Explaining landscape preference heterogeneity using machine learning-based survey analysis
| Autor: | Xiaozi Liu, Endre Tvinnereim, Henrik Lindhjem, Hanna Lee, Heidi Iren Saure, Liv Guri Velle, Kristine Grimsrud |
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| Rok vydání: | 2021 |
| Předmět: |
business.industry
05 social sciences Geography Planning and Development 0211 other engineering and technologies 0507 social and economic geography Preference heterogeneity 021107 urban & regional planning 02 engineering and technology Management Monitoring Policy and Law The Internet Psychology business 050703 geography Nature and Landscape Conservation General Environmental Science Cognitive psychology |
| Zdroj: | Landscape Research |
| ISSN: | 1469-9710 0142-6397 |
| Popis: | 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. publishedVersion |
| Databáze: | OpenAIRE |
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