Super-resolution optical mapping of floating macroalgae from geostationary orbit

The spatial resolution of an observation from a geostationary orbiting satellite is usually too coarse to track small scale macroalgae blooms. For macroalgae mapping to benefit from a geostationary orbit's staring monitoring and frequent revisit intervals, we introduced a super-resolution metho...

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Bibliographic Details
Published in:Applied optics (2004) 2020-04, Vol.59 (10), p.C70
Main Authors: Cui, Tingwei, Li, Feng, Wei, Yunhong, Yang, Xue, Xiao, Yanfang, Chen, Xiaoying, Liu, Rongjie, Ma, Yi, Zhang, Jie
Format: Article
Language:English
Subjects:
Algae
Environmental Monitoring - methods
Geography
Geosynchronous orbits
Image contrast
Image Processing, Computer-Assisted
Image quality
Image resolution
Mapping
Meteorological satellites
Models, Theoretical
Optical Imaging - methods
Patches (structures)
Satellite tracking
Seaweed - metabolism
Signal to noise ratio
Spatial resolution
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Summary:The spatial resolution of an observation from a geostationary orbiting satellite is usually too coarse to track small scale macroalgae blooms. For macroalgae mapping to benefit from a geostationary orbit's staring monitoring and frequent revisit intervals, we introduced a super-resolution method that reconstructs a high-resolution (HR) image of a region from a sequence of raw geostationary low-resolution images of the same region. We tested our method with GF-4 images at 50 m spatial resolution and demonstrated that the spatial resolution increased to 25 m. In addition, the derived HR image had better image quality characterized by a higher signal-to-noise ratio, clarity, and contrast. The increased spatial resolution and improved image quality improved our ability to distinguish macroalgae patches from the surrounding waters, especially tiny patches of macroalgae, and to precisely delineate the patch boundaries. Lastly, we more accurately estimated the areal coverage of the patches by reducing underestimation of the coverage of tiny patches and overestimation of the coverage of large patches.
ISSN:1559-128X
2155-3165
DOI:10.1364/AO.382081