The impact of landscape complexity on preference ratings and eye fixation of various urban green space settings

Potential of eye-tracking simulation software for analyzing landscape preferences

“…The identified hotspots mostly contained single trees and tree trunks, buildings and horizon transitions, which corroborates the results of other studies [ 86 , 87 ]. Other elements such as glaciers, snowfields and rocks were also often included in the hotspots, representing all elements with a high degree of naturalness, which are generally preferred over artificial elements [ 26 , 33 , 47 ]. In contrast to other studies [ 47 , 86 ], single artificial elements (e.g., fences, street signs, cars) or individual natural elements (e.g., plant leaves, single stones) were hardly tracked in our study, which may be because certain elements such as benches are more in the focus of people’s interests and therefore more recognized in real eye-tracking experiments [ 87 ].…”

“…Landscape preferences can depend on the quality and distribution of the "interesting" objects [ 33 , 55 , 86 ], but frequently viewed elements indirectly contribute to the perception process, as the observer forms an opinion about these hotspots. For example, Cottet et al (2018) found that observers mentioned the same objects that were in the hotspots when describing their motivations for judging a landscape.…”

“…For this purpose, panoramic photographs are considered useful stimuli to holistically depict the surrounding landscape [ 28 , 29 ], as they are easier to recognize and memorize and therefore the responses are more adequate and detailed than for standard photographs [ 30 ]. To understand and map aesthetic landscape values, researchers have related landscape preferences to visual landscape characteristics and spatial patterns [ 24 , 25 , 31 – 33 ]. Such studies revealed, for example, that mean levels of diversity and complexity are generally preferred over highly complex or homogeneous patterns [ 26 , 33 , 34 ] or that landscape openness is positively related to landscape preferences, which can be measured through visibility metrics [ 25 ].…”

“…To understand and map aesthetic landscape values, researchers have related landscape preferences to visual landscape characteristics and spatial patterns [ 24 , 25 , 31 – 33 ]. Such studies revealed, for example, that mean levels of diversity and complexity are generally preferred over highly complex or homogeneous patterns [ 26 , 33 , 34 ] or that landscape openness is positively related to landscape preferences, which can be measured through visibility metrics [ 25 ]. There is also a growing body of literature using novel approaches and new data sources such as social media data to identify landscape preferences and the level of aesthetic value [ 16 , 18 , 28 , 35 , 36 ].…”

“…For example, eye-tracking experiments were used to examine landscape perceptions in relation with the level of openness and heterogeneity in rural landscapes [ 30 ] as well as different levels of urbanization and visual complexity along a rural-urban gradient [ 44 ]. Other studies focused on the beauty of natural environments, e.g., forests [ 38 , 45 – 47 ], underwater reefs [ 48 ] or lakescapes [ 49 ] as well as visual preferences in urban environments and urban green spaces, e.g., [ 33 , 50 – 55 ]. Eye-tracking experiments can also support the understanding individual’s perceptions and cognitive processes for decision-making related to landscape and ecosystem service planning as shown for mountain landscapes [ 21 ] and forest landscapes [ 47 ].…”