Predicting the scenic beauty value of mapped landscape changes in a mountainous region through the use of GIS
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2007-01-01
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Environment and planning. B: Urban analytics and city science
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SAGE PUBLICATIONS LTD
Melbourne Authors
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Geomatics
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Journal Article
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GrĂȘt-Regamey, A., Bishop, I. D. & Bebi, P. (2007). Predicting the scenic beauty value of mapped landscape changes in a mountainous region through the use of GIS. Environment and Planning B Planning and Design, 34 (1), pp.50-67. https://doi.org/10.1068/b32051.
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C1 - Journal Articles Refereed
Abstract
Planning frequently fails to include the valuation of public goods, such as scenic beauty. This can lead to negative economic impacts for a region over the longer term. Especially in mountainous regions such as the Alps in central Europe, which depend on tourist income, the change of landscape views through the development of facilities for recreation and tourism may negatively affect the tourism experience, and hence the economy. In this study we present a prototypical technique to predict preferences for views using geographic information system (GIS)-based variables. A three-dimensional GIS including the effects of slope, aspect, and distance, as well as the height of landscape features, is developed to calculate the proportion of land-cover areas that make up the view. A Web-based survey is used to gather data on scenic preferences for landscape changes in the region around Davos (Switzerland). Willingness-to-pay (WTP) responses are used to identify preferred landscapes. A forced-choice questionnaire asks participants to compare pairs of landscape photographs. Two original pictures were digitally altered to visually represent landscape change scenarios developed for the study area. The visual magnitudes of the different land-cover areas are found to be correlated with the WTP values expressed by the respondents. The relationship is used to predict changes in scenic values for another view in the region. The approach presented in this paper could be useful in regional planning to estimate the influence of view components on people's preferences.
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Spatial Information Systems; Other