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|Title:||CBR spatial similarity analysis on mesoscale ocean eddies with remote sensing data|
Case-Based Reasoning (CBR)
Spatial similarity, Radius Vector Serial Analysis Model Based on Barycentre (RVSAMB)
|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.|
|Appears in Collections:|| IJMS Vol.33(4) [December 2004]|
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