An inversion algorithm based on the Classification and Regression Tree (CART) has been developed to retrieve sea ice from Moderate Resolution Imaging Spectroradiometer (MODIS) images in the Bohai Sea where the sea water is characterized by a high concentration of suspended sediment
in coastal areas. The inversion algorithm has been successfully applied to the sea-ice extraction from 2009 to 2012. The estimated sea ice is compared with previous studies and the comparison shows reasonable agreement. The model is further examined using sea-ice data from higher-spatial-resolution
satellites, and the result indicates that the CART method is able to successfully retrieve sea ice in high sediment environments in the Bohai Sea. To comprehensively understand the working principles of the CART, a series of sensitivity studies to model input parameters such as sampling locations,
the number of bands, and the effect of the thermal infrared band (TIB), was conducted. The sensitivity studies show that the CART method is easy to set up and the results are realistic. The TIB may play an important role in sea-ice inversion in turbid waters. The algorithm is also compared
with a ratio-threshold segmentation (RTS) method, a common way to retrieve sea ice from satellite images in open oceans, and the comparison indicates that the algorithm developed in the present article is superior to the RTS method in high sediment environments.
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Document Type: Research Article
School of Civil Engineering, Tianjin Chengjian University, Tianjin, 300384, China
Marine Ecosystem Section, Ocean and Ecosystem Sciences Division, Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada B2Y 4A2
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China
Publication date: March 19, 2015
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