LAND SURFACE TEMPERATURE RETRIEVED FROM COMBINED MID-INFRARED AND THERMAL INFRARED DATA

被引：0

作者：

Qian, Yong-Gang ^{[1
]}

Li, Kun ^{[1
,2
]}

Wang, Ning ^{[1
]}

Ma, Ling-Ling ^{[1
]}

Liu, Yao-Kai ^{[1
,2
]}

Li, Wei ^{[1
,2
]}

Ren, Lu ^{[1
]}

Qiu, Shi ^{[1
]}

Li, Chuan-Rong ^{[1
]}

Tang, Ling-Li ^{[1
]}

机构：

[1] Chinese Acad Sci, Acad Optoelect, Key Lab Quantitat Remote Sensing Informat Technol, Beijing 100094, Peoples R China

[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

来源：

2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2017年

基金：

中国国家自然科学基金; 国家重点研发计划; 国家高技术研究发展计划(863计划);

关键词：

Temperature; mid-infrared and thermal infrared; split window algorithm; EMISSIVITY;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

This paper addressed the retrieval of land surface temperature (LST) from combined mid-infrared and thermal infrared data of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP). To efficiently remove the effect of the direct solar radiance, a relationship between direct solar radiance and water vapor content, view zenith angle and solar zenith angle is proposed to improve the retrieve accuracy. Then, a split-window algorithm from combined mid-infrared and thermal infrared data is used to correct for the atmospheric effects and retrieve the LST with the aid of emissivity provide by VIIRS product. Finally, comparison of the standard VIIRS LST product and the retrieved LST from the proposed algorithm, a good agreement was shown. Analysis indicated the root mean square error (RMSE) of the LST over these land cover types is 2.04K for desert and 1.84K for vegetation, respectively.

引用

页码：3969 / 3972

页数：4

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