Nonlinear Split-Window Algorithms for Estimating Land and Sea Surface Temperatures From Simulated Chinese Gaofen-5 Satellite Data
文献类型：期刊论文
| 作者 | Tang, Bo-Hui1,2
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| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2018-11-01 |
| 卷号 | 56期号:11页码:6280-6289 |
| 关键词 | Different thermal channel combination split-window (DTCC-SW) Gaofen-5 (GF-5) land surface temperature (LST) sea surface temperature (SST) thermal infrared (TIR) |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2018.2833859 |
| 通讯作者 | Tang, Bo-Hui(tangbh@igsnrr.ac.cn) |
| 英文摘要 | This paper proposes a different thermal channel combination split-window (DTCC-SW) method to estimate the land surface temperature (LST) and sea ST (SST) from the Chinese Gaofen-5 (GF-5) satellite thermal infrared (TIR) data. A nonlinear combination of two adjacent channels CH8,20 (centered at 8.20 mu m) and CH8.63 (centered at 8.63 mu m) was proposed to estimate LST for low-emissivity surfaces. A nonlinear combination of two adjacent channels, CH10.80 (centered at 10.80 mu m) and CH11.95 (centered at 11.92 mu m), was developed to estimate LST and SST for high-emissivity surfaces under dry atmospheric conditions, and a nonlinear combination of two channels, CH8.63 and CH11.95, was used to estimate LST and SST for high-emissivity surfaces under wet atmospheric conditions. The numerical values of the DTCC-SW coefficients were obtained using a statistical regression method from synthetic data simulated with an accurate atmospheric radiative transfer model moderate spectral resolution atmospheric transmittance mode 5 over a wide range of atmospheric and surface conditions. The LST (SST), mean emissivity, and atmospheric water vapor content were divided into several tractable subranges to improve the fitting accuracy. The experimental results and the preliminary evaluation results showed that the root-mean-square error between the actual and estimated LSTs (SSTs) is less than 0.7 K (0.3 K), provided that the land surface emissivities are known, which indicates that the proposed DTCC-SW method can accurately estimate the LST and SST from the GF-5 TIR data. |
| WOS关键词 | EMISSIVITY RETRIEVAL ; MU-M ; ASTER ; VALIDATION ; PRODUCTS ; GOES-8 ; SPACE |
| 资助项目 | National Natural Science Foundation of China[41571353] ; Innovation Project of LREIS[O88RA801YA] ; National Key Research and Development Program of China[2016YFA0600103] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000448621000002 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; Innovation Project of LREIS ; National Key Research and Development Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/52620]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tang, Bo-Hui |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Tang, Bo-Hui. Nonlinear Split-Window Algorithms for Estimating Land and Sea Surface Temperatures From Simulated Chinese Gaofen-5 Satellite Data[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2018,56(11):6280-6289. |
| APA | Tang, Bo-Hui.(2018).Nonlinear Split-Window Algorithms for Estimating Land and Sea Surface Temperatures From Simulated Chinese Gaofen-5 Satellite Data.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,56(11),6280-6289. |
| MLA | Tang, Bo-Hui."Nonlinear Split-Window Algorithms for Estimating Land and Sea Surface Temperatures From Simulated Chinese Gaofen-5 Satellite Data".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 56.11(2018):6280-6289. |
入库方式： OAI收割
来源：地理科学与资源研究所
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