Please use this identifier to cite or link to this item:
Title: CBR spatial similarity analysis on mesoscale ocean eddies with remote sensing data
Authors: Du, Yunyan
Li, Ce
Su, Fenzhen
Zhang, Tianyu
Yang, Xiaomei
Keywords: Mesoscale eddy;Case-Based Reasoning (CBR);Spatial similarity, Radius Vector Serial Analysis Model Based on Barycentre (RVSAMB)
Issue Date: Dec-2004
Publisher: CSIR
Abstract: Ocean eddy Case-Based Reasoning (CBR) is developed and extended to the spatial-tempo domain in this paper to extract ocean eddy spatial similarity information in a quantificational manner, which can be very difficult to acquire using current routine eddy feature recognition and analysis algorithms. Present work includes three basic steps. First, information about the eddy’s spatial structure and attributes is obtained from the original remote sensing data. Then a library of historical eddy cases is built using the cases’ expression models. Finally, a Radius Vector Serial Analysis Model Based on Barycentre (RVSAMB) is provided to analyse the spatial similarity between the historical cases for further forecasting and dynamic analysis. In this study, a new quantitative method to analyse and extract ocean mesoscale eddy information using Case-based Reasoning is presented. Firstly, a historical ocean eddy case library was constructed based on the specific expression model. Then, the sketch of this method is discussed in detail, especially the similarity assessment method—“Radius Vector Serial Analysis Model Based on Barycentre”. Finally, a mesoscale warm eddy example in the Gulf Stream of the North Atlantic indicated that this is a feasible way to analyse ocean eddies.
Page(s): 319-328
ISSN: 0379-5136
Appears in Collections: IJMS Vol.33(4) [December 2004]

Files in This Item:
File Description SizeFormat 
IJMS 33(4) 319-328.pdf1.21 MBAdobe PDFView/Open

Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.