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A remote sensing method for retrieving land surface emissivity and temperature in cloudy areas: a case study over South China
Zhou, Fang-Cheng1,2; Li, Zhao-Liang3; Wu, Hua1,2; Duan, Si-Bo3; Song, Xiaoning2; Yan, Guangjian4
2019
Source PublicationINTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
Volume40Issue:5-6Pages:1724-1735
Corresponding AuthorWu, Hua(wuhua@igsnrr.ac.cn)
AbstractLand surface temperature (LST) is an important parameter at the surface-atmosphere interface, and measurements of the LST at continuous temporal and spatial scales are necessary in many research fields. Passive microwave radiation can penetrate clouds and detect land surface information under clouds; consequently, passive microwave remote sensing has the potential to obtain LST under almost all weather conditions. In this study, the relationships between the brightness temperature polarization ratio (PR) and horizontally polarized emissivities, and between the horizontally and vertically polarized emissivities are combined to develop a three-stage LST retrieval algorithm from 19 GHz microwave brightness temperature observations in cloudy areas. During the first two stages, the horizontally and vertically polarized emissivities are solely obtained from the brightness temperature data. In the last stage, the LST is calculated with the known emissivity data by ignoring the atmospheric effect. In the validation of South China, the root-mean-square errors (RMSEs) of the estimated horizontally and vertically polarized emissivities at 19 GHz are 0.0078 and 0.0023, respectively. The retrieved LST is compared to single-point measurements of the meteorological stations, and the RMSE is 4.1200K. The LST errors are mainly due to the propagation of estimated land surface emissivity (LSE) errors, and the poor representativeness of the validated data in mixed pixels. The superiority of this LST retrieval algorithm lies in simultaneously obtaining the LST and both polarized LSE under almost all weather conditions with little input data.
DOI10.1080/01431161.2018.1519288
WOS KeywordPASSIVE MICROWAVE ; AMSR-E ; SSM/I ; VALIDATION ; PRODUCTS
Indexed BySCI
Language英语
Funding ProjectStrategic Priority Research Program of the Chinese Academy of Sciences[XDA20030302] ; National Natural Science Foundation of China[41471297] ; National Natural Science Foundation of China[41531174] ; National Natural Science Foundation of China[41571352]
Funding OrganizationStrategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China
WOS Research AreaRemote Sensing ; Imaging Science & Photographic Technology
WOS SubjectRemote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000464043900008
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/48286
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWu, Hua
Affiliation1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Chinese Acad Agr Sci, Key Lab Agr Remote Sensing, Minist Agr, Inst Agr Resources & Reg Planning, Beijing, Peoples R China
4.Beijing Normal Univ, State Key Lab Remote Sensing Sci, Sch Geog, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Zhou, Fang-Cheng,Li, Zhao-Liang,Wu, Hua,et al. A remote sensing method for retrieving land surface emissivity and temperature in cloudy areas: a case study over South China[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019,40(5-6):1724-1735.
APA Zhou, Fang-Cheng,Li, Zhao-Liang,Wu, Hua,Duan, Si-Bo,Song, Xiaoning,&Yan, Guangjian.(2019).A remote sensing method for retrieving land surface emissivity and temperature in cloudy areas: a case study over South China.INTERNATIONAL JOURNAL OF REMOTE SENSING,40(5-6),1724-1735.
MLA Zhou, Fang-Cheng,et al."A remote sensing method for retrieving land surface emissivity and temperature in cloudy areas: a case study over South China".INTERNATIONAL JOURNAL OF REMOTE SENSING 40.5-6(2019):1724-1735.
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