## 3 Data and Methodology
### Acquisition of Research Data
It is one of the more important visual elements in human vision. Space enclosure degree is an important kind of public spatial measure. The degree of spatial closure has a significant influence on the perception of spatial preference attributes and the sensory feedback for mental health [57]. Therefore, it is indispensable to the measurementindex of this study. The degree of motorization and non-motorization measures represent the urban population mobility and the urban traffic situation to some extent. In Chinese cities, the occurrence rate of non-motor vehicles is becoming higher and higher. They are not constrained by the motor vehicle lane, indicating that the impact this will have on pedestrian feelings is direct. We calculated the spatial metrics from each visual element, and five metrics were selected for spatial metrics: the green vision index, sky visibility, degree of interface enclosure, degree of motorization, and degree of non-motorization. (1) Green vision index  
Green visibility can improve the attractiveness and visual experience of urban streets; the public's mental health is significantly affected by the perception of the amount of green in urban streets [58]. The green vision index refers to the proportion of green plants in the visual field, and the formula for its study is:  
\[GVI_{i}=\frac{n_{v}}{n_{i}}\times 100\%\]  
where \(GVI_{i}\) is the green vision index at the \(i\)-th position; \(n_{v}\) is the number of vegetation pixels of the street attraction; and \(n_{i}\) is the total number of pixels of the street-view image at the \(i\)-th location. (2) Sky visibility index  
The sky visibility index has a significant impact on metropolitan areas. It is an important factor in the urban heat island effect [59] that the area experiences, as well as a crucial factor in research into urban morphology. This indicator refers to the visual proportion of sky features in an image in this study, and its calculation formula is as follows:  
\[SVI_{i}=\frac{n_{s}}{n_{i}}\times 100\%\]  
where \(SVI_{i}\) is the sky visibility index at the \(i\)-th position; \(n_{s}\) is the number of sky pixels of the street's attractions; and \(n_{i}\) is the total number of pixels in the \(i\)-th location street-view image. (3) Degree of enclosure  
The degree of the interface enclosure of urban street space measures the enclosure of living street space by facilities such as buildings, walls, fences, etc., which in this study is the pixel occupancy of elements such as buildings, fences, walls, etc. in the image. The specific calculation formula is:  
\[DOE_{i}=\frac{n_{a}+n_{w}+n_{f}}{n_{i}}\times 100\%\] \begin{table}
\begin{tabular}{c c c c c} \hline  & **Maximum** & **Minimum** & **Average** & **Standard Deviation** \\ \hline road & 0.723 & 0.016 & 0.188 & 0.068 \\ sidewalk & 0.140 & 0.000 & 0.017 & 0.017 \\ building & 0.681 & 0.000 & 0.151 & 0.101 \\ wall & 0.172 & 0.000 & 0.005 & 0.009 \\ fence & 0.133 & 0.000 & 0.007 & 0.011 \\ vegetation & 0.713 & 0.000 & 0.205 & 0.154 \\ sky & 0.480 & 0.000 & 0.200 & 0.123 \\ person & 0.189 & 0.000 & 0.010 & 0.008 \\ rider & 0.025 & 0.000 & 0.001 & 0.001 \\ car & 0.983 & 0.000 & 0.191 & 0.064 \\ truck & 0.186 & 0.000 & 0.007 & 0.013 \\ bus & 0.115 & 0.000 & 0.001 & 0.005 \\ motorcycle & 0.048 & 0.000 & 0.002 & 0.004 \\ bicycle & 0.059 & 0.000 & 0.002 & 0.003 \\ \hline \end{tabular}
\end{table} 
Table 1: Segmentation results of the 14 visual elements. where \(DOE_{i}\) is the degree of enclosure at the \(i\)-th position; \(n_{a}\) is the number of architectural pixels of the street's attractions; \(n_{w}\) is the pixels of the number of walls of the street's attractions; \(n_{f}\) is the number of pixels of the fence of the street's attractions; and \(n_{i}\) is the total number of pixels in the \(i\)-th location street-view image. (4) Degree of motorization  
The degree of motorization impacts urban pedestrian mobility, which influences the environmental, socio-demographic, mobility, and road safety characteristics of pedestrian travel communities [60].