A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data

Remote Sensing

Chen Du²  Huazhong Ren²  Qiming Qin²  Jinjie Meng²  Shaohua Zhao³  Zhao-Liang Li¹  Jose A. Sobrino¹  Xiaoning Song¹ 

[1] Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China;;Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China; E-Mails:;Satellite Environmental Application Center, Ministry of Environmental Protection, Beijing 100094, China; E-Mail:

关键词: Land Surface Temperature (LST);    Landsat 8;    split-window algorithm;    Thermal Infrared (TIR);   

DOI  :  10.3390/rs70100647

来源: mdpi

【 摘 要 】

This paper developed a practical split-window (SW) algorithm to estimate land surface temperature (LST) from Thermal Infrared Sensor (TIRS) aboard Landsat 8. The coefficients of the SW algorithm were determined based on atmospheric water vapor sub-ranges, which were obtained through a modified split-window covariance–variance ratio method. The channel emissivities were acquired from newly released global land cover products at 30 m and from a fraction of the vegetation cover calculated from visible and near-infrared images aboard Landsat 8. Simulation results showed that the new algorithm can obtain LST with an accuracy of better than 1.0 K. The model consistency to the noise of the brightness temperature, emissivity and water vapor was conducted, which indicated the robustness of the new algorithm in LST retrieval. Furthermore, based on comparisons, the new algorithm performed better than the existing algorithms in retrieving LST from TIRS data. Finally, the SW algorithm was proven to be reliable through application in different regions. To further confirm the credibility of the SW algorithm, the LST will be validated in the future.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.