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Wavelet analysis for detecting anisotropy in point patterns
Author(s) -
Rosenberg Michael S.
Publication year - 2004
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/j.1654-1103.2004.tb02262.x
Subject(s) - quadrat , wavelet , point pattern analysis , point (geometry) , anisotropy , field (mathematics) , computer science , spatial analysis , spatial ecology , pattern recognition (psychology) , common spatial pattern , data mining , algorithm , mathematics , artificial intelligence , statistics , ecology , physics , geometry , optics , shrub , pure mathematics , biology
Although many methods have been proposed for analysing point locations for spatial pattern, previous methods have concentrated on clumping and spacing. The study of anisotropy (changes in spatial pattern with direction) in point patterns has been limited by lack of methods explicitly designed for these data and this purpose; researchers have been constrained to choosing arbitrary test directions or converting their data into quadrat counts and using methods designed for continuously distributed data. Wavelet analysis, a booming approach to studying spatial pattern, widely used in mathematics and physics for signal analysis, has started to make its way into the ecological literature. A simple adaptation of wavelet analysis is proposed for the detection of anisotropy in point patterns. The method is illustrated with both simulated and field data. This approach can easily be used for both global and local spatial analysis.