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A physically based algorithm for retrieving land surface temperature under cloudy conditions from AMSR2 passive microwave measurements

文献类型：期刊论文

作者Huang, Cheng1,2; Duan, Si-Bo2; Jiang, Xiao-Guang1; Han, Xiao-Jing2; Leng, Pei2; Gao, Mao-Fang2; Li, Zhao-Liang2,3
刊名INTERNATIONAL JOURNAL OF REMOTE SENSING
出版日期2019
卷号40期号:5-6页码:1828-1843
ISSN号0143-1161
DOI10.1080/01431161.2018.1508920
通讯作者Duan, Si-Bo(duansibo@caas.cn) ; Jiang, Xiao-Guang(xgjiang@ucas.ac.cn)
英文摘要Satellite remote sensing provides a unique way to measure land surface temperature (LST) at regional and global scales. Algorithms using thermal infrared (TIR) data provide a reliable way to retrieve LST. However, they are limited to clear-sky conditions due to their inability to penetrate clouds. As an alternative for LST retrieval, passive microwave data are much less affected by clouds and water vapour than TIR data. In this study, we presented an improved physically based algorithm for the retrieval of LST under cloudy atmospheric conditions from Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature measurements at 18.7 and 23.8 GHz vertically polarized channels based on the assumption that the emissivity relationship between the two adjacent frequencies is linear. The performance of the algorithm was firstly evaluated using simulation data, with a root mean square error (RMSE) of approximately 2.1K. Moreover, the RMSE value reduces with precipitable water vapour (PWV) increasing. This algorithm was further applied to AMSR2measurements. The retrieved cloudy LST was compared with ground-based air temperature over China in 2016. The bias varies from approximately 2K to 4K and the RMSE from approximately 4K to 6K during daytime and night-time. To eliminate the systematic bias between the retrieved LST and the ground-based air temperature, a linear adjustment was performed to the retrieved LST during daytime and nighttime, respectively. The accuracies for the adjusted LST are nearly the same during daytime and night-time, with an RMSE of approximately 3.6K. The combination of this physically based LST retrieval algorithm with TIR LST algorithm is attractive for generating an all-weather LST product at global scale.
WOS关键词BRIGHTNESS TEMPERATURES ; MODEL ; PARAMETERS ; EMISSION ; DROUGHT
资助项目National Natural Science Foundation of China[41231170] ; National Natural Science Foundation of China[41571352] ; National Natural Science Foundation of China[41501406]
WOS研究方向Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者TAYLOR & FRANCIS LTD
WOS记录号WOS:000464043900015
资助机构National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/48282]  
专题中国科学院地理科学与资源研究所
通讯作者Duan, Si-Bo; Jiang, Xiao-Guang
作者单位1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
2.Chinese Acad Agr Sci, Key Lab Agr Remote Sensing, Minist Agr, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China
3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Huang, Cheng,Duan, Si-Bo,Jiang, Xiao-Guang,et al. A physically based algorithm for retrieving land surface temperature under cloudy conditions from AMSR2 passive microwave measurements[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019,40(5-6):1828-1843.
APA Huang, Cheng.,Duan, Si-Bo.,Jiang, Xiao-Guang.,Han, Xiao-Jing.,Leng, Pei.,...&Li, Zhao-Liang.(2019).A physically based algorithm for retrieving land surface temperature under cloudy conditions from AMSR2 passive microwave measurements.INTERNATIONAL JOURNAL OF REMOTE SENSING,40(5-6),1828-1843.
MLA Huang, Cheng,et al."A physically based algorithm for retrieving land surface temperature under cloudy conditions from AMSR2 passive microwave measurements".INTERNATIONAL JOURNAL OF REMOTE SENSING 40.5-6(2019):1828-1843.

入库方式： OAI收割

来源：地理科学与资源研究所

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