on June 31, 2011, the authors calculated surface temperature at pixel scale using several schemes, comparatively studied the surface temperature of the coal fire area inversed by mono-window algorithm, and generalized single-channel algorithm and Weng algorithm with TM data. The results show that all the three algorithms show a consistent distribution of surface temperature of the Shuixigou underground coal fire area, and the mono-window algorithm and generalized single-channel algorithm have the smallest difference in the average surface temperature of the whole study area, which is about 1.60℃. Through a comparison with the ground measurements, a lower difference value is obtained by all the three algorithms, and the retrieved data by generalized single-channel algorithm are highly close to the data retrieved by mono-window algorithm, wih the regression coefficient and RMSE being 0.886 and 1.48℃ respectively. The retrieval results of generalized single-channel algorithm are in line with the spatial distribution law of the temperature of the underground coal fire area, and the high-temperature anomaly district is obvious. The result of the retrieved data of surface temperature is acceptable and the generalized single-channel algorithm is somewhat effective in acquisition of the LST of the underground coal fire area, thus providing a reference for the dynamic monitoring and evaluation of underground coal fire areas.
Key wordssplit-window algorithm    Earth surface temperature    thermal infrared band    MODTRAN
收稿日期: 2012-07-16      出版日期: 2012-11-13
: 

TP 722.5

 
  P 237

 
基金资助:

新疆维吾尔自治区科技支撑计划项目(编号: 201033122)。

通讯作者: 塔西甫拉提·特依拜(1958-),男(维吾尔族),毕业于东京理科大学遥感应用研究所(工学博士),教授(博士生导师),主要从事遥感技术及其应用研究。
引用本文:   
姬洪亮, 塔西甫拉提·特依拜, 蔡忠勇, 师庆东, 魏军, 夏军. 基于TM数据的地下煤火区地表温度反演与验证[J]. 国土资源遥感, 2012, 24(4): 101-106.
JI Hong-liang, TASHPOLAT稵iyip, CAI Zhong-yong, SHI Qing-dong, WEI Jun, XIA Jun. The Inversion and Verification of Land Surface Temperature for Coal Fire Areas Based on TM Data. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(4): 101-106.
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https://www.gtzyyg.com/CN/10.6046/gtzyyg.2012.04.17      或      https://www.gtzyyg.com/CN/Y2012/V24/I4/101
[1] 张建民.中国地下煤火研究与治理[M].北京:煤炭工业出版社,2008:3-4.

Zhang J M.Underground Coal Fires in China:Origin,Detection,Fire-fighting,and Prevention[M].Beijing:China Coal Industry Publishing House,2008:3-4(in Chinese with English Abstract).

[2] 钟茂华,符泰然,胡忠斌.新疆煤田火区现状调查研究——小尺度区域热辐射信息分析[J].中国工程科学,2010,12(1):12-17.

Zhong M H,Fu T R,Hu Z B.Small-scale Area Survey and Analyses of Xinjiang’s Coal Field Fire in China[J].Engineering Science,2010,12(1):12-17(in Chinese with English Abstract).

[3] 武建军,蒋卫国,刘晓晨,等.地下煤火探测、监测与灭火技术研究进展[J].煤炭学报,2009,35(12):1669-1674.

Wu J J,Jiang W G,Liu X C,et al.Innovative Technologies for Exploration,Monitoring and Extinction of Underground Coal Fires[J].Journal of China Coal Society,2009,35(12):1669-1674(in Chinese with English Abstract).

[4] Düzgün S,Künzer C,Karacan C .Applications of Remote Sensing and GIS for Monitoring of Coal Fires,Mine Subsidence,Environmental Impacts of Coal-mine Closure and Reclamation[J].International Journal of Coal Geology,2011,86(1):1-2.

[5] Mishra R K,Bahuguna P P,Singh V K.Detection of Coal Mine Fire in Jharia Coal Field Using Landsat-7 ETM+ Data[J].International Journal of Coal Geology,2011,86:73-78.

[6] 康高峰,雷学武,吴军虎,等.TM图像在新疆奇台北山煤田火区动态监测中的应用[J].国土资源遥感,1996(2):57-62.

Kang G F,Lei X W,Wu J H,et al.Study and Application of TM Image in Coal Fire in Beishan Qitai, Xinjiang[J].Remote Sensing for Land and Resources,1996(2):57-62(in Chinese with English Abstract).

[7] 蒋卫国,武建军,顾磊,等.基于夜间热红外光谱的地下煤火监测方法研究[J].光谱学与光谱分析,2011,31(2):357-361.

Jiang W G,Wu J J,Gu L,et al.Monitoring Method of Underground Coal Fire Based on Night Thermal Infrared Remote Sensing Technology[J].Spectroscopy and Spectral Analysis,2011,31(2):357-361(in Chinese with English Abstract).

[8] 陈云浩,李京,杨波,等.基于遥感和GIS的煤田火灾检测研究——以宁夏汝箕沟煤田为例[J].中国矿业大学学报,2005,34(2):226-230.

Chen Y H,Li J,Yang B,et al.Monitoring Coal Fires Based on Remotely Sensed Data and GIS Technique in Coalfields—a Case Study of Rujigou Coal Field in Nixia,China[J].Journal of China University of Mining and Technology,2005,34(2):226-230(in Chinese with English Abstract).

[9] 覃志豪,Zhang M H,Karnieli A,等.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466.

Qin Z H,Zhang M H,Karnieli A,et al.Mono-window Algorithm for Retrieving Land Surface Temperature from Landsat TM6 Data[J].Acta Geographica Sinica,2001,56(4):456-466(in Chinese with English Abstract).

[10] Jiménez-Mun[DD(-*2/3] ~[DD)] oz J C,Sobrino J A.A Generalized Single-channel Method for Retrieving Land Surface Temperature from Remote Sensing Data[J].Journal of Geophysical Research,2003,108(D22):4688-4695.

[11] Weng Q H,Lu D S,Schubring J.Estimation of Land Surface Temperature Vegetation Abundance Relationship for Urban Heat Island Studies[J].Remote Sensing of Environment,2004,89(4):467-487.

[12] Sobrino J A,Jiménez-Mun[DD(-*2/3] ~[DD)] oz J C,Paolini L.Land Surface Temperature Retrieval from Lsndsat TM5[J].Remote Sensing of Environment,2004,90(4):434-440.

[13] 覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004(3):28-32,36,41.

Qin Z H,Li W J,Xu B,et al.The Estimation of Land Surface Emissivity for Landsat TM6[J].Remote Sensing for Land and Resources,2004(3):28-32,36,41(in Chinese with English Abstract).
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