Atmospheric water vapor retrieval from Landsat 8 thermal infrared images

• Published in: Journal of Geophysical Research: Atmospheres
• Main Authors: Ren, Huazhong, Du, Chen, Liu, Rongyuan, Qin, Qiming, Yan, Guangjian, Li, Zhao-Liang, Meng, Jinjie
• Other Authors: Qin, QM (reprint author), Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China., Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China., Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China., Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Minist Agr, Key Lab Agriinformat, Beijing 100193, Peoples R China., Univ Strasbourg, ICube Lab, Illkirch Graffenstaden, France.
• Format: Journal/Newspaper
• Language: English
• Published: journal of geophysical research atmospheres 2015
• Subjects: water vapor; Landsat 8; MSWCVR; TIRS; thermal infrared remote sensing; SPLIT-WINDOW ALGORITHM; RESOLUTION IMAGING SPECTRORADIOMETER; SURFACE-TEMPERATURE; PRECIPITABLE WATER; RADIOMETRIC CALIBRATION; SENSOR; PERFORMANCE; Aerosol Robotic Network
• Online Access: https://hdl.handle.net/20.500.11897/155318; https://doi.org/10.1002/2014JD022619

Atmospheric water vapor (wv) is required for the accurate retrieval of the land surface temperature from remote sensing data and other applications. This work aims to estimate wv from Landsat 8 Thermal InfraRed Sensor (TIRS) images using a new modified split-window covariance-variance ratio (MSWCVR) method on the basis of the brightness temperatures of two thermal infrared bands. Results show that the MSWCVR method can theoretically retrieve wv with an accuracy better than 0.3g/cm(2) for dry atmosphere (wv<2g/cm(2)) conditions and better than 0.5g/cm(2) for wet atmosphere conditions. The method was applied at different locations with dry and moist atmospheres and was validated at 42 ground sites using AERONET (Aerosol Robotic Network) ground-measured data and MODIS (Moderate Resolution Imaging Spectroradiometer) products. The results show that the retrieved wv from the TIRS data is highly correlated with the wv of AERONET and MODIS but is generally larger. This difference was probably attributed to the uncertainty of radiometric calibration and stray light coming outside from field of view of TIRS instrument in the current images. Consequently, the data quality and radiometric calibration of the TIRS data should be improved in the future. Meteorology & Atmospheric Sciences SCI(E) 0 ARTICLE [e-mail] 5 1723-1738 120