Abstract
Cloud component removal for shallow water depth retrieval with multi-spectral satellite imagery
Highlights
The water depth and underwater topography are essential geospatial information for coastal engineering, aquaculture, fishing industry, and other marine applications
This study considers the effect of cloud abundance and utilizes linear un-mixing for the cloud component removal for improving the quality of depth retrieval
The depth retrieval scheme proposed in this study includes cloud component removal with linear un-mixing algorithm
Summary
The water depth and underwater topography are essential geospatial information for coastal engineering, aquaculture, fishing industry, and other marine applications. The bathymetry lidar determines the water depth from green and near-infrared lasers These two lasers are used for collecting waveform features from sea floor and sea surface, respectively. Features means a large coverage at a lower cost Disadvantages of this method include lower accuracy and a limited depth range, valuable information for understanding the sea bottom topography that is likely complimentary to the traditional acoustic sounding techniques can still be gathered. For these optical images, cloud and haze are common sources of disturbance. Both the neural network and semi-analytical modeling schemes are applied
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