Choice modelling to describe qualities explaining visual landscape quality

Authors and Affiliations: 

Beatrice Schüpbach1, Philippe Jeanneret1, Matthias Albrecht1, Louis Sutter1, Sören Weiss2 and Oliver Frör2

1Agroscope Agricultural Landscape and Biodiversity, 8046 Zürich, Switzerland
2Institute for Environmental Economics, University Koblenz-Landau, 76829 Landau, Germany

Corresponding author: 
Beatrice Schüpbach, Agroscope, Switzerland

In the EU project QuESSA (quantifying ecological services for sustainable agriculture, ( the ecosystem service delivery of woody and grassy semi-natural habitats for pollination and pest predation were determined in eight European countries (UK, Netherlands, Germany, France, Italy, Hungary, Estonia and Switzerland). The impact of grassy and woody semi-natural habitats on the quality of the visual landscape was estimated as an additional service.
Several studies have shown that semi-natural habitats (SNH) are preferred to conventional crops(Klein et al., 2015; Strumse, 1994). However, results based on a few studies cannot be applied over the whole Europe as landscape preference is also influenced by socio-cultural factors. Furthermore, the SNH characteristics may distinctly variate across Europe.
Pictures comprising crop-crop, crop-grassy, crop-woody and crop-grassy-woody combinations were showed to participants in six European countries (UK, D, F, I HU and CH) using an online panel-based questionnaire.
The four pairs of combinations were presented in a set of four pictures. Participants had to rank two series of three or four sets of pictures according to their preference (rank 1 for the most preferred, rank 4 for the least preferred picture). The sets of pictures differed in their seasonal appearance. The two series varied in the crop type and the quality of the SNH.
The survey provided answers of 350 participants for each country, which were representative with respect to sex, age and education.
First analyses show that SNH basically have a positive influence on the visual preference of participants for the landscape. This however, is strongly influenced by the characteristics of the SNH but also the crop occurring in the picture. The fact however, that also crop land use can positively influence the preference, suggests, that characteristics behind the depicted elements could explain the preferences.
In a first step characteristics describing all elements for all countries were established in order to include them in a choice Model. Choice models enable to evaluate the utility of characteristics of a certain item (e.g. car) for a potential user (Louiviere et al., 2000). In this case it is applied on landscape preference.
First analyses of the Swiss datasets show that characteristics like ‘colourful’, presence or absence of dry vegetation have a positive respectively a negative impact on the preference of the combination. In a second step these characteristics and models should be applied on the datasets of the remaining countries, in order to find out, if these characteristics are generally applicable across the European countries.
Finding such general characteristics would have several advantages: it would enable farmers or landscape managers to define landscape quality independently from land-use types. Furthermore, it would make it easier to predict the effects of elements newly introduced in the landscape on landscape preference.

Beatrice Schüpbach acknowledges the receipt of a fellowship from the OECD Co-operative Research Programme: Biological Resource Management for Sustainable Agricultural Systems in 2015 to work on this project


Klein, L.R., Hendrix, W.G., Lohr, V.I., Kaytes, J.B., Sayler, R.D., Swanson, M.E., Elliot, W.J., Reganold, J.P., 2015. Linking ecology and aesthetics in sustainable agricultural landscapes: Lessons from the Palouse region of Washington, U.S.A. Landscape and Urban Planning 134, 195-209.
Louiviere, J., Hensher, D.A., Swait, J.D., 2000. Stated choice methods: analysis and application., in: Press, C.U. (Ed.), Cambridge, UK.
Strumse, E., 1994. Environmental Attributes and the prediction of visual preferences for Agrarian Landscapes in Western Norway. Environmental Psychology 14, 203-303.

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