IGSNRR OpenIR
Land Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform
Zhang, Yu-Ze1; Wu, Hua1,2,3; Jiang, Xiao-Guang1,2,4; Jiang, Ya-Zhen1; Liu, Zhao-Xia5; Nerry, Franoise6
2017-05-01
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume9Issue:5Pages:16
Corresponding AuthorWu, Hua(wuhua@igsnrr.ac.cn) ; Jiang, Xiao-Guang(xgjiang@ucas.ac.cn)
AbstractCurrently, the main difficulty in separating the land surface temperature (LST) and land surface emissivity (LSE) from field-measured hyperspectral Thermal Infrared (TIR) data lies in solving the radiative transfer equation (RTE). Based on the theory of wavelet transform (WT), this paper proposes a method for accurately and effectively separating LSTs and LSEs from field-measured hyperspectral TIR data. We show that the number of unknowns in the RTE can be reduced by decomposing and reconstructing the LSE spectrum, thus making the RTE solvable. The final results show that the errors introduced by WT are negligible. In addition, the proposed method usually achieves a greater accuracy in a wet-warm atmosphere than that in a dry-cold atmosphere. For the results under instrument noise conditions (NE Delta T = 0.2 K), the overall accuracy of the LST is approximately 0.1-0.3 K, while the Root Mean Square Error (RMSE) of the LSEs is less than 0.01. In contrast to the effects of instrument noise, our method is quite insensitive to noises from atmospheric downwelling radiance, and all the RMSEs of our method are approximately zero for both the LSTs and the LSEs. When we used field-measured data to better evaluate our method's performance, the results showed that the RMSEs of the LSTs and LSEs were approximately 1.1 K and 0.01, respectively. The results from both simulated data and field-measured data demonstrate that our method is promising for decreasing the number of unknowns in the RTE. Furthermore, the proposed method overcomes some known limitations of current algorithms, such as singular values and the loss of continuity in the spectrum of the retrieved LSEs.
Keywordtemperature and emissivity separation hyperspectral field-measured data wavelet transform
DOI10.3390/rs9050454
WOS KeywordSPLIT-WINDOW ALGORITHM ; ATMOSPHERIC CORRECTION ; SPECTRAL EMISSIVITY ; IMAGES ; SEPARATION ; SENSOR
Indexed BySCI
Language英语
Funding ProjectNational Key Basic Research Program of China (973 Program)[2013CB733402] ; National Natural Science Foundation of China[41331171] ; National Natural Science Foundation of China[41571352] ; National Natural Science Foundation of China[41471297] ; Innovation Project of LREIS[O88RA801YA]
Funding OrganizationNational Key Basic Research Program of China (973 Program) ; National Natural Science Foundation of China ; Innovation Project of LREIS
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000402573700057
PublisherMDPI AG
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/63568
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWu, Hua; Jiang, Xiao-Guang
Affiliation1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
4.Chinese Acad Sci, Acad Optoelect, Key Lab Quantitat Remote Sensing Informat Technol, Beijing 100094, Peoples R China
5.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, Urumqi 830011, Peoples R China
6.CNRS, ICube, UdS, 300 Bld Sebastien Brant,CS10413, F-67412 Illkirch Graffenstaden, France
Recommended Citation
GB/T 7714
Zhang, Yu-Ze,Wu, Hua,Jiang, Xiao-Guang,et al. Land Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform[J]. REMOTE SENSING,2017,9(5):16.
APA Zhang, Yu-Ze,Wu, Hua,Jiang, Xiao-Guang,Jiang, Ya-Zhen,Liu, Zhao-Xia,&Nerry, Franoise.(2017).Land Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform.REMOTE SENSING,9(5),16.
MLA Zhang, Yu-Ze,et al."Land Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform".REMOTE SENSING 9.5(2017):16.
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