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QUANTITATIVE METHODS FOR INVESTIGATING THE VARIABLES THAT UNDERLIE PREFERENCE FOR LANDSCAPE SCENES
Author(s) -
Pearce Stephen R.,
Waters Nigel M.
Publication year - 1983
Publication title -
canadian geographer / le géographe canadien
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.35
H-Index - 46
eISSN - 1541-0064
pISSN - 0008-3658
DOI - 10.1111/j.1541-0064.1983.tb00841.x
Subject(s) - grid , multidimensional scaling , basis (linear algebra) , terrain , elevation (ballistics) , sample (material) , principal component analysis , field (mathematics) , computer science , vegetation (pathology) , repertory grid , geography , cartography , artificial intelligence , physical geography , mathematics , psychology , geodesy , machine learning , medicine , social psychology , chemistry , geometry , chromatography , pathology , pure mathematics
A series of quantitative methods for investigating the basis for preference for landscape scenes was applied to photographs of alpine and subalpine landscapes in Alberta. The procedure incorporates a multidimensional scaling analysis with the repertory grid technique and also employs a property vector‐fitting algorithm as an aid in interpreting the dimensional solution. The preferences of a sample group were based on three criteria. In order of importance, these are character of vegetation cover, depth of field, and elevation of terrain. Additional validation of the results was obtained through a principal components analysis of the repertory grid data.