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Chen, Shuguo; Zhang, Tinglu (2015). An improved cloud masking algorithm for MODIS ocean colour data processing. REMOTE SENSING LETTERS, 6(3), 218-227.

Abstract
Cloud cover is one major obstacle to obtaining an accurate ocean colour signal by satellite remote sensing methods. Identifying the cloud pixels correctly is of great importance for satellite ocean colour data processing. Several cloud masking algorithms currently exist: near infrared threshold, shortwave infrared threshold, spatial variability threshold, and spectral variability threshold. Any of these algorithms can identify nearly all of the real cloud pixels. However, the influence of turbid waters, turbidity fronts, aerosols, and sunglint causes some amount of non-cloud pixels to be mistaken as clouds. This situation inevitably leads to the loss of valuable data. After reviewing these current approaches, this study proposes an improved cloud masking algorithm for the Moderate Resolution Imaging Spectroradiometer, which is based on the high spatial variability characteristic of clouds, as well as the small contribution from water reflection at shortwave bands. The new cloud masking algorithm reduces the influence of turbid waters, turbidity fronts, aerosols, and sunglint, although some high-gradient glint pixels are still misclassified as clouds.

DOI:
10.1080/2150704X.2015.1026955

ISSN:
2150-704X

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