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Inspired by the narrative nature of Landscape Character Assessment (LCA), we present a complete workflow to (i) build a collection of almost 7000 online texts capturing first-person perception of the Lake District National Park in England, and (ii) analyse these for sight, sound and smell perception. We extract and classify more than 28,000 descriptions referring to sight, almost 1500 to sound and 78 to smell experiences using text analysis. The resulting descriptions can be explored for the whole Lake District revealing for example, how traffic noise intrudes on experiences in the mountains close to transportation axes. Linking descriptions to LCA areas allow us to compare properties of different regions in terms of scenicness or tranquillity at a macro-level by identifying, for example, LCA areas dominated by descriptions of tranquillity or anthropogenic sounds. At a micro-level, we can zoom in to individual descriptions and landscape elements to understand how particular places are experienced in context. Local experts gave positive feedback about the utility of such information as a monitoring tool complementary to existing approaches. Our method has potential for use both in allowing comparison over time and identifying emerging themes discussed in online texts. It provides a scalable way of collecting multiple perspectives from written text, however, more work is required to understand by whom, and why, these contributions are authored.

Maintenance of the agricultural landscape, preservation of biodiversity and landscape aesthetics are part of a multifunctional agriculture. However, little is known about the influence of single agricultural landscape elements in different seasonal stages on landscape aesthetics. In a Swisswide photo survey, the aesthetic preferences of Swiss residents for typical agricultural landscape elements in the Swiss lowlands were investigated. Photographs of seven ecological compensation areas (ECAs) and seven other elements (crops, high-intensity meadows and pastures) were selected. Each element was presented in four to six different seasonal stages, each on single paper-based questionnaire pages to allow a random selection of elements and seasonal stages. In addition, each element was replicated in each seasonal stage. Four randomly selected elements were sent to each study participant for aesthetic valuation (preference rating scores). Overall, ECAs received higher preference ratings than crops or high-intensity grassland. Most preferred were ECAs with a vertical structure, i.e. trees and bushes, and species-rich elements. In addition, the seasonal stage of a landscape element strongly influenced preference ratings. Flowering stages were clearly liked most. Moreover, perceived diversity and naturalness of an element had a strong positive effect on its rating. The results indicate that ECAs, besides their ecological function, are powerful elements to enhance the public's preference for agricultural landscapes. Moreover, the results might be useful for the development and adaptation of quantitative methods to capture the aesthetic value of agricultural regions and might provide a basis for political decisions concerning direct payments for aesthetic services of agriculture.