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Relationships between visual landscape preferences and map-based indicators of landscape structure [An article from: Landscape and Urban Planning]
Book Details
PublisherElsevier
ISBN / ASINB000PBZWQG
ISBN-13978B000PBZWQ2
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Landscape and Urban Planning, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
There is increasing awareness of the need to monitor trends in our constantly changing agricultural landscapes. Monitoring programmes often use remote sensing data and focus on changes in land cover/land use in relation to values such as biodiversity, cultural heritage and recreation. Although a wide range of indicators is in use, landscape aesthetics is a topic that is frequently neglected. Our aim was to determine whether aspects of landscape content and configuration could be used as surrogate measures for visual landscape quality in monitoring programmes based on remote sensing. In this paper, we test whether map-derived indicators of landscape structure from the Norwegian monitoring programme for agricultural landscapes are correlated with visual landscape preferences. Two groups of people participated: (1) locals and (2) non-local students. Using the total dataset, we found significant positive correlations between preferences and spatial metrics, including number of land types, number of patches and land type diversity. In addition, preference scores were high where water was present within the mapped image area, even if the water itself was not visible in the images. When the dataset was split into two groups, we found no significant correlation between the preference scores of the students and locals. Whilst the student group preferred images portraying diverse and heterogeneous landscapes, neither diversity nor heterogeneity was correlated with the preference scores of the locals. We conclude that certain indicators based on spatial structure also have relevance in relation to landscape preferences in agricultural landscapes. However, the finding that different groups of people prefer different types of landscape underlines the need for care when interpreting indicator values.
Description:
There is increasing awareness of the need to monitor trends in our constantly changing agricultural landscapes. Monitoring programmes often use remote sensing data and focus on changes in land cover/land use in relation to values such as biodiversity, cultural heritage and recreation. Although a wide range of indicators is in use, landscape aesthetics is a topic that is frequently neglected. Our aim was to determine whether aspects of landscape content and configuration could be used as surrogate measures for visual landscape quality in monitoring programmes based on remote sensing. In this paper, we test whether map-derived indicators of landscape structure from the Norwegian monitoring programme for agricultural landscapes are correlated with visual landscape preferences. Two groups of people participated: (1) locals and (2) non-local students. Using the total dataset, we found significant positive correlations between preferences and spatial metrics, including number of land types, number of patches and land type diversity. In addition, preference scores were high where water was present within the mapped image area, even if the water itself was not visible in the images. When the dataset was split into two groups, we found no significant correlation between the preference scores of the students and locals. Whilst the student group preferred images portraying diverse and heterogeneous landscapes, neither diversity nor heterogeneity was correlated with the preference scores of the locals. We conclude that certain indicators based on spatial structure also have relevance in relation to landscape preferences in agricultural landscapes. However, the finding that different groups of people prefer different types of landscape underlines the need for care when interpreting indicator values.
