Assessment of landscape aesthetics—Validation of a landscape metrics-based assessment by visual estimation of the scenic beauty

Abstract

The assessment of cultural ecosystem services, in our case landscape aesthetics, is the most commonly investigated but least formalized issue in the scope of the ecosystem services concept. In contrast to ecological or economic aspects, the assessment of aesthetics cannot easily be based on quantitative information. Therefore, two different methodological approaches that assess landscape aesthetics either from an objective or a subjective point of view have been established in the past.This article presents in its first part an objective, landscape metrics-based assessment approach. We defined naturalness and landscape diversity as assessment criteria and selected Shannon's Diversity Index (SHDI), Shape Index (SHAPE) and Patch Density (PD) as indicators. We tested our approach for a set of nine different landscape types in a model region in Saxony, Germany.For validating the developed methodology, we carried out a survey with 153 participants in order to investigate their subjective preferences for the different landscape types. These preferences had to be expressed by rating the landscape types on a scale from 1 (very ugly) to 5 (very beautiful). The study was based on three different data sets, namely photographs of the landscape types, satellite images, and land cover maps.Statistical tests were applied (a) to investigate the impact of personal factors on the ratings, (b) to detect whether abstraction levels are suitable for preference studies, and (c) to compare the results of the objective approach (landscape metrics) and the subjective approach (visual assessment). Personal factors did not influence the visual assessment results significantly. We found the highest correlation of the landscape metrics-based assessment with the visual assessment results of the photographs. We conclude that the three landscape metrics might be applied to the monitoring of landscape aesthetics. An extended study with more participants might be useful to further investigate the reliability of our findings.