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Remote Sens. 2015, 7(9), 11481-11500; doi:10.3390/rs70911481

Removal of Thin Clouds in Landsat-8 OLI Data with Independent Component Analysis

School of Resources and Environment, University of Electronic and Science Technology of China (UESTC), 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu 611731, China
Department of Geography, Planning, and Environment, East Carolina University, Greenville, NC 27858, USA
Institute of Remote Sensing Big Data, Big Data Research Center of UESTC, 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu 611731, China
Author to whom correspondence should be addressed.
Academic Editors: Alexander A. Kokhanovsky and Prasad S. Thenkabail
Received: 15 June 2015 / Revised: 16 August 2015 / Accepted: 2 September 2015 / Published: 9 September 2015
(This article belongs to the Special Issue Aerosol and Cloud Remote Sensing)
View Full-Text   |   Download PDF [3248 KB, uploaded 9 September 2015]   |  


An approach to remove clouds in Landsat-8 operational land imager (OLI) data was developed with independent component analysis (ICA). Within cloud-covered areas, histograms were derived to quantify changes of the reflectance values before and after the use of the algorithm. Referred to a cloud-free image, changes of histogram curves validated the algorithm. Scatterplots were generated and linear regression performed for the reflectance values of each band before and after the algorithm, and compared to those of the reference image. Band-by-band, results in cloud removal were acceptable. The algorithm had little effect on pixels in cloud-free areas after the analyses of histograms, scatterplots, and linear regression equations. Finally, the algorithm was applied to various land use and land cover types and cloud conditions, and to a full Landsat-8 scene yielding satisfactory results efficiently. View Full-Text
Keywords: cloud removal; independent component analysis (ICA); Landsat-8 OLI data cloud removal; independent component analysis (ICA); Landsat-8 OLI data

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Shen, Y.; Wang, Y.; Lv, H.; Qian, J. Removal of Thin Clouds in Landsat-8 OLI Data with Independent Component Analysis. Remote Sens. 2015, 7, 11481-11500.

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