Predicting scenic beauty of mountain regions

Scenic beauty of mountain landscapes contributes to human well-being. Valuation of natural scenery and specific landscape properties by perception studies is complex and time-consuming. Sophisticated spatial analysis tools can support the assessment of scenic beauty by quantitative methods. We implemented an innovative GIS-based modeling approach for mountain regions which combines objective methods with perception-based methods. Based on viewpoints, spatial patterns of visible landscape were analyzed by means of landscape metrics. A set of 60 landscape metrics were reduced by principal component analysis (PCA) to 11 components explaining 93% of the variance. The components were related to perceived scenic beauty values found through a perception study via stepwise regression analysis. We found that two components, shape complexity and landscape diversity, are positively related to visual quality (R2 = 0.72). In the Central Alps, especially areas above the tree line are characterized by high scenic beauty. Abandonment of agriculturally used areas implies a loss of scenic beauty, mainly in the valley bottom and in the subalpine forest belt, as a result of urban sprawl and natural reforestation. The GIS-based model offers a valid instrument for scenic beauty assessments of mountain regions as a basis for policy making and landscape planning.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Developed method allows predicting scenic beauty of mountain regions. ► Good prediction of scenic beauty (R2 = 0.72). ► Near zone contributes to scenic beauty by 48%. ► Method can be used for decision making and landscape planning.