Atmospheric water vapor retrieval from Landsat 8 thermal infrared images

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)...

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Bibliographic Details
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
Description
Summary: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 qmqinpku@163.com 5 1723-1738 120

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