Classification of recreational boat types based on trajectory patterns

Spatial pattern analysis of recreational boating has become increasingly important because of the growing popularity of recreational boating activity and the magnitude of its associated risks. The nature of recreational boating movements provides useful input for risk analyses. However, there are no known pattern analyses which explore the difference in the movement characteristics across boat types. This study developed an innovative procedure to recognize spatial patterns in this area. Samples of recreational boating GPS trajectory points for four types of boats were collected in two environments. Using discriminant analysis, a classification model can group the different boat types based strictly on their trajectories. The outcome of this study is valuable for recreational boating traffic analysis, as well as coastal security.

[1]  R. Fisher THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[2]  Michael H. Kutner Applied Linear Statistical Models , 1974 .

[3]  Sidney Marks,et al.  Discriminant Functions When Covariance Matrices are Unequal , 1974 .

[4]  Kim Peterson The Delineation of Recreational Boating Markets: a Multivariate Approach , 1991 .

[5]  J. Vaske,et al.  Degree and Range of Recreation Specialization: Toward a Typology of Boating Related Activities , 1986 .

[6]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[7]  Philip Groff,et al.  Will it Float? Mandatory PFD Wear Legislation in Canada , 2003 .

[8]  D. English,et al.  A Crowding-based Model of Social Carrying Capacity: Applications For Whitewater Boating Use , 1996 .

[9]  Yan. Wu Characterizing recreational boating patterns based on GPS trajectory points. , 2007 .

[10]  Berith F. Jensen,et al.  Classification of Membrane Permeability of Drug Candidates: A Methodological Investigation , 2005 .

[11]  W. J. Spillane,et al.  Development of structure-taste relationships for monosubstituted phenylsulfamate sweeteners using classification and regression tree (CART) analysis. , 2005, Journal of agricultural and food chemistry.

[12]  Terence J. O'Neill Error rates of non-Bayes classification rules and the robustness of Fisher's linear discriminant function , 1992 .

[13]  Ray R. Hashemi,et al.  Pattern development for vessel accidents: a comparison of statistical and neural computing techniques , 2001, Expert Syst. Appl..

[14]  J. Hair Multivariate data analysis , 1972 .