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Remote Sensing Technology and Application  2018, Vol. 33 Issue (5): 803-810    DOI: 10.11873/j.issn.1004-0323.2018.5.0803
Comparison of Land Surface Temperature Retrieval Algorithms in Karst City
Wang Kaining1,Wang Xiuxin2,3,Huang Fengrong1,Luo Lianling2
(1.School of Urban and Environmental Sciences,Liaoning Normal University,Dalian 116029,China;
2.College of Computer Science and Information Technology,Guangxi Normal University,
Guilin 541004,China;3.State Key Laboratory of Remote Sensing Science,Beijing NormalUniversity,Beijing 100875,China)
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Abstract  Urban land covers have changed greatly with the rapid expansion of Guilin karst city in recent two decades.Some agriculture lands,forest and pools converted to buildings and roads,and some karst hills also entered urban district.However,the vegetation on some karst hills was destroyed and parts of limestone hill body were exposed.High air temperature was felt frequently in summer.Spatial distribution of land surface thermal field was affected by land cover changes directly.Land surface thermal field could be quantitatively descripted with Land Surface Temperature(LST).In order to analyze the impact of urban rapid expansion on thermal environment in karst city,LSTs were derived from Landsat 8 images and five retrieval algorithms with the proposal of the emissivity estimation method in the mixed pixels on karst hills.Then the derived LST results were compared with measurements so that the available retrieving algorithm for karst city was got.Finally,sensitive factors on LST were analyzed.Result shows that LSTs from Single\|Channel (SC) algorithms are more accurate than those from Split\|Window(SW) algorithms with high atmospheric moisture content in karst district.The errors are within1.0 ℃ between LST measurements and retrieval results from Jimenez SC(JSC) and Qin Mono\|Window(QMW).LST statistics derived from JSC and QMW are close with average difference of 0.26 ℃ and standard deviation difference of 0.01 ℃.Average LST differences of building and bare rock are 0.43 ℃ and 0.54 ℃ respectively,higher than those of water body and dense vegetation.LST statistics from Jimenez SW(JSW) and Rozenstein SW(RSW) are close with average LST difference of 1.14 ℃ and standard deviation difference of 0.19 ℃.LST statistics from Weng SC arebetween those from SWs and those from JSC,QMW.As five algorithms show high sensitivity to emissivity,LST average will change 0.4~0.7 ℃ with 0.01 increment of emissivity.Five algorithms are relatively less sensitive to air temperature,total water vapor content,atmospheric transmittance in addition to QMW with which 1.0  ℃increment of air temperature will result in nearly 0.5 ℃ error of LST.JSC and QMW with Landsat 8 TIRS band 10 are suitable for LST retrieval with high accuracy in karst city.The research results can provide scientific data for thermal environment monitoring in karst cities.
Key words:  Karst city      Remote sensing      Land Surface Temperature(LST)      Retrieval algorithms      Sensitivity analysis     
Received:  27 March 2018     
TP 79  
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Articles by authors
Wang Kaining
Wang Xiuxin
Huang Fengrong
Luo Lianling

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Wang Kaining,Wang Xiuxin,Huang Fengrong,Luo Lianling. Comparison of Land Surface Temperature Retrieval Algorithms in Karst City. Remote Sensing Technology and Application, 2018, 33(5): 803-810.

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