Land Surface Temperature Retrieval Using Airborne Hyperspectral Scanner Daytime Mid-Infrared Data

Remote Sensing

Enyu Zhao²  Yonggang Qian¹  Caixia Gao¹  Hongyuan Huo²  Xiaoguang Jiang²  Xiangsheng Kong³  Janet Nichol⁴ 

[1] Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China; E-Mail:;University of Chinese Academy of Sciences, Beijing 100049, China; E-Mails:;College of Geography and Planning, Ludong University, Yantai 264025, China; E-Mail:University of Chinese Academy of Sciences, Beijing 100049, China;

关键词: mid-infrared data;    land surface temperature;    split-window;    AHS data;   

DOI  :  10.3390/rs61212667

来源: mdpi

【 摘 要 】

Land surface temperature (LST) retrieval is a key issue in infrared quantitative remote sensing. In this paper, a split window algorithm is proposed to estimate LST with daytime data in two mid-infrared channels (channel 66 (3.746~4.084 μm) and channel 68 (4.418~4.785 μm)) from Airborne Hyperspectral Scanner (AHS). The estimation is conducted after eliminating reflected direct solar radiance with the aid of water vapor content (WVC), the view zenith angle (VZA), and the solar zenith angle (SZA). The results demonstrate that the LST can be well estimated with a root mean square error (RMSE) less than 1.0 K. Furthermore, an error analysis for the proposed method is also performed in terms of the uncertainty of LSE and WVC, as well as the Noise Equivalent Difference Temperature (NEΔT). The results show that the LST errors caused by a LSE uncertainty of 0.01, a NEΔT of 0.33 K, and a WVC uncertainty of 10% are 0.4~2.8 K, 0.6 K, and 0.2 K, respectively. Finally, the proposed method is applied to the AHS data of 4 July 2008. The results show that the differences between the estimated and the ground measured LST for water, bare soil and vegetation areas are approximately 0.7 K, 0.9 K and 2.3K, respectively.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.