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Explaining landscape preference heterogeneity using machine learning-based survey analysis
We conducted a national survey on a high-quality internet panel to study landscape preferences in Norway, using photos as stimuli. We examined preference heterogeneity with respect to socio-demographic characteristics and latent topics brought up by the respondents, using ordinal logistic regression and structural topic modelling (STM), a machine learning-based analysis. We found that pasture landscapes are the most favoured (55%), while densely planted spruce forests are the least favoured (8%). The contrast was particularly strong between eastern and western Norway, between men and women, and between young and old. STM revealed that the choices were mainly driven by the preference for landscape openness, especially by women. Other important drivers were concerns regarding reforestation of former farmlands, aesthetic properties, forest management, biodiversity issues, and cultural values. Our results suggest that landscape policies may clash with socio-cultural preferences, and failure to account for these may undermine the success of a policy.
Explaining landscape preference heterogeneity using machine learning-based survey analysis
We conducted a national survey on a high-quality internet panel to study landscape preferences in Norway, using photos as stimuli. We examined preference heterogeneity with respect to socio-demographic characteristics and latent topics brought up by the respondents, using ordinal logistic regression and structural topic modelling (STM), a machine learning-based analysis. We found that pasture landscapes are the most favoured (55%), while densely planted spruce forests are the least favoured (8%). The contrast was particularly strong between eastern and western Norway, between men and women, and between young and old. STM revealed that the choices were mainly driven by the preference for landscape openness, especially by women. Other important drivers were concerns regarding reforestation of former farmlands, aesthetic properties, forest management, biodiversity issues, and cultural values. Our results suggest that landscape policies may clash with socio-cultural preferences, and failure to account for these may undermine the success of a policy.
Explaining landscape preference heterogeneity using machine learning-based survey analysis
Liu, Xiaozi (author) / Tvinnereim, Endre (author) / Grimsrud, Kristine M. (author) / Lindhjem, Henrik (author) / Velle, Liv Guri (author) / Saure, Heidi Iren (author) / Lee, Hanna (author)
Landscape Research ; 46 ; 417-434
2021-04-03
18 pages
Article (Journal)
Electronic Resource
Unknown
Explaining landscape preference heterogeneity using machine learning-based survey analysis
| BASE | 2021
Explaining landscape preference heterogeneity using machine learning-based survey analysis
| BASE | 2021
Creating Landscape Preference Models Using Internet Survey Techniques
| Taylor & Francis Verlag | 2000
Creating Landscape Preference Models Using Internet Survey Techniques
| British Library Online Contents | 2000
Creating Landscape Preference Models Using Internet Survey Techniques
| Online Contents | 2000