ATMOSPHERIC WATER VAPOR RETRIEVAL FROM LANDSAT 8 AND ITS VALIDATION

被引：9

作者：

Ren, Huazhong ^{[1
]}

Du, Chen ^{[1
]}

Qin, Qiming ^{[1
]}

Liu, Rongyuan

Meng, Jinjie ^{[1
]}

Li, Jing

机构：

[1] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

Landsat; 8; TIRS; water vapor; split-window algorithm; MSWCVR;

D O I：

10.1109/IGARSS.2014.6947119

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This objective of this paper is to estimate atmospheric water vapor (m)) from the latest Landsat 8 Thermal InfRared Sensor (TIRS) image by using a new modified split-window covariance-variance ratio (MSWCVR) method. Model analysis showed that the MSWCVR method can theoretically retrieve wv with an accuracy better than 0.45g/cm(2) for most atmospheric moisture conditions. The MSWCVR was evaluated by using AERONET ground-measured data and cross-compared with MODIS products in 2013 at forty two ground sites, and results presented that the retrieved wv from TIRS data was highly correlated with but generally larger (about 1.0 g/cm(2)) than two others. The reasons for this uncertainty were mainly ascribed to data systematic noise and radiative calibration error. Future work must pay more attention to the data quality and radiative calibration of Landsat 8 TIRS data.

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