An alternative split-window algorithm for retrieving land surface temperature from Visible Infrared Imaging Radiometer Suite data

文献类型： 外文期刊

第一作者： Wang, Chenguang

作者： Wang, Chenguang;Zhang, Xiaoyu;Wang, Chenguang;Duan, Si-Bo;Gao, Mao-Fang;Leng, Pei;Wu, Hua

作者机构：

期刊名称：INTERNATIONAL JOURNAL OF REMOTE SENSING （ 影响因子：3.151； 五年影响因子：3.266 ）

ISSN： 0143-1161

年卷期： 2019 年 40 卷 5-6 期

页码：

收录情况： SCI

摘要： Land surface temperature (LST) is a key parameter for surface water and energy budget calculations. To improve the accuracy of LST retrieval over bare soil surfaces, we proposed an alternative split-window algorithm to retrieve LST from Visible Infrared Imaging Radiometer Suite (VIIRS) thermal infrared data. Atmospheric water vapour content (WVC) and surface emissivity are key input parameters in the split-window algorithm. The National Centres for Environmental Prediction (NCEP) reanalysis data in combination with the Moderate Resolution Transmittance Code (MODTRAN) were used to estimate atmospheric WVC. The Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Emissivity Dataset (ASTER GED) product was used to correct emissivity effects. The accuracy of the retrieved LST was evaluated using in situ measurements collected from the Hailar and Urad Front Banner sites in China. The root mean square error (RMSE) values of approximately 1.10 and 1.70K are obtained for grass/snow surfaces in the Hailar site and sand surfaces in the Urad Front Banner site, respectively. The VIIRS LST product is also validated using the in situ LST in the two sites. The RMSE values of approximately 2.50 and 5.80K are achieved for the Hailar and Urad Front Banner sites, respectively. The results indicate that the proposed LST algorithm with surface emissivity estimated from the ASTER GED product has better accuracy of LST retrieval.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序