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REMOTE SENSING FOR LAND & RESOURCES    2003, Vol. 15 Issue (2) : 55-58     DOI: 10.6046/gtzyyg.2003.02.13
Technology and Methodology |
SPECTRAL CHARACTERISTICS AND INFORMATION EXTRACTION OF BURNT ROCKS IN COAL FIRE FIELDS
ZHU Shan-you1, HAN Zuo-zhen1, ZHANG Guang-chao2
1. College of Geo-info Science and Engineering, Shandong University of Science and Technology, Tai'an 271019, China;
2. Remote Sensing Application Institute of Aerophotogrammetry and Remote Sensing of China Coal, Xi'an 710054, China
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Abstract  Spontaneous combustion of coal constitutes a very serious problem in North China. Practice proves that the application of remote sensing technology can achieve rapid dynamic monitoring of coal fire and provide information for the fire-extinguishing project, thus exhibiting great significance. Burnt rocks as the indicators of coal fire at the earth's surface serve as the most visual information for interpreting coal fire. Based on the reflectance curve characteristics of burnt rocks, the authors compared various methods for extracting the information of burnt rocks, and then determined the best method for this purpose, which can help locate and delineate the coal fire.
Keywords Marsh extraction      Spectrum model      Knowledge discovery      Zhalong wetland      TM image     
Issue Date: 02 August 2011
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HAN Min,CHENG Lei,LIU Quan. SPECTRAL CHARACTERISTICS AND INFORMATION EXTRACTION OF BURNT ROCKS IN COAL FIRE FIELDS[J]. REMOTE SENSING FOR LAND & RESOURCES, 2003, 15(2): 55-58.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2003.02.13     OR     https://www.gtzyyg.com/EN/Y2003/V15/I2/55


[1] 管海晏,等.中国北方煤田自燃环境调查与研究[M].北京:煤炭工业出版社,1998.





[2] 陈述彭,赵英时.遥感地学分析[M].北京:测绘出版社,1990.





[3] 朱述龙,张占睦.遥感图像获取与分析[M].北京:科学出版社,1998.





[4] Green A A, Berman M, Switzer P, et al. A transformation for ordering multispectral data in terms of image quality with implications for noise removal[J].IEE Transactions on Geosience and Remote Sensing,1988,26(1):65-74.





[5] Boardman J W, Kruse F A.Automated spectral analysis:A geologic example using AVIRIS data, north Grapevine Mountains[C].Tech Thematic Conference on Geologic Remote Sensing,Environmental Research Institute of Michigan.Nevada:Ann Arbor,MI, 1994,I:407-418.





[6] 浦瑞良,宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2000.





[7] 陈述彭,童庆禧,郭华东.遥感信息机理研究[M].科学出版社.1998.





[8] 万余庆,等.矿物岩石高光谱数据库分析[J].地球信息科学.2001(3).54-58.
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