| China is a mountainous country with a large number of mountainous cities and a wide range,which holds a special and important strategic position.Due to the unique terrain and natural landscape pattern,mountainous urban expressways are endowed with a rich landscape and charm.However,due to the uneven development of urban expressway road landscape spatial pattern and the lack of distinctive features,it is necessary to analyze the types of visual attraction elements and their optimal ratios of urban expressway road landscape,in order to provide theoretical reference for the high-quality development of mountain urban expressway road landscape space.Guiyang is the capital of Guizhou Province,with a total mileage of 148 kilometers.This paper takes Guiyang’s expressways(Huaguan Road,Jiaxiu South Road,Gui’an Avenue,Qianzhong Avenue)as the research object,and starts from the perspective and physical and mental feelings of motor vehicle users,to explore the types of visual attraction elements that are highly attractive in the landscape space of expressways in mountainous cities The optimal ratio of various elements and the optimal combination of landscape elements are proposed,and the optimization strategy for road landscape space is proposed.This article conducts the following research through research methods such as SD semantic analysis,SBE beauty analysis,and image analysis:Firstly,theoretical knowledge learning was conducted on relevant literature and books.Through on-site research on four expressways in four seasons,basic images and video materials were obtained.Starting from the aspect of road landscape elements,all road landscape elements in the research object were extracted.The degree of human factor participation was divided into two categories: artificial elements and natural elements,which included a total of 19 elements,Determine 10 sets of guiding words for landscape visual semantic environment through literature research and interview methods.Using 3200 valid questionnaires as the data source for subsequent analysis,the questionnaire data is mainly divided into two modules: landscape visual attraction element types based on SBE method and landscape environmental perception based on SD method.Secondly,the obtained image materials are extracted from the basic data of visual attraction factor matching through image analysis method.Cut the video materials from the perspective of four seasons and four expressways from the perspective of motor vehicle traffic into 3-minute videos,totaling 48 minutes,and process them into images.Use Labelme software to manually label 960 images to assist computer recognition of the elements within the images.Then,use Python programming software to establish a dataset,and finally perform image semantic segmentation to segment the visual attraction elements of the landscape and calculate the ratio of the elements,Then,integrate and summarize some of the same type of elements to obtain a data table for the matching of landscape visual attraction elements under different seasons and roads.Once again,explore the types and combinations of landscape visual attraction elements based on the semantic environmental characteristics of the four expressways under different seasons.Using SPSS software to conduct descriptive statistics on the survey questionnaire data table,obtain the landscape visual semantic environment characteristics of the four expressways in different seasons;By using SPSS exploratory factor analysis,the combination of attractive elements with better landscape visual appeal for the four expressways in different seasons was summarized;Using SPSS correlation analysis,explore the correlation between the types of visual attraction elements and the semantics of the visual environment,the ratio of visual attraction elements,and the attractiveness of visual attraction elements.Finally,based on the above correlation analysis,further regression analysis was conducted on the ratio of visual attraction factors and the attractiveness of visual attraction factors.Through linear regression analysis,a regression model was determined that the variables fully matched and had no significant relationship.Combining the visual semantic environment requirements of the four expressways in different seasons and the combination of excellent landscape visual attraction elements,it is concluded that in spring,in order to make the mountains and grasslands have good attraction at the same time,the proportion of mountain elements needs to be controlled within the range of 3.2%-43%.When the proportion is around 3.2%,the spatial sense in the visual environment of the road landscape is enhanced.When it reaches about 40%,The sense of tranquility in the landscape visual environment is significantly enhanced.In the summer expressway road landscape,when the ratio of terrain elements is controlled within the range of 3.7%-47%,both terrain and tree elements can present good attractiveness.The average total ratio of trees and shrubs in this study is about 33%.Reducing their ratio appropriately can enhance the spatial and hierarchical sense of the road landscape visual environment.To make transportation vehicles and billboards/signage both attractive,it is necessary to control the proportion of transportation elements within the range of 2.3%-19.4%.In the autumn expressway landscape,when the visual ratio of transportation elements is controlled at around 6%,both transportation and overpass elements can exhibit good attractiveness.In winter,in the landscape of expressways,in order to make vehicles and tunnels both a ttractive,the visual ratio of vehicle elements should be controlled at around 1.5%.When the ratio of vehicle elements is less than 1%,the sense of tranquility in the visual environment of the road landscape is improved.This study is based on the research idea of "context+focus one-landscape visual semantic environment+landscape visual attraction elements",providing new ideas for future landscape visual planning and design of road landscape aesthetics,transportation,and health. |
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