## 4 Results and Analysis  
### Analysis of Spatial Patterns of Perceived Spatial Quality in Urban Streets  
The results of the global [PERSON]'s \(I\) calculations are shown in Table 3, where the [PERSON]'s \(I\) indices for all six perceptions are positive, indicating that the data exhibit a spatially positive correlation. The results of the spatial autocorrelation analysis for all six perceptions have high \(z\) scores and low \(p\) values, with small \(p\) values indicating that the observed spatial patterns are unlikely to arise from stochastic processes (small probability events). Therefore, hotspot analysis is also needed to detect agglomeration areas' locations. The hotspot analysis yielded six urban street perception clustering results (Figure 3). Figure 3a demonstrates the spatial clustering relationship between the high and low values of the boring score. According to the map, there is an apparent clustering of high values in the northeast region. This is the East Lake Tunnel section, which is perceptually exceptionally closed with only a monotonous view. Similar to this situation is the beautiful low-score aggregation of the East Lake Tunnel in Figure 3b. The five cross-river bridges over the east region also have low scores. Although the cross-river bridges have an open view range, the lack of landscape diversity may contribute to the high boring score. There is a wide range of low scores in the southeast area of Wuchang District, a university area with a long history of construction, rich cultural heritage, a beautiful green landscape, unique architectural and cultural attributes, and a beautiful campus environment. The low score aggregation of boredom here may be related to the diverse environment of the university campus. A similar aggregation of low scores is the depressing score in Figure 3c, both of which are negative evaluations; it can be assumed that the lower their perceived scores, the better the spatial quality. Figure 3b demonstrates the aggregation of high and low values of beautification. Wuchang District along the Yangtze River, which contains more Wuhan historical neighborhoods, cultural parks, and newly built residential areas, presents a more extensive range of score aggregation. It is one of the most critical sections of Wuhan's urban area style control. Figure 3c shows the depressing score aggregation. There is no wide range of high aggregations of depressing scores, but there are two low aggregations of scores near East Lake. Figure 3d shows the lively score; the overall dynamic low aggregation of scores in the area is more significant, and the high aggregation of scores in the area is not apparent and needs further study to transform it into a low aggregation of scores. In Figure 3e, in addition to the low-scoring aggregation near East Lake, there is also a low-scoring area in the eastern region, which has more old neighborhoods and older buildings. Hence, the site has a high population density but narrower roads, more on-street parking, and older facilities. The more aged settlement environment may create a sense of insecurity for pedestrians, resulting in lower scores. Another significantly low-scoring roadway includes the tunnel and viaduct, and the urban expressway harms pedestrians' perceptions of safety. The overall perception of affluence in Figure 3f is better, with high scores clustered mainly in dense urban residential and commercial areas and low scores primarily clustered around the East Lake neighborhood. The overall economic development of the Wuchang District is more advanced in the central metropolitan area of Wuhan. Generally speaking, the city's more prosperous commercial and residential areas have higher commercial value, and the affluence perception is consistent with the general perception. Results and Analysis of Regression Analysis of the Spatial Quality of Urban Streets and Urban Amentity Points  
Table 4 gives the local R2 of the six perception dimensions.