Context: It is essential for policy-making and planning that we understand landscapes not only in terms of landscape ecological patterns, but also in terms of their contribution to people's quality of life. Objectives: In this study our objective is to test relationships between landscape ecology and social science indicators, by investigating how landscape patterns are linked to people’s perception of landscape quality. Methods: To assess public views on landscapes we conducted a survey among 858 respondents in Switzerland. We combined this survey data on perceived landscape quality and place attachment with landscape metrics (e.g. diversity, naturalness of land cover, urban sprawl, fragmentation) in a statistical model to test hypotheses about the relationships between the different variables of interest. Results: Our results illustrate the contribution of both landscape composition metrics and social science indicators to understanding variation in people’s perception and assessment of landscape. For example, we found the landscape ecology metrics on urban sprawl and fragmentation to be a negative predictor of overall satisfaction with landscape, and that perceived landscape quality positively predicted place attachment and satisfaction with the municipality landscape. Conclusions: This study highlights the importance and feasibility of combining landscape ecology metrics and public survey data on how people perceive, value and relate to landscape in an integrated manner. Our approach has the potential for implementation across a variety of settings and can contribute to holistic and integrated landscape assessments that combine ecological and socio-cultural aspects.

How do people perceive landscapes? What elements of the landscape do they identify as characteristic of a landscape? And how can we arrive at descriptions, and ultimately representations that better reflect people’s notions of landscapes? In this study, we collected landscape descriptions from five landscape types at 10 study sites in Switzerland. For each site, we collected data from three sources: free lists with participants, hiking blogs, and Flickr tags. Free lists were obtained through on-site interviews with visitors, hiking blogs were gathered by focused crawling of web content, and Flickr tags were selected based on spatial footprints obtained from the hiking blogs. We quantitatively compared landscape descriptions between data sources and landscape types using cosine similarity. We found that descriptions from the same data source were significantly more similar, irrespective of landscape type. Descriptions from the same landscape type were more similar, but only within the same data source. Through a qualitative analysis of different aspects of landscape in our content, we found that each data source offered a different distribution of landscape aspects. For example, while Flickr tags contained high proportions of toponyms, they contained little content relating to sense of place. In contrast, hiking blogs contained more information about sense of place. Our approach combining these varied textual sources thus offers a more holistic view on landscapes. This study constitutes a step toward extracting semantically rich descriptions of landscapes from a variety of sources and using this information to distinguish different landscapes, with potential applications for landscape monitoring and management.