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Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition.

Authors :
Bo Gao
Huili Gong
Tianxing Wang
Li Jia
Source :
Remote Sensing. Sep2016, Vol. 8 Issue 9, p727. 18p.
Publication Year :
2016

Abstract

Clouds usually cause invalid observations for sensors aboard satellites, which corrupts the spatio-temporal continuity of land surface parameters retrieved from remote sensing data (e.g., MODerate Resolution Imaging Spectroradiometer (MODIS) data) and prevents the fusing of multi-source remote sensing data in the field of quantitative remote sensing. Based on the requirements of spatio-temporal continuity and the necessity of methods to restore bad pixels, primarily resulting from image processing, this study developed a novel method to derive the spectral reflectance for MODIS band of cloudy pixels in the visual-near infrared (VIS-NIR) spectral channel based on the Bidirectional Reflectance Distribution Function (BRDF) and multi-spatio-temporal observations. The proposed method first constructs the spatial distribution of land surface reflectance based on the corresponding BRDF and the solar-viewing geometry; then, a geographically weighted regression (GWR) is introduced to individually derive the spectral surface reflectance for MODIS band of cloudy pixels. A validation of the proposed method shows that a total root-mean-square error (RMSE) of less than 6% and a total R² of more than 90% are detected, which indicates considerably better precision than those exhibited by other existing methods. Further validation of the retrieved white-sky albedo based on the spectral reflectance for MODIS band of cloudy pixels confirms an RMSE of 3.6% and a bias of 2.2%, demonstrating very high accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
8
Issue :
9
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
118431078
Full Text :
https://doi.org/10.3390/rs8090727