4.7 Article

Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images

期刊

REMOTE SENSING OF ENVIRONMENT
卷 159, 期 -, 页码 269-277

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2014.12.014

关键词

Fmask; Cloud; Cloud shadow; Snow; Landsat; Sentinel; Cirrus

资金

  1. USGS [G11PS00422]
  2. NASA Earth Science U.S. [NNX11AE18G]

向作者/读者索取更多资源

Identification of clouds, cloud shadows and snow in optical images is often a necessary step toward their use. Recently a new program (named Fmask) designed to accomplish these tasks was introduced for use with images from Landsats 4-7 (Zhu & Woodcock, 2012). In this paper, there are the following: (1) improvements in the Fmask algorithm for Landsats 4-7; (2) a new version for use with Landsat 8 that takes advantage of the new cirrus band; and (3) a prototype algorithm for Sentinel 2 images. Though Sentinel 2 images do not have a thermal band to help with cloud detection, the new cirrus band is found to be useful for detecting clouds, especially for thin cirrus clouds. By adding a new cirrus cloud probability and removing the steps that use the thermal band, the Sentinel 2 scenario achieves significantly better results than the Landsats 4-7 scenario for all 7 images tested. For Landsat 8, almost all the Fmask algorithm components are the same as for Landsats 4-7, except a new cirrus cloud probability is calculated using the new cirrus band, which improves detection of thin cirrus clouds. Landsat 8 results are better than the Sentinel 2 scenario, with 6 out of 7 test images showing higher accuracies. (C) 2014 Elsevier Inc All rights reserved.

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