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 linear Park around the Hunhe river in Shenyang was evaluated the basis of the Scenic Beauty Estimation Method and Semantic Differential Method, and the principal components of the landscape characteristics were extracted and a regression model of the visual quality and the landscape characteristics was established. Results show that the natural feature and the formal feature have a positive influence on the visual quality in waterfront linear parks, and the man-made feature has a negative impact on the visual quality. The six landscape characteristics are Sense of seclusion, ecology, intactness, uniqueness, unity and vitality, which are the main factors which affect the visual quality. This study puts forward improvement measures for the waterfront trails and the greenbelt trails, and the results can be applied to the planning, construction, and management of waterfront linear parks.

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.

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.

With the rapid development of urbanization in China, the urban complex with a public transportation-oriented development (TOD) meets people's needs in living space, however, its characteristics of large building volumes and complex space make it difficult for people to find their destination in the urban complex. The signage system is regarded as the main medium of communication between people and the spatial environment and also has a significant impact on pedestrian way-finding. In order to investigate the influence of the signage types and signage carriers location on people's way-finding, we designed a series of way-finding experiments in the study, Among them the forecast variables are organized into two types in the questionnaire design: signage types and location of the signage carriers. The results indicated that pedestrians pay more attention to directional and illustrative signs in the TOD commercial centre, they hope the signage carriers could be placed in crowded areas, such as escalators and central courtyard. In addition, signs and side signs identification are easier to be ignored. This study has great significance for the design of the signage system in the TOD, it could improve people's way-finding effectiveness in complex space.