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Remote Sensing Technology and Application  2018, Vol. 33 Issue (5): 811-819    DOI: 10.11873/j.issn.1004-0323.2018.5.0811
    
Inversion of Land Surface Temperature and Its Application in Urban Agglomeration Thermal Environment Monitoring based on Tiangong-2 Data
Shi Man1,Chen Jian1,Qin bangyong2,Li shengyang2
(1.School of Remote Sensing and Surveying and Mapping Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,china;2.Key Laboratory of Space Utilization,Technology and Engineering Center for Space Utilization,Chinese Academy of Sciences,Beijing100094,china)
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Abstract  According to the characteristics of thermal infrared spectrum of wide band imager of Tiangong-2 data,a spilt-window algorithm applied to Tiangong-2 data was proposed.Taking the South of Jiangsu urban agglomeration as the research area,the inversion of the land surface temperature was carried out.On this basis,the spatial distribution characteristics of thermal environment of South of Jiangsu urban agglomeration were analyzed through SUHI index.The results show that the split-window algorithm can be effectively applied to the thermal infrared of Tiangong-2 data.The root mean square error of land surface temperature inversion is within 1 K.The result of land surface temperature are in good agreement with the types of land use in the research area,and the temperature of the building land is the highest and the water is the lowest.A global heat island is formed in Suzhou-Wuxi-Chanzhou,and the intensity and spatial distribution of the heat island in the urban agglomeration are monitored by SUHI index.


Key words:  Tiangong-2      Wide band imaging spectrometer      Urban agglomeration      Land Surface Temperature(LST)      Heat island effect     
Received:  13 January 2018      Published:  01 March 2019
ZTFLH:  TP 79  
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Shi Man
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Li shengyang

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Shi Man, Chen Jian, Qin bangyong, Li shengyang. Inversion of Land Surface Temperature and Its Application in Urban Agglomeration Thermal Environment Monitoring based on Tiangong-2 Data. Remote Sensing Technology and Application, 2018, 33(5): 811-819.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2018.5.0811     OR     http://www.rsta.ac.cn/EN/Y2018/V33/I5/811

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