Planning Strategies and Design Concepts
Study on the Factors Affecting the Restorativeness of Pedestrian Streets in Winter Cities
2025 Volume 13 Issue 3 Pages 1-13
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2025 Volume 13 Issue 3 Pages 1-13
Faced with an increasingly tense global public mental health crisis, the restorativeness of built environments has attracted much attention. The outbreak of COVID-19 outbreak impeded the balanced physical, psychological, and social development of individuals, inducing and exacerbating mental health problems. Because of the high incidence of seasonal mental illness in a winter city, the health risk is more intense than in other climate areas. Therefore, special attention needs to be paid to health-supportive environments that are closely related to daily life in the design and planning processes of cold land cities. As a critical part of the city, streets have a significant impact on the public's behavior and psychological perception, especially when there is no traffic interference and users are completely exposed to the environment on pedestrian streets, which will more directly affect people's psychological feelings. Therefore, from the perspective of the user's psychological perception, based on the particularity of cold climates and the users' needs, this study provides a system of influencing factors for the restorativeness of pedestrian streets in winter cities, including visuality, mobility, ecology, and usability factors. Subsequently, three types of pedestrian streets in Harbin, a typical winter city, were selected to collect and analyze multi-source data on various pedestrian street factors. The study considers users as the main body of evaluation to measure the public perception level of the three types of pedestrian streets in cold and non-cold seasons using the Perception Recovery Scale. Finally, the correlation between various factors and public perception is discussed using a geographic detector model to explore the factors influencing the restorativeness of pedestrian streets in winter cities and the correlation degree of various factors. These findings can help develop targeted design strategies to improve pedestrian street design for better restorativeness.
With the acceleration of industrialization, urbanization, and population aging, the production and lifestyle of Chinese residents as well as the spectrum of diseases are constantly changing. Building healthy cities in an all-around manner has become a critical measure for national development and transformation and a national strategy for realizing people's health and sustainable urban development.
In April 2022, The National Health Commission of the People’s Republic of China proposed that a healthy city should be considered an important starting point for Healthy China Construction, based on the outline of the “Healthy China 2030” initiative. In addition, under the significant impact of the novel coronavirus, people's daily life patterns and work status have changed, and their psychological state is in a cycle of "stress-adjustment-restoration of normalcy.” Public health status is often in a passive and fluctuating state (Bustamante, Guzman et al., 2022) which leads to mental health crises. Therefore, obtaining positive intervention elements for physical and mental health from daily life environments has become a topic of concern for many scholars (Bustamante, Guzman et al., 2022). As a vital part of the city, streets are healthy and supportive environments closely related to daily life and have a remarkable impact on public behavior and psychological perception. In particular, pedestrian streets with no traffic interference, which entirely expose users to the environment, have a more direct psychological perception. Meanwhile, in the post-coronavirus society, there is more demand for environmental healing.
In 1989, Kaplan and his wife first proposed the theory of attention recovery, which links human cognition with the natural environment, prompting many domestic and foreign scholars to study the relationship between the built environment and public health. Most studies have reached a consensus on the effects of the accessibility of public transport and service facilities (WANG, J.-j., ZHU et al., 2022), land use mixing (Alcock, White et al., 2015), green space proportion (Saraswat, Pipralia et al., 2024), and accessibility (Yang, Wen et al., 2023) and have determined that the built environment has direct and indirect effects on mental health (Zijlema, Cerin et al., 2024).
Kaplan and Talbot proposed the concept of healing in the restorative environment theory (Kaplan and Kaplan, 1989; Ulrich, 1984), and in recent years, the concept of "healing streets” was proposed, which confirmed the healing nature of streets as an urban space (Xu, Meng et al., 2019) and as a single space that can enhance environmental health.
In addition, Gascon et al. (2015) found differences in the effects of the same environmental factors on mental health across countries with different climates, living conditions, and cultural characteristics as well as between urban and rural areas (Gascon, Triguero-Mas et al., 2015). Among them, climate change adversely affects physical health by acting on the fundamental determinants of health, such as air, water, soil, and infectious disease transmission patterns (Chen and Yang, 2023). Moreover, extreme natural disasters due to climate change can pose a threat to the lives of populations (Liu, Z. and Qin, 2013), which shows that climate has a non-negligible impact on public health.
Medical studies have shown that the incidence of cardiovascular diseases and immune system diseases increases in winter (The-Eurowinter-Group, 1997); consequently, the long winter in cold cities, characterized by low temperatures, snowfall, cold wind, short daylight hours, and other climatic characteristics, can bring more health effects to urban residents. Leng et al. (2017) explored how to reduce the impact of urban space on public health under cold climatic conditions from the perspective of public health in winter (Leng and Li, 2017).
International research on the relationship between the built environment and public health started earlier, and the number is much higher than that in China. Research methods, depth, and tools are more mature, whereas research in China is still in its infancy. Spatially, international studies have gradually shifted to a more microscopic neighborhood scale and the spatial design of green parks, and some studies have subdivided the population by age and gender. In China, macro- and meso-scale studies have mainly been conducted in cities and regions, and meso-scale studies on communities and parks have started appearing in recent years.
Moreover, most previous studies on the healing function of urban built environments have focused on the impact of urban blue and green spaces, such as urban parks and waterfront spaces (Asl, 2022), and the city space has a more natural environment. However, in urban systems, streets are public spaces with high accessibility and spatial continuity, and it is more practical to use the street environment to provide residents with healing experiences; therefore, studying the healing influence of streets on urban residents is of great value.
Currently, research has made preliminary attempts to understand the mechanisms of the built environment's influence on public health and the application of modern information science and technology in data collection. The validity of mental health questionnaires has been confirmed, scientific and objective data measurement and analysis methods are gradually being applied, data analysis methods used to reveal the correlation between the two are becoming mature, and there is a tendency to construct multilevel and multiscale optimization design strategies. However, in general, existing studies have paid less attention to the special effects of cold climates and have not yet conducted relevant studies with the cold urban street environment as the research object. There is also a lack of seasonal exploration of spatial environments and residential activities.
Based on the above research background, this study aimed to construct a factor system affecting the restorativeness of urban walking streets in cold areas and explore the factors influencing the restorativeness of urban walking streets in cold regions. Further, the degree of correlation of various factors from the perspective of users' psychological perception, based on the climatic particularity of cold areas and users' needs, was explored. From the perspective of planning, this study proposed methods to increase the comfort level of pedestrians, reduce their negative emotions, and promote their physical and mental health through the design of urban pedestrian streets in cold areas, providing a basis and reference for dealing with increasing health needs in the future.
The study area was concentrated in downtown Harbin, Heilongjiang Province (125°42'-130°10' E, 44°04'-46°40' N). Harbin is the provincial capital of Heilongjiang Province, located on the northeast plain of China and southwest of Heilongjiang Province, a vice-provincial city. Its permanent population is 10.098 million. Harbin belongs to the middle temperate continental monsoon climate, with an annual average temperature of 5.6 ℃, highs of 39 ℃, and lows of -37.7 ℃. The difference between the highest and lowest temperatures is ~80 ℃. Cold, long winters are important climatic features of Harbin.
According to the regional distribution and functional positioning of pedestrian streets in Harbin, three pedestrian streets were selected for the investigation, as shown in Figure 1. The selection of the sample streets was typical, and these three urban pedestrian streets are located in the three core administrative districts of the city. The three streets cover traditional pedestrian streets and modern pedestrian streets, and in terms of street functions, they cover the priorities of pedestrian sightseeing functions and commercial residency functions.
① Zhongyang Street. Zhongyang Street is located in the Daoli district of Harbin City. It is the longest pedestrian street in Asia. It is a rich historical pedestrian street with characteristics of both tourism and commerce. A section approximately 500 m long and 20 m wide from the intersection of Central Street and West Seventh Street to the flood control memorial tower, was selected for the study.
② Jianshe Street. Jianshe Street is located in Nangang District, Harbin City, adjacent to Dongzhi Street and Gogol Street, and has a total length of more than 200 m. There are many large shopping malls nearby and transportation is convenient. This is a typical commercial pedestrian street. Owing to its location close to the city center and the distribution of several old brands and large businesses, it is more attractive to the public.
③ Zhonghua Baroque Pedestrian Street. Zhonghua Baroque Pedestrian Street is located in the Daowai District of Harbin City. The street is part of the "Zhonghua Barock" architectural complex, which is famous in the international architectural field. Because it embodies a combination of Chinese and Western characteristics, it is a critical block for world history and cultural protection and a beautiful scenery line among Chinese architectural groups.
The methodology used in this study is illustrated in Figure 2. This study analyzed public perception data on three selected typical pedestrian streets using a Perception Recovery Scale. Figure 2 shows a visual representation of the current restorativeness of pedestrian streets. This study used the GeoDetector model to analyze the correlation between the influencing factors of the healing performance of pedestrian streets in cold cities to determine how to adjust the influencing factors that can effectively improve the physical and mental health of pedestrians.
In this study, the public perception level (dependent variable) of the sample pedestrian streets was measured using the Perceived Restorativeness Scale by controlling for mediating variables such as age, gender, and behavioral activities. A system of influencing factors on the restorativeness of urban pedestrian streets in winter cities was developed based on a literature review, and the influencing factors (independent variables) of the sample streets were acquired through field measurements and street scene image analysis. level was statistically analyzed using a detector model based on factor and interaction detection.
Likert scaleTo test the influence of urban pedestrian streets in winter cities on public mental health perception and explore how these factors affect pedestrians' intention to stay and the degree of influence of different factors on activity intention, this study combined electronic and paper questionnaires to obtain data. A 5-point Likert scale (ranging from 1 = very unacceptable to 5 = highly acceptable) was used to set the perceptual recovery indicators. Because the independent variables of the geodetector model are type quantities, they are similar and contribute to increased representativeness of the sample units. The geodetector model can achieve an accuracy that other models can achieve using larger sample sizes with sample sizes of less than 30 (Wang, J. and Xu, 2017). Questionnaires were distributed from winter (December to February) to summer (May to July); the total number of questionnaires was 135. The recovered perception scale questionnaires were filtered based on the completeness of the answers and the apparent regularity of the results, and 120 effective questionnaires were eligible after filtering. The overall effectiveness rate of the questionnaires was 89%, and the number of male and female participants was the same to ensure the rationality of the survey data. The perceived restorativeness scale is shown in Table 1.
| Dimensions | Specific issues |
| Distance | The atmosphere here is different from other places |
| I feel like I can do something here that I can't normally do | |
| I came here to feel free from work, study and chores | |
| I came here to feel less constrained | |
| Coherence | The scenery here is in harmony with each other |
| Everything here forms a single entity | |
| Everything looks like it belongs here | |
| The place is in harmony with the surrounding environment | |
| Attractiveness | There are a lot of new discoveries here |
| I feel immersed in this environment | |
| There are many things that attract me to stay here | |
| There are a lot of things that catch my attention here | |
| Consistency | I can do my favorite activities here |
| I can manage the issues that arise here | |
| I am adapting quickly to the environment here | |
| The environment here is perfect for doing what I like to do |
Studies on the restorativeness of urban pedestrian streets have confirmed that visual, activity, ecological, amenity, etc. factors influence the restorativeness of the pedestrian streets from the perspectives of urban road environments, resident health, and psychology. Notably, scholars such as Liu, Y., Wang et al. (2020) have explored, through the use of Structural Equation Modeling and Remote Sensing Technology, how enhancing streets with green spaces can foster neighborhood cohesion, thereby improving community relations and participation. Fisher et al. studied street scenes with biodiversity and concluded that such scenes positively impact air pollution reduction, quality of life enhancement, and emotional well-being by promoting improvements in the visual, olfactory, and auditory aspects of streets (Fisher, Rankin et al., 2022). Buttazzoni and Minaker studied the mental health of adolescents, a group socially sensitive to external environments, and found that well-configured street facilities could provide more opportunities for social interaction. They also note that narrower streets contribute to a more stable street atmosphere (Buttazzoni and Minaker, 2023). The factors influencing restorativeness were selected through literature review and field studies, and the factors influencing the restorativeness of cold urban pedestrian streets were classified into four categories: visual, activity, ecological, and pleasant.
Visual factors are the sources of users' intuitive perceptions of urban pedestrian street spaces. The visual factors of space directly affect users' physical and psychological comfort, bringing them psychological feelings such as freedom, belonging, and immersion. The quantitative study of the visual factors affecting street restorativeness focuses on four aspects: street space color, side interface transparency, environmental neatness, and interface extension.
The activity factor is the source of users' feelings after using an urban pedestrian street space. The scale of street space and arrangement of street facilities affect users' activities in space. Good infrastructure stimulates users to engage in richer types of activities in street spaces, thus achieving the healing purpose of physical and mental pleasure. Three street characteristics, namely sports facilities, recreational facilities, and sidewalk width, were filtered to influence restorativeness.
Ecological factors are natural elements in urban pedestrian street spaces, and it has been confirmed that blue-green spaces and natural environmental elements in the city can enhance the restorativeness of the built environment. Therefore, this study selected the street green vision rate as an indicator to calculate the effect of ecological factors on restorativeness.
Amenities are a vital indicator of the spatial quality of urban pedestrian streets. The suitability of the street spatial scale (width-height ratio) and degree of pedestrian congestion can improve the restorativeness of streets.
| Categories | Factors | Data source |
|---|---|---|
| Visual factors | Street space color | Evaluating the mood-enhancing qualities of environmental colors within the sample space range |
| Side interface transparency (X1) |
X1 = (L1 × 1 + L2 × 0.75 + L3 × 0.5 + L4 × 0)/L where L1 is the length of a completely open commercial facade or a relatively sparse fence; L2 is the length of a transparent and illuminated commercial window or a relatively dense fence; L3 is the length of a building façade or a low wall that generally contains doors and windows; L4 is the length of a building façade that does not have doors and windows or is not illuminated in the above conditions or the length of a solid wall that is higher than the average person's line of sight; and L is the range of spatial samples. |
|
| Interface extensibility (X2) |
X2 = (Ld1 + Ld2 + Ld3 +…·+ Ldn) / L Where Ld is the width of the accessible entrance/exit of a section of a street for an area such as a city road, a residential area, or a park (entrances/exits that are closed or locked are excluded); and L is the range of spatial samples. |
|
| Environmental tidiness | Evaluation of environmental cleanliness within a sample of spaces | |
| Activity factors | Sports facilities | Number of perceived sports facilities within the spatial extent of the sample |
| Recreational facilities | Number of perceived recreational facilities within the spatial extent of the sample | |
| Sidewalk width | Field measurement | |
| Ecological factors | Street Green Vision Rate | Thee average value of the green visibility of the street photos in the front, back, left, and right of each street point |
| Plant Diversity | Field Research | |
| Amenity factor | Spatial scale of streets | Height-width Ratio of Building and Street Surface (HWR) |
| Pedestrian Crowdedness | Reflecting pedestrian congestion with thermal distribution of pedestrian walkways on open source mapping software between 7:00 a.m. and 11:00 p.m. |
The Geographical Detector Model is a statistical tool for measuring and exploring spatial hierarchical heterogeneity and the driving forces behind it. It has obvious advantages over other statistical models. By calculating and comparing the q-value of each factor and that of the two superimposed factors, the Geographical Detector Model can determine the strength and direction of the interaction between the detectors. If there is a correlation between the detectors interacting with the dependent variable, the GeoDetector model can test the relationship.
The relationship between the factors influencing the restorativeness of cold urban walkways and public perception was statistically analyzed using factor detection in the GeoDetector model to obtain the magnitude of the influence of each factor.
This study used factor detection in the GeoDetector model to probe the correlation between each influencing factor and pedestrian perception using equation (1) and investigates the correlation between the two based on the q-value of the explanatory power of the dependent variable and its significance test.
(1)
where q represents the explanatory power of each factor on the restorativeness of pedestrian streets, and the range of the q value is between 0 and 1. The larger the q value, the better the interpretive ability, which means a greater influence, and vice versa. N is all the pedestrian streets in the study, σ2 represents the discrete variance of the restorativeness of all the pedestrian streets in the study, h represents the partitions of each factor, L represents the number of factor partitions, and h is an integer of 1-L. In this study, the q value typically represents the intensity of the influence of factors on the restorativeness of pedestrian streets in cities with cold climates. A higher q value indicates a greater impact of this factor on the healing performance of pedestrian streets.
The public perception level of each street was determined according to the electronic and paper versions of the distributed questionnaire, and a representative word was selected for each problem. The four characteristics–distance, coherence, attractiveness, and consistency–were summarized to analyze the scores of the three samples. To compare the influence of each factor influencing restorativeness on the restorativeness of pedestrian streets, this study visualized and compared 16 items of restorativeness data for the three streets based on the statistical results. Figure 3 shows the visualization results of the restorativeness of the pedestrian streets in the cold and non-cold seasons.
Overall, the restorativeness of pedestrian streets was generally lower in the cold season than in the non-cold season and averaged out among the three samples. In the non-cold season, Zhongyang Street, a comprehensive tourist pedestrian street sample, showed a higher restorative performance. In terms of the four characteristics of the restorativeness of pedestrian streets, the scores were in the following order: coherence > attractiveness > distance > consistency.
Factors affecting restorativenessThe factors influencing the restorativeness of the three urban pedestrian streets were measured based on field research and the measurements shown in Table 2, and the measurement results are shown in Figure 4. Factors influencing restorativeness of urban pedestrian streets The overall results show that the restorativeness of a pedestrian street is generated by the interaction between multiple influences, rather than by a single influence.
To investigate the overall influence mechanism of the restorativeness of pedestrian streets in winter cities, the data were first discretized and calculated using the detector model. The results showed that street space color (q = 0.029), interface transparency (q = 0.004), environmental cleanliness (q = 0.013), resting facilities (q = 0.029), and plant diversity (q = 0.029) did not have significant effects on the restorativeness of pedestrian streets in the cold season. Although the interface extension (q = 0.030), sidewalk width (q = 0.030), street space scale (q = 0.030), and degree of pedestrian congestion (q = 0.030) passed the significance test, the strength of each factor in explaining the variation in the restorativeness of pedestrian streets was the same, with little difference. However, in the non-cold season, all other factors passed the significance test except for the difference between the interface transparency (q = 0.000) and the healing strength of the pedestrian street. There was little difference in the explanatory strength of the different factors (q = 0.573) for the differentiation of the restorative strength of pedestrian streets. The main difference was that the influence of recreational facilities (q = 0.438) was weak.
On this basis, the GeoDetector Model was used to calculate and analyze the factors influencing the distance, coherence, attractiveness, and consistency of the restoration of walking streets in cold and non-cold seasons. By comparing the magnitude of the q-values of each factor with the variance of the restorativeness intensity of pedestrian streets, it was found that the explanatory power of each factor differed more between cold and non-cold seasons; however, the difference in the strength of explanatory power between factors under the same conditions was not significant.
The calculation results are as follows:
(1) In the cold season, distance was significantly correlated with all factors except environmental tidiness (q = 0.012). By comparing the q-values of each factor with the variance in distance, the influences of the interface extension (q = 0.076), sidewalk width (q = 0.076), street space scale (q = 0.076), and pedestrian congestion (q = 0.076) were slightly larger than those of the interface transparency (q = 0.075). The effect of interface transparency was greater than that of spatial color (q = 0.028), leisure facilities (q = 0.028), and plant diversity (q = 0.028). In the non-cold season, the distance attribute was significantly correlated with all factors except interface transparency (q = 0.015), among which the influence of open-space facilities (q = 0.176) was the lowest, and the explanatory power of the other factors was not significantly different.
From the results of the calculation of the influencing factors of distance, some influencing factors must be screened to optimize the design and obtain better results in the cold season.
(2) In the cold season, coherence was not significantly correlated with any factor (all q values were ≤0.003). In contrast, under non-cold season conditions, the coherence attribute was significantly correlated with all factors. The explanatory power of interface transparency (q = 0.033) was the lowest, followed by the other facilities (q = 0.194), and the other factors (q values were all approximately 0.409) had strong and close explanatory power.
From the results of the calculation of the coherent influencing factors, it can be observed that the optimized design of such influencing factors can only obtain better results in the non-cold season.
(3) During the cold season, the variance in charismatic intensity was not significantly related to spatial color (q = 0.001), resting facilities (q = 0.001), environmental tidiness (q = 0.027), or plant diversity (q = 0.001). The explanatory power of the interface transparency (q = 0.0399) was the weakest, whereas that of the remaining factors was comparable (q = 0.0459). In the non-cold season, only interface transparency (q = 0.000) was not significantly correlated. Among the other factors, the explanatory power of the remaining facilities (q = 0.249) was the weakest, and the explanatory power of the remaining factors (q = 0.340) did not differ.
The attractiveness influence factor was calculated similarly to the distance influence factor, with healing performance enhancement being more limited in the cold season than in the non-cold season.
(4) In the cold season, consistency was not significantly related to interface transparency (q = 0.004) and environmental cleanliness (q = 0.024), and the explanatory powers of interface extension (q = 0.051), sidewalk width (q = 0.051), street space scale (q = 0.051), and pedestrian crowding (q = 0.051) were greater than that of spatial color (q = 0.048), resting facilities (q = 0.048), and plant diversity (q = 0.048) among the other factors. In the non-cold season, consistency was only insignificantly correlated with interface transparency (q = 0.009) and weakly correlated with open-space facilities (q = 0.179), whereas the correlations of the remaining factors (q = 0.196) were consistent.
The results of the consistency impact factor calculations clearly show that optimizing the design of such impact factors under any seasonal condition yields better results.
Interaction DetectorThe calculated results under the interaction of the factors showed the explanatory power of the joint action between any two of the 10 factors on the restorativeness of pedestrian streets in winter cities. The type of interaction was further analyzed by comparing the interaction probe results with the single-factor probe results. The results showed that the effects of the influencing factors on the restorativeness of the pedestrian street were nonlinearly or two-factor enhanced, indicating that the influencing factors had stronger effects on the restorativeness of the pedestrian street when acting together. The restorativeness of pedestrian streets was directly affected by many factors. The explanatory power of the interacting factors was greater than that of a single factor. Even for minor factors and factors that have no obvious mechanism of action on the restorativeness of pedestrian streets, the influence of their combination with other factors substantially increased
In this study, three types of pedestrian streets in Harbin, a typical cold city, were selected to measure the public perception level of the three types of pedestrian streets in the cold and non-cold seasons using the perception recovery scale. Multi-source data collection and analysis were conducted on various pedestrian street factors. To a certain extent, the influence of partial sample data was reduced. The final results were as follows:
(1) The restorativeness characteristics of pedestrian streets differed significantly in different seasons.
(2) There were significant correlations between pedestrian street restorativeness and various other factors.
(3) Different attributes were significantly correlated with different factors by calculating the factors influencing the distance, coherence, attractiveness, and consistency of the restorativeness of pedestrian paths in cold and non-cold seasons.
(4) The effect on the restorativeness of pedestrian streets was more significant when the influencing factors work together.
(5) The restorativeness of a pedestrian street can be improved only when all the influencing factors are balanced.
The quantitative results obtained in this study can provide a reference for the design of pedestrian streets geared toward restorativeness enhancement, which can help the future layout construction and investment development of other winter cities and play a critical role in promoting environmental benefit enhancement while also balancing economic and social benefits. In addition, the research method of this study can also be appropriate for other types of related studies, and its technical route can provide insights into the future sustainable development of cold land cities.
Conceptualization, L.Y; methodology, L.Y and M.Z; software, L.Y; investigation, Z.Y and Y.W; resources, L.Y, Z.Y and Y.W.; data curation, L.Y and M.Z; writing—original draft preparation, L.Y, M.Z, Z.Y and Y.W; writing—review and editing, L.Y and M.Z; supervision, L.Y and M.Z. All authors have read and agreed to the published version of the manuscript.
The authors declare that they have no conflicts of interest regarding the publication of this paper.
