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In recent years, Chinese cities have begun to pay attention to their rivers, and a large number of waterfront linear parks have been built in the riverside areas, so that the public can easily enjoy their landscape and entertainment functions. In this study, the visual quality of the waterfront trails and the greenbelt trails in the Waterfront line...
Citations
... As a result of their study in Shenyang China, Sun et al. (2021) stated that natural and formal features have a positive effect on visual quality, while man-made features have negative effects on visual quality. Similarly, Li et al. (2022) discussed the aesthetic value of the visual quality of the landscapes they created along the green axis by the river. ...
Although the landscape quality parameter in rural areas, which is called landscape beauty, varies according to the way the individual perceives the landscape, being able to perceive and understand the landscape visually in rural and urban landscape areas, natural and cultural tourism and recreation areas is directly related to whether that recreational area is used actively or not. This study aims to examine the effect of perceptual landscape parameters in touristic and recreational landscape character. In this study, it was investigated how the recreational and touristic landscape character can be emphasized with visual quality value. For this purpose, Gölbaşı Pond and its surroundings in Bursa in Turkey, which has a rich landscape character selected as study area, by evaluating the area’s visual landscape quality. The method of the study visual quality analysis was performed and the data obtained by visual quality analysis were compared. As a result, Gölbaşı Pond and its surroundings with its natural beauty and nature, as well as its landscape qualities suitable for recreational activities, provide opportunities for many recreational activities, and the study concluded that all landscape quality parameters support each other and create a potential for more.
... The water substrate gives waterfront spaces their unique landscape attributes. Hence, green visibility, blue visibility, openness, cleanliness, naturalness, and water-friendliness are the indicators that best represent the landscape characteristics of the waterfront space [28][29][30][31], as shown in Table 1. In this case, the green visibility and blue visibility were calculated from the percentage of the number of grids with the corresponding content after the pixelization of the panoramic photo. ...
Landscapes in urban waterfront spaces are of high societal value as they can meet people’s physical, psychological, and social needs for health and well-being, but the relationship between waterfront landscape features and public health benefits has yet to be clarified. From the perspective of blue health, this paper takes blue spaces along the Min River of Fuzhou City as the research object. It constructs the mediation model of “Waterfront landscape characteristic (WLC)→Water-friendly environmental preference (WEP)→Emotional benefit (EB)”. The role of WEP in the mechanisms linking WLC and EB in different waterfront spaces was explored through the quantification of indicators, questionnaires, and physiological measurements. The main results showed that (1) the ability of different types of waterfront spaces to arouse positive emotions in the population is characterized by blue-dominated space > co-dominated space > green-dominated space, while the opposite is true in terms of inducing negative emotions; (2) green visibility, blue visibility, naturalness, water-friendliness, and openness are all significantly related to EBs and could affect positive emotions either directly or mediated by WEPs, but openness seems not to affect negative emotions through WEPs; (3) cleanliness affects the population’s WEP for the coherence dimension, but has no significant role in improving EBs. This study could expand new ideas for research in habitat health, provide a reference for embodied evidence-based waterfront landscape design, and help promote the construction and development of healthy cities.
... Landscapes' visual quality is determined by how an observer values the elements of the surrounding environment through their perception, emotional and psychological processes [27]. The landscape's visual quality is based on the perceptual interaction between visitors and the landscape; hence, it can be subjectively quantified [28,29]. ...
The rural road landscape is crucial in forming rural areas’ landscape character (LC). As a platform for portraying the rural landscape, the rural roads demonstrate the area’s unique natural and cultural characteristics to visitors. However, with the continuous development of rural areas, the rural LC has been severely impacted, thus impacting visitors’ visual experience. In order to preserve and protect the rural landscape, this study aims to assess the visual quality of rural road landscapes based on public preference and heatmap analysis. The results indicated that most of the participants had a higher level of preference for rural landscapes with open horizontal views represented by agricultural areas, such as paddy fields. It was also found that different paddy field characters based on their planting stages can also positively affect the visual quality of rural road landscapes. The study also revealed that rural LCs with roadside settlements, commercial structures, mixed agricultural crops, and vegetation received low preference ratings. These characters negatively impact the visual quality of the rural road landscape. These findings provide significant insight for planners and decision-makers regarding protecting and preserving the essential rural road landscapes for the rural tourism experience.
... The SD method, also known as the semantic differential method, was proposed by Osgood in 1957(Osgood et al 1957. The SD method has been widely used in environment evaluation studies due to its better applicability (Sun et al 2021, Lyu et al 2022. The evaluation process of SD method usually involoves 20 to 50 observers who need a certain amount of professional knowledge. ...
Urban street walkability can effectively promote public health and the construction of livable cities. In addition, the coastal streets play a positive role in showing urban vitality and image. Due to the growing leisure needs of residents, measuring the visual walkability perception (VIWP) in urban streets and exploring the influence mechanisms of urban coastal street environments on VIWP have theoretical and practical significance. However, the methods of the previous walkability studies have limitations in terms of cost, time and measurement scale. Based on Google Street View Panoramic (GSVP) image data, this study used the semantic difference (SD) method with virtual reality (VR) technology to evaluate the VIWP of Fukuoka coastal streets. Meanwhile, the proportion of streetscape elements was extracted from GSVP images by semantic segmentation. The correlation and regression analyses were performed between the VIWP evaluation values and streetscape elements. Then, the regression model of the VIWP and the streetscape elements was established. The results showed that the natural features had a positive influence on VIWP in coastal streets. Correspondingly, trees were the strongest contribution rate for the VIWP, followed by shrubs, grasses and water, however, buildings and cars had a negative influence on VIWP. The method extends previous studies for measuring walkability, and optimization strategies were proposed to improve the visual quality of the coastal streets. It can be applied in the construction and management of walkable coastal street environments.
... These benefits include ecological, psychological, and social contributions, enhancing human well-being and urban livability (Tzoulas et al 2007, Kabisch et al 2015. In the context of urban landscape and design, these spaces incorporate various features such as parks, gardens, green roofs and walls, wetlands, rivers, canals, and ponds , Sun et al 2021. The conceptualization of blue-green spaces has evolved over the years, reflecting the growing understanding of their multidimensional benefits. ...
Urban blue-green spaces offer numerous environmental and social benefits to human beings. As these spaces vary by season, residents' preferences may also change. However, the seasonal differences in preferences and the factors influencing waterfront degree preferences in different seasons remain unclear. This study employs space syntax theory to measure the configurational attributes of blue-green spaces in Changhe Park, Dezhou, China, and utilizes a four-section questionnaire to investigate residents' preferences. The methods applied in this research include convex analysis, Mann-Whitney U test, and Spearman's rho correlation analysis. The main findings are fourfold: 1) park users predominantly consist of older, less educated, and lower-income individuals; 2) blue spaces have higher choice values than green spaces; 3) season significantly impacts waterfront preferences, with 21.8 % of respondents preferring high-degree waterfronts in summer, compared to 4.6 % in winter; 4) age group is the sole decisive factor for blue space preference in summer, while sex and time spent in the park contribute to winter preferences. These findings contribute to the understanding of seasonal preferences for urban blue-green spaces and inform planning and design strategies, such as targeting specific demographic groups or adjusting waterfront features to enhance year-round appeal.
... Both local and international academics have conducted a significant amount of research on the appraisal of water landscapes. The study primarily assesses the ecological role, aesthetic value, and humanistic expression of water landscapes in various regions, illuminating the relationships and rules between them (Yang, 2014;Cao, 2016;Lu et al., 2016;Huang et al., 2019;Sun et al., 2021;Ye et al., 2021;Xu et al., 2022;Wang et al., 2023). The waterfront greenway is a type of water landscape, and it is crucial to investigate how water bodies, buildings, and plants interact in space (Luo et al., 2023;Ren et al., 2023) as well as their ecological and humanistic benefits in order to support the development of spiritual civilization. ...
... beauty degree of the Tongjian Lake waterfront greenway were derived using multiple linear regression analysis and expert evaluation analysis, and based on this, a comparable optimization technique is suggested as a guide for creating future urban waterfront greenways. 2) Regarding the study of the beauty of the urban river and lake landscapes, the method of deriving landscape factors mostly relies on regression models (Sun et al., 2021;Xu, 2023), which are standard but not comprehensive enough. This paper combines the regression model with professional human evaluation to make a comprehensive judgment and comes up with the weight ranking of landscape factors, which fully considers the aesthetic judgment and subjective consciousness feelings. ...
In order to assess the unique beauty of Tongjian Lake in Hangzhou, 80 sample photographs were selected for landscape beauty degree assessment using the Scenic Beauty Estimation method. The 14 characteristic influencing factors of landscape photos were extracted according to the Scenic Beauty Estimation value, and the influencing factors with insignificant differences and small bias correlation coefficients were eliminated through multiple linear regression analysis. The results showed that the main factors affecting the expression of the beauty of Tongjian Lake were water ecology, greenway morphology, landscape openness, water area ratio, vegetation color richness, and vignette matching. Combining the abovementioned analysis results, the two-dimensional plan, isometric map, and three-dimensional space are combined to show the main factors in a visual way, and on this basis, the corresponding optimization strategy is proposed. It provides a reference for future urban waterfront greenway landscape creation.
... Waterfront linear parks are an integral element of the city's ecosystem and water supply, providing a place for people to relax, socialize, exercise, and share ideas. These parks also have special value for the city's ecology and economy (Sun et al., 2021). ...
... In contrast to the city center, the outlying districts have seen a major change in spatial heterogeneity and an increase in the fragmentation of the environment (Hong et al., 2011). The term "landscape visual quality" (LVQ) refers to the result of how various aspects of the landscape interact with the observer's cognitive, affective, and behavioral processes (Sun et al., 2021). Moreover, it is the degree to which an observer values a landscape for its aesthetic value. ...
... Moreover, it is the degree to which an observer values a landscape for its aesthetic value. According to Sun et al. (2021), the aesthetic value is determined by the relationship between ecological quality and visual quality, and this in turn is influenced by the ecology, diversity, vividness, and maintainability of the landscape. ...
... The visual information is more concentrated and focused on landscape elements that easily stimulate people's interest, such as lanterns, vignettes, flower boxes, notice boards, etc. The contrast between the white spaces and the details of the two types of spaces also creates more exploration opportunities for visitors [89]. ...
As an important part of rural space, the public space landscape has a positive influence on tourists and local residents, and also has an important guiding significance for the sustainable development of rural areas. This study expands the previous research on rural public space, taking the “user-oriented” landscape preference as an important entry point, taking Beijing rural public space as the research object, using eye-tracking technology to objectively reflect the degree of users’ preference for the landscape, making quantitative analysis through eye-tracking objective data and subjective satisfaction evaluation to explore the subconscious and aesthetic laws of the subjects, and summarizing the internal driving factors leading to its evolution from the summary of phenomena. This paper explores the visual behavior information and significance behind the “subjective space” created by the countryside for the users, intending to provide strategies for landscape optimization and the management of rural public space in an effort to aid the sustainable development of the countryside.
... Most studies on river landscapes mainly start from the perspective of the river bank (Sun et al., 2021;Xin et al., 2022). Researchers perform on-site observations and/or take photos for remote perception. ...
... However, such large-scale analysis based on land-use types can only obtain the general spatial characteristics of river corridors, rather than the visual perceptions of human beings. To visually examine the spatial surroundings, some researchers used static discontinuous human perspective photographs to obtain multi-dimensional remote impression of aspects such as beauty, vitality, and ecology of urban rivers, lakes, and other waterscapes (Sun et al., 2021;Yamashita, 2002;Pflüger et al., 2010). These studies provide a reference for people to comprehend the distribution features of river space and landscape elements by objectively describing the visual characteristics of relevant places. ...
Gathering knowledge about physical settings and visual information of places has long been of interest to a wide variety of fields as they affect the experience of observers. Previous studies have relied on on-site surveys, low-throughput methods, and limited data sources, which especially hinder analyzing waterscape features. Thus, detecting the relationships between the human perception results of large-scale urban water areas and the waterfront features at high spatial resolutions remains challenging, and worldwide studies have not been conducted. We investigate an alternative: a data-driven waterscapes evaluation approach based on computer vision (CV) to analyze water view imagery (WVI) in 16 cities around the world and measure how people perceive scenes using virtual reality (VR). We bring attention to WVI – the counterpart of street view imagery (SVI) on water bodies, which is readily available for many cities thanks to the usual SVI services, but has been entirely overlooked in research hitherto. Specifically, a deep learning model, which has been trained with 500 segmented water-level photos, was developed to analyze them, achieving the mean pixel accuracy (MPA) of 94%, which advances state of the art. These panoramic images have been assessed through a virtual experience survey in which 60 participants indicated their perceptions across multiple dimensions. Afterwards, a series of statistical analyses were conducted to determine the visual indicators that drive perceptions, and the relationship between the people’s subjective visual perceptions and objective waterscape environment as seen by machines has been established. The results take researchers and watercourse planners one step toward understanding the interactions of the perceptions and semantics of water areas globally. The large-scale dataset we produced in this research has been released openly as the first such instance of open segmented water view imagery, and it is intended to support future studies.
... It is a type of (Wright 2015). The SD is universally applicable in semantic rating scale that captures the affective and cognitive components of respondents' attributions to selected concepts environment, landscape and architecture researches (Kang and Zhang 2010, Cao et al 2020, Li et al 2021, Sun et al 2021. ...
... It is a type of (Wright 2015). The SD is universally applicable in semantic rating scale that captures the affective and cognitive components of respondents' attributions to selected concepts environment, landscape and architecture researches (Kang and Zhang 2010, Cao et al 2020, Li et al 2021, Sun et al 2021. ...
The coastal streets are the most attractive urban space, improving spatial quality and public perception of coastal streets is an important work of urban regeneration. The study used machine learning semantic segmentation, GIS and Semantic difference (SD) etc methods to obtain the spatial data and perceptual evaluation of coastal streets in Qingdao. Each of the six perceptual features, imageability, enclosure, human scale, transparency, complexity and nature, was taken as dependent variables and the corresponding physical features was taken as independent variables. The six regression models were established and the influence rules of spatial parameters on public perception were obtained. Meanwhile, based on the results of perceptual features evaluation, the overall coastal streets are divided into three types, open streets, mixed streets and biophilic streets. In all the three types coastal streets, the nature was the most significant perceptual feature due to the high greenness; the complexity was the lowest perceptual feature because of the low landscape diversity. The research results provided theoretical and technical support for the urban regeneration and spatial quality improvement of coastal streets in Qingdao.
