Mountain regions meet an increasing demand for pleasant landscapes, offering many cultural ecosystem services to both their residents and tourists. As a result of global change, land managers and policy makers are faced with changes to this landscape and need efficient evaluation techniques to assess cultural ecosystem services. This study provides a spatially explicit modelling approach to estimating aesthetic landscape values by relating spatial landscape patterns to human perceptions via a photo-based survey. The respondents attributed higher aesthetic values to the Alpine landscape in respect to areas with settlements, infrastructure or intensive agricultural use. The aesthetic value of two study areas in the Central Alps (Stubai Valley, Austria and Vinschgau, Italy) was modelled for 10,215 viewpoints along hiking trails according to current land cover and a scenario considering the spontaneous reforestation of abandoned land. Viewpoints with high aesthetic values were mainly located at high altitude, allowing long vistas, and included views of lakes or glaciers, and the lowest values were for viewpoints close to streets and in narrow valleys with little view. The aesthetic values of the reforestation scenario decreased mainly at higher altitudes, but the whole area was affected, reducing aesthetic value by almost 10% in Stubai Valley and 15% in Vinschgau. Our proposed modelling approach allows the estimation of aesthetic values in spatial and qualitative terms for most viewpoints in the European Alps. The resulting maps can be used as information and the basis for discussion by stakeholders, to support the decision-making process and landscape planning. This paper also discusses the role of mountain farming in preserving an attractive landscape and related cultural values.
This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 August 2020.
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#2,569,628
of 28,747,675 outputs
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#360
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#36,352
of 317,000 outputs
Outputs of similar age from Ecological Indicators
#2
of 31 outputs
Altmetric has tracked 28,747,675 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,004 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,000 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.
