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. 2009 Jul;90(9):2889-99.
doi: 10.1016/j.jenvman.2007.10.016. Epub 2008 Oct 23.

Cognitive attributes and aesthetic preferences in assessment and differentiation of landscapes

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Cognitive attributes and aesthetic preferences in assessment and differentiation of landscapes

Marjanne Sevenant et al. J Environ Manage. 2009 Jul.

Abstract

The increasing pace and scale of landscape changes involve objective measurements in order to estimate the effects of changes on people's landscape preferences in a meaningful way. In the literature, some attempts have been made to provide a more conceptual base related to landscape preferences. These concepts and their indicators need to be tested empirically in different contexts and landscape types. In the present study, different items related to theoretical concepts of both aesthetic preference and cognitive rating were examined. They were combined in an in situ questionnaire, which was conducted among undergraduate students in geography during two different field excursions. Stimuli consisted of 11 landscape vistas selected during the excursions. All vistas represent rather rural landscapes but they vary with regard to relief, degree of urbanisation, and degree of agricultural land use. Statistical analysis of all data yielded significant correlations between aesthetic and cognitive ratings. However, these correlations did not appear to be very strong. When considering landscape vistas separately, the relations between all cognitive ratings seemed to vary. Further, not all cognitive aspects had an equal predicting value for aesthetic preference. Moreover, this predicting value appeared to vary between different landscape vistas. The groups of interrelated cognitive aspects could not be associated consistently with theoretical concepts. The results demonstrated the inconsistencies existing between the contents of the theoretical concepts and the indicators found within the landscape. The findings argued for the necessity to distinguish between different ratings and landscape types instead of using unitary preference measures and generalized data when studying landscape preference.

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