Vitality Analysis and Improvement of Micro Urban Spaces in Cold Regions Evidence from Harbin, China

Shuqi Li; Yang Ye; Haoyu Chen; Yuhan Yang; Yi Huang; Zihao Wu

doi:10.14246/irspsd.12.3_95

Abstract

In the context of urban public spaces, which tend to be shrunk and humanistic, micro urban spaces (MUSs) might offer residents additional opportunities for public activities to occur because of their small scale, discrete distribution, and frequent interaction. Cold cities have severe climatic restrictions; thus, as the seasons change, MUSs in cold regions are more significant than medium- and large-scale public spaces. To investigate how MUSs in cold regions contribute to enhancing urban vitality during transition seasons, a system of indicators was developed for the measurement of the intensity of public activities and the environmental elements of MUSs in cold regions. Then, a typical cold city, namely Harbin, China, was selected for research, and 93 samples of independent and dependent MUSs were chosen for investigation. Based on the results of behavior mapping, multiple regression analysis was used to investigate the relationships between the vitality of various types of urban MUSs in cold cities and their environmental elements. The results show that function, greenery, and public facilities are three categories of environmental factors that significantly affect the vitality of urban MUSs, with greenery and function having stronger relationships with independent and dependent MUSs, respectively. Finally, according to the results, design and optimization suggestions for different types of MUSs in cold regions are put forward.

Introduction

In the context of inventory planning, people's utilization of urban public space has shifted from crude quantitative expansion to fine quality enhancement. Under the contradiction of limited space and growing demand, smaller-scale and underutilized micro urban spaces (MUSs) have gradually attracted the attention of many researchers (Hamdy and Plaku, 2021). Public open spaces consist of a series of small public spaces that connect various parts of the city like nodes and facilitate public life; these are called MUSs (Hou, Chen et al., 2020). As defined by McPherason and Marshall (McPhearson and Marshall, 2015), MUSs are characterized by a weak hierarchy, a discrete distribution, a large number, and a small scale as compared with medium and large public spaces, as a type of urban public space attached to the main urban space (roads, squares, waterfront spaces, green spaces, and buildings). They are open to the city and can be defined and classified according to the scale of the human perception of the space of the street and building coupling, as well as the space range of the street and street coupling. Broadly speaking, MUSs are extracted from the urban public space system based on the human-centered spatial scale from the most microscopic morphological perspective, and their starting point is to meet human-centered needs, i.e., to create places for crowd interaction or to provide rest for residents (Gibson and Canfield, 2016).

Public activities give cities their vitality and charm. It is commonly believed that urban vitality plays an important role in evaluating the well-being of residents and is the basis for securing their basic quality of life. Since the 1990s, there has been a growing call for the construction of vibrant cities. Through social interaction, the occurrence of public activities, and the demonstration of a sense of place, spaces with high levels of vitality tend to reflect a better quality of life, which in turn enhances the distinctive character of the area. Public activities can be understood as consisting of necessary, spontaneous, and social activities. Necessary and spontaneous activities respectively refer to those that occur under various conditions and those that occur only under suitable outdoor conditions, while social activities refer to various activities in public spaces that depend on the participation of others. Social activities are indirectly promoted by improving the conditions for the occurrence of necessary and spontaneous activities (Gehl, 1987). If the quality of MUSs is improved, the attractiveness of the public space will be increased, which will promote the occurrence of public activities and enhance vitality. In particular, in the context of epidemics, medium and large public green spaces are usually restricted from activities (Gubić and Wolff, 2022). Because of their characteristics, MUSs can provide residents with a basic space for outdoor activities and play a crucial role in maintaining urban vitality and improving the well-being of citizens. Therefore, the study of MUSs can complement and improve the existing urban public space hierarchy from the macro and meso levels to the micro level, and can provide theoretical references for fine management and urban design.

MUSs in cold regions are important for enriching the daily lives of residents and providing suitable spaces for interaction. Cold regions are defined differently based on different boundaries of air temperature, ice cover, and permafrost (Bates and Bilello, 1966). A broadly accepted definition is an area where the average (mean) temperature is below 1°C for more than one month of each year (Smith, 1996). There is no strict climatological definition of cold cities in this study. Cities with four distinct seasons affected by snowfall and with temperatures below 1°C for at least one month of a year are considered cold cities. According to the calculations of the International Association of Cold Cities, there are a large number of cold cities occupying a very large area, and at least 600 million people worldwide experience living in a winter climate. However, cold cities are subject to climatic constraints that affect them for up to six months of the year during the long cold season. Cold winds, snow and ice, low temperatures, low sunlight, and a lack of green landscape reduce the safety of travel and walking comfort, thus greatly limiting winter travel activities for residents of cold cities. In this context, MUSs have great value as fragmented public spaces coupled with streets and buildings, and they are the most frequently contacted public space for residents. Because of the material base and climate shelter provided by the building interface and street greenery, the environmental quality directly affects the form, time, and willingness of outdoor activities in cold cities. The winter climate in cold cities is too harsh, and it is difficult for artificial measures to change the physical environment of low outdoor temperatures; thus, residents' willingness to engage in outdoor activities is low (Yuan, Zhang et al., 2022). Compared with other seasons, the elasticity of residents' willingness to engage in spontaneous outdoor activities is higher in transition seasons (Guo, F., Wang et al., 2022). Therefore, determining how to optimize MUSs in cold regions and thus attract residents to participate in public activities and promote their use in the transition season is significant for the enhancement of the vitality of cold cities.

In order to capture the activity as well as the MUSs vitality and to scientifically promote vitality through spatial design in cold cities, the research design attempted to test the hypotheses that the MUSs vitality is correlated with the elements of the built environment and the vitality intensity in different types of MUSs is correlated with different elements. To test this, a methodology was adopted whereby residents' behaviors were directly observed during different seasons as they engaged in local daily outdoor activities. These behaviors were mapped so that the results could be more clearly linked to specific small-scale design features. On this basis, a mathematical model for predicting the MUSs vitality in cold cities was developed to clarify which elements of the built environment determine the vitality intensity.

Literature Review

Research and practice of micro urban spaces

American landscape architect Zion proposed in 1963 that a 50 × 100-square-foot vest-pocket park would allow workers and shoppers to take a break (Tate, 2015), and in 1967 built the classic MUS of Paley Park in New York. The Park Association of New York, led by Whitney North Seymour, encouraged and promoted the creation of numerous small parks and compiled theoretical books (Seymour Jr, 1969). Later, in 1980, Whyte (Whyte, 1980) described the close relationship between small urban public spaces and social activities in New York in "The Social Life of Small Urban Spaces." Ashihara (Ashihara, 1984) proposed that the landscape aesthetics of MUSs, such as architectural boundaries, shaded spaces, and pocket gardens, carry value for public life. In "Collage City," Clinro (Rowe and Koetter, 1984) proposed that corner spaces play an important role in public activities and texture restoration in the city. In the 2007 Lisbon Architecture Biennale "Urban Voids on the City and Urban Voids," architects from different countries and regions provided their ideas and showcased practical cases of urban voids in different cities worldwide. The aim was to discuss how to use small, neglected public spaces in a city, and the participating designers jointly proposed that when these neglected spaces are linked and re-evaluated, they can activate the city. Austrian urban planner (Paul, Camillo et al., 1946) analyzed MUSs in European historic districts, and argued that these irregular, small-scale spaces should be attended to and utilized in the urban renewal process. Through years of observation and practice, Gehl (Gehl, 2011) proposed that cities need MUSs and summarized the strategies of MUS design. Francis and Marcus (Marcus and Francis, 1997) analyzed the factors related to the design of small and pocket parks, and suggested that people in the neighborhood could be involved in the design and construction of small public spaces.

In terms of the evaluation of the public space environment, Gehl took Copenhagen as the object of research and practice in the early stage, and proposed the analysis and evaluation of protection, comfort, and pleasure, which laid the foundation for the evaluation of each type of public space environment. From a health promotion perspective, Nordh (Nordh and Østby, 2013) focused on the functions of "rest and healing" and "social interaction" in pocket parks, and compared the spatial environment elements in several urban pocket parks in Copenhagen. Mehta Mehta (2014) created a public space index to assess the quality of public spaces by empirically assessing their inclusiveness, meaningfulness, safety, comfort, and pleasantness, and the publication provided examples of fragmented public spaces to shed more light on this field of study.

Regarding the practice of urban renewal, Japan began to renovate and design small squares in historic districts in the 1970s. In the utilization of fragmented street spaces, not only were the needs of residents taken into account, but the joint design with public art also endowed the MUSs with both aesthetic and applicable value. The book "Introduction to Road Observation" documents the current situation and changes in various small, unofficially operated, and maintained fragmented small public spaces in a city (藤森照信, 1993). From 1981 to 1991, the government of Barcelona, Spain, issued a policy on small public spaces, which focused on small public spaces in decaying areas and optimized hundreds of small parks and green spaces, thus improving the overall appearance of the city and enhancing public vitality. In the United States, the concept of a "parklet" was introduced in 2005, mainly to transform one or more parking lots along a carriageway into temporary or permanent miniature public spaces. The Tactical Public Realm Guidelines published in 2018 proposed the renewal strategy of MUSs, such as street parking spaces and street corner spaces, as urban living rooms, urban canvases, and experimental sites (Walsh, 2018). China has also been exploring the renewal of MUSs in recent years. The "Shanghai Planning Guidance of 15-minute Community-Life Circle" proposes to explore and utilize the "corner waste" in the city and initiate a revival of MUSs to transform some neglected MUSs into "urban living rooms" for urban residents to socialize (Shanghai-Urban-Planning-and-Land-Resources-Administration-Bureau, 2016). In recent years, Beijing has begun to focus on the refined design and renewal of public activity spaces in old urban areas, especially MUSs in “hutongs” and old settlements, thus providing residents with diverse, small-scale, and accessible public spaces.

The current situation reveals that MUSs, as small-scale urban public spaces at the micro level, have been widely considered by scholars and designers, and are an important carrier of residents' activities. However, previous studies in various countries have mainly summarized design strategies by considering practical cases such as pocket parks (Labuz, 2019), street corner spaces, community MUSs, etc. Relevant quantitative studies are still mainly focused on public spaces such as medium- and large-scale parks and squares in cities, and there are fewer studies on small-scale urban public spaces.

Environmental indicators affecting the vitality of urban public spaces

To derive the elements of MUSs in cold regions that affect vitality, the studies on public space should first be sorted out. The elements that may affect public activities are outlined at two levels: the macro level is concerned with factors like the land-use mix, street integration, and building density; the micro level is concerned with factors at the near-human scale, such as the place design, spatial size, and interface morphology.

In terms of spatial distributions and functional patterns, Montgomery (Montgomery, 1998) argued that many factors can influence urban vitality, including the land use, building diversity, street-level store density, nighttime lighting support, street performances, and vendors. Higher street integration obtained using spatial syntax usually implies greater accessibility and thus greater urban vitality (Giles-Corti, Broomhall et al., 2005; Ruiz-Apilánez, Karimi et al., 2017). Cao (Cao, 2015) integrated behavioral snapshot analysis to confirm that street connectivity can promote public activity, and suggested that a pedestrian space in the front areas of buildings can enhance the frequency of public activity. The mixed nature of businesses is often considered to be effective in enhancing the intensity and density of outdoor public activities. The data collection methods usually include behavioral notation combined with GIS visualization analysis (Shirazi, 2020), or the use of mobile location data (Wu, W., Niu et al., 2021).

Regarding the spatial scale and interface design, the height difference between the activity place and the sidewalk (Gehl, 1987), the street height-to-width ratio (Ashihara, 1984), the number of lanes (Choi, Kim et al., 2016), and the spatial layout (Askarizad and Safari, 2020) can affect the psychological perception of users, and thus can influence public activities. In addition, MUSs are closely related to buildings in terms of spatial location, so the design assumptions of building interfaces can have an impact on public activities. Among them, transparency was described by Jacobs as one of the characteristics of the best streets Jacobs (1993). Building interface materials can affect the thermal environment by influencing the microclimate and therefore the thermal comfort of pedestrians (Mutlu, Yılmaz et al., 2018). Edney (Edney, 1976) proposed that the special marking of places, residents, or communities can make places more personalized and recognizable, and stores with distinctive architectural interface styles or frequently changing store signs and window displays have higher attractiveness and will enhance the pleasure of pedestrians while walking.

Regarding greenery and public facilities, Whyte (Whyte, 1980) observed in cities that people usually seek shade provided by trees, awnings, eaves, and buildings, so bus stops provide good meeting places for residents due to the sitting facilities and shade. Furthermore, he investigated the impacts of seating and landscape facilities in MUSs on vitality. The presence of greenery, such as trees and grass, affects the way people move in outdoor spaces and increases the number of social activities (Sullivan, Kuo et al., 2004). For cold cities, the green view (Aoki, 1987), tree canopy cover (Yilmaz, Külekçi et al., 2021), and landscape structure (Tandoğan and Şişman, 2018) all affect public activities by influencing thermal comfort. Chapman et al. (Chapman, Nilsson et al., 2019) proposed the concept of cold urbanism, and, after a mental map study, suggested that blue-green landscape infrastructure could be upgraded to blue-green-white landscape facilities. Mehta’s (Taylor, 2014) empirical study showed that compared to neighborhoods without public seats, neighborhoods with public seats have a stronger social atmosphere. Gehl proposed that all types of street amenities affect the attractiveness of space to people (Gehl, 1987).

Researchers in various countries have revealed the roles of various environmental elements in influencing public activities. However, the correlation and influence degree of spatial environmental elements and activities have large differences due to the national conditions, urban areas, and construction levels of each country. The relevant research should be combined with the cold urban climate, as well as the scale characteristics of MUSs, to screen and add environmental indicators.

Methodology

Research and classification of micro urban spaces

The preceding literature review revealed that the definition of MUSs in academic circles is generally summarized, e.g., Whitney North Seymour's classification of these spaces into three types: street corners, within blocks, and through blocks (Seymour Jr, 1969). However, there is a dearth of detailed classification from the perspectives of the area scale, spatial location and morphology, spatial dependence on the main body, and spatial use function. Therefore, after field research in the present study, MUSs were classified into two categories, with the building interface as the dependency factor. Independent MUSs refer to a separate activity area mostly surrounded by urban roads, with a weak connection and articulation with buildings; examples include the remaining space under urban viaducts and the texture division zone represented by urban road parks. Marcus proposed that the area of MUSs is about 1-4 homestead area (about 400 m² each) (Marcus and Francis, 1997), but some dependent MUSs are smaller in scale, while independent MUSs are larger. The specific functions and area profiles are provided in Table 1, and the scale of partially dependent MUSs is smaller than that of independent MUSs.

Table 1. The classification of MUSs

Main	Secondary	Functions	Scale
Independent	Under an elevated bridge	Parking, recreation, commerce, greenery, walking through	800-4000m²
Independent	Segmen-tation	Recreation, greenery, display	200-800m² 800-4000m²
Dependent	Street corner	Parking, commerce, greenery, waiting	0-200m² 200-800m²
	Building boundary	Parking, recreation, commerce, greenery, show	0-200m² 200-800m²
	Building enclosure	Parking, recreation, greenery, show	200-800m²

Research and classification of public activities in micro urban spaces

Because spontaneous and social activities are the primary source of urban vitality (Gehl, 1987), public activities that are attracted by the spatial environment and that enhance the vitality of public space are taken as the main subject of observation of this study. Vitality is quantitatively measured by investigating the public activities in MUSs. After a field pre-study, the public activities that can effectively enhance vitality were classified into business, leisure, and social activities according to their intensity and behavior types (Table 2). Business activities include business waiting-and-seeing and business stays. Business waiting-and-seeing generally does not change the original route or activity status of users, but attracts them by the goods displayed in fixed stores or by mobile vendors. Business stays refer to a strong interest in a store or a commercial activity, which leads to stopping and is likely to occur with consumption behavior, generally lasting about 1-10 min. Leisure activities include leisure observation and leisure stays. Leisure observation generally refers to a brief lingering of the eyes that is attracted by an environmental element or activity in a public space. Leisure stays refer to the behavior of users for non-commercial reasons, including sitting, waiting, exercising alone, etc. The duration of leisure stays varies widely, from 10 min to 1-2 h. Social activities are usually communication activities in intimate groups, which emphasize the social attributes of the group and depend more on the quality of the environment and atmosphere of the place; these activities mainly include social conversation, social entertainment, and social fitness. In addition, the activity duration is classified into three categories: short viewing stays (passive viewing), short behavioral stays (active activities), and long behavioral stays (active participation and interaction) (Rajabi and Shrifian, 2022).

Table 2. The public activity type classification

Main	Secondary	Contents
Business activities	Business waiting-and-seeing	Viewing display windows or mobile vendor goods, etc.
Business activities	Business stays	Asking questions, buying goods, dining outdoors, etc.
Leisure activities	Leisure observation	Viewing of sculptures or public events, taking photos, etc.
Leisure activities	Leisure stays	Making phone calls, sitting quietly, working out alone, etc.
Social activities	Social conversation	Group conversation
	Social entertainment	Group entertainment such as chess, singing and dancing, instrument playing, etc.
	Social fitness	Group fitness such as Tai Chi, square dancing, etc.

Data collection

By combing previous theoretical and empirical studies and summarizing the additional elements based on MUS research in cold regions, the seven dimensions of the spatial distribution, functionality, spatial scale, interface design, degree of greenery, public facilities, and degree of maintenance were considered to explore their relevance to public activities. Among them, the orientation angle, interface design, greening degree, and shelter facility are assumed to affect the vitality in cold cities due to the microclimate. Due to the limited area of MUSs, whether the size of the area and the complexity of public facilities affect the vitality are questions that require investigation. Among the public facilities, informal seats refer to facilities such as flower terraces or fences with a height suitable for people to sit, and it was found that informal seats play an important role in attracting people to stay. Full use was made of various open-source data from major platforms during the data collection process (Table 3), which included the OSM files in Open Street Map, Baidu Map POI data, Baidu Map satellite photos, and on-site field measurement data. Baidu Map is a map service provider with the leading collection team and collection equipment in China, and provides abundant panoramic data. The street view panorama has covered 95% of the cities in China, and the coverage rate of functional formats in China has reached 98%.

Table 3. The environmental elements affecting the public activities in MUSs in cold regions

Main	Secondary	Indicators and Formula	Sources
Spatial distribution	Integration degree	Calculated by spatial syntax (OSM data were crawled and corrected)	Giles-Corti, Broomhall et al. (2005); Ruiz-Apilánez, Karimi et al. (2017)
	Perspective integration degree
	Orientation Angle	Measured by Baidu Map	Supplement based on Cold Cities Survey
Functionality	Total functional formats	Calculated by GIS (Baidu Map POI data within a 200-m radius of MUSs were crawled and corrected)	Montgomery (1998); Roozkhosh, Molavi et al. (2022)
	Functional mix
	Number of retail and shopping formats
	Number of catering formats
	Number of leisure and entertainment formats
	Number of service businesses
	Fixed vendors	Recorded by field researchers	Supplement based on Cold Cities Survey
	Mobile vendors	Recorded by field researchers	Supplement based on Cold Cities Survey
Spatial scale	Area of the space (m²)	Measured by Baidu Map	Gehl (1987) Ashihara (1984); Askarizad and Safari (2020); Choi, Kim et al. (2016)
	Height difference with the sidewalk (m)	Height difference with the sidewalk = number of steps × 0.15 m Recorded by field researchers
	Street height-to-width ratio	Street height-to-width ratio = height of buildings along the street opposite the space / distance between buildings along the street on both sides Calculated by researchers (Streetscapes were photographed by field researchers)
	Lane width (m)	Lane width = number of lanes × 3.5 m Recorded by field researchers
	Enclosure	Enclosure = length of buildings / perimeter of the space Measured by Baidu Map
Interface design	Transparency	Transparency = ((① class interface length × 1.25) + (② class interface length × 1) + (③ class interface length × 0.75) + (④ class interface length × 0)) / perimeter of the space (① completely open storefront, ② transparent glass window, ③ advertising glass window, ④ opaque solid wall or flat advertisement) Calculated by researchers (Streetscapes were photographed by field researchers)	Edney (1976); Jacobs (1993); Mutlu, Yılmaz et al. (2018)
	Number of materials	Recorded by field researchers
	Number of colors	Recorded by field researchers
	Degree of personalized design	Measured by field researchers (Average score from 1-5 points)
Degree of greenery	Lawn coverage	Lawn coverage = lawn area / area of the space Measured by Baidu map	(Aoki, 1987; Sullivan, Kuo et al., 2004; Yilmaz, Külekçi et al., 2021)
	Green shadowing rate	Green shadowing rate = vertical projected area of trees / area of the space Measured by Baidu map
	Green visual rate	Green visual rate = green pixel value / total pixel value Calculated by researchers (Streetscapes were photographed by field researchers)
Public facilities	Distance to the nearest bus stop	Calculated by GIS (Baidu map POI data were crawled and corrected)	Whyte (1980)
	Distance to the nearest parking space
	Distance to the nearest toilet
	Shelter facilities	Recorded by field researchers	Supplement based on Cold Cities Survey
	Monitoring facilities		Chapman, Nilsson et al. (2019); Gehl (1987); Tandoğan and Şişman (2018); Taylor (2014)
	Lighting facilities
	Formal seats
	Informal seats
	Commercial seats
	Self-contained seats
	Landscape facilities
	Signs
	Sanitary facilities
	Amusement facilities
Degree of maintenance	Tidiness	Measured by field researchers (Average score from 1-5 points)	Supplement based on Cold Cities Survey
Degree of maintenance	Pavement integrity	Measured by field researchers (Average score from 1-5 points)	Supplement based on Cold Cities Survey

Traditional methods for quantifying the vitality of public space include indirect and direct description quantification. Via the indirect description quantification method, evaluation questionnaires regarding the built environment, such as the traffic accessibility and micro-quality of a space, are usually used to describe spatial vitality. The methods for this include the analytic hierarchy process (AHP) (Joo, Lee et al., 2011), the expert scoring method (Wang, G. H., Wei et al., 2012), the semantic differential (SD) method (Kang and Zhang, 2010), etc. However, residents' spontaneous reports of activities often do not objectively reflect the direct correlation with the real spatial characteristics and ignore spatially dynamic subjects. The direct description quantification method provides a direct description of the spatial and temporal dynamic characteristics of public activities, and the field survey method is the main way to obtain data. In recent years, scholars have mostly used mobile phone location data (Wu, W. and Niu, 2019), GPS data (Wu, J., Ta et al., 2018), social media data (Wu, C., Ye et al., 2018), etc., to conduct more efficient and macroscopic research under the development of information and communication technology (ICT). However, MUSs are the most microscopic units of urban public space with a high mobility of activities. For small-scale, widely dispersed MUSs, the data must be precise. Therefore, field observations, although time-consuming and costly, remain the main method for investigating MUS activity. Data collection methods can be combined with data crawling and field research, and the behavioral mapping approach has evolved to the collection of snapshots that are taken at regular intervals (Hou, Chen et al., 2020).

Vitality intensity is usually quantified as crowd density (Liu and Shi, 2022). However, the limitations of a single number of people do not fully reflect the quality of activities, so the concepts of vitality stability (Guo, X., Chen et al., 2021) and activity diversity (Wang, M., Qiu et al., 2021) have been introduced. Because the mobility of activities in MUSs is one of their main properties, to more intensely reflect the intensity of MUS vitality S, the number of people engaged in each type of public activity / (MUS heat * MUS area) was chosen as the index.

S j , k = ∑ i = 1 n N i , j , k H i , j × A , ……………………………………………………………(1)

S k = 1 m × ∑ j = 1 m S j.k , …………………………………………………………… (2)

S = ∑ k = 1 q S k , ……………………………………………………………(3)

where S j , k is the vitality intensity of the k-th type of public activity on day j, N i , j , k is the number of people engaged in the k-th type of public activity on day j in the i-th observation period, H i , j is the heat on day j in the i-th observation period, A is the area of the space, n is the number of observation periods, m is the number of observation days, and q is the number of activity types. In this study, n = 6, m = 2, and q = 3 (respectively representing business, leisure, and social activities). The collection of the number of activities was conducted by timed snapshots for behavior mapping, indicating the basic status of the users' gender and age, the activity type, etc., and counting the number of different types of public activities. MUS heat data were collected by Baidu Map, indicating the number of users positioned in the area determined by cell phone base stations and synchronized with the behavior snapshot collection time, and the total value of heat within a 200-m radius of the MUSs was collected. The probability of activity in this MUS among the total population within this range in the current period is indicated by the ratio of the number of participants to the heat of the space. The area of the space was measured by Baidu Map, and the ratio of the number of participants to the area of the space is used to express the activity density.

Workflow of field research and data analysis

Harbin, China, a typical cold city, is characterized by a high degree of influence of seasonal changes on public activities. The transition seasons each year are in April and October, when the temperature respectively rises and falls rapidly, and the temperature is relatively low but outdoor public activities remain abundant. Public activities in this period are more influenced by the built environment. In this study, MUSs with different construction periods in the main urban area of Harbin were selected, and the samples were screened in terms of whether the spatial environmental elements were distinctive and whether public activities were abundant. A sample of 32 independent and 61 dependent MUSs was selected.

Via the all-day timed snapshots obtained in the pre-study, it was determined that public activities began to occur at 06:00, and basically ended at around 20:00. Therefore, the formal research was conducted on weekdays and weekends to weaken the influence of chance factors on the research results and to more comprehensively reflect the overall situation of activities. To avoid the influence of unfavorable weather such as thunderstorms on outdoor activities, days with better weather were selected for the research. Each sample was observed once in a 2h observation period between 06:00 and 20:00.

Because more environmental elements that may have an effect on vitality were selected in the preliminary stage, and because not all independent variables have a statistically significant effect on the dependent variable, correlation analysis was first conducted on the initial environmental elements and vitality. Pearson’s correlation analysis was used for continuous variables, while the independent t-test correlation analysis was adopted for categorical variables to screen out the statistically significant elements. On this basis, the screened elements were normalized to the data using z-score standardization, and multiple linear regression analysis was performed to establish an optimal regression model. Therefore, by comparing the input and stepwise multiple regression models, the model with a larger adjusted R2 value, i.e., a higher degree of explanation, was selected as the final model. The variance inflation factors (VIFs) between the respective variables were calculated to exclude multicollinearity among the independent variables. The closer the VIF value is to 1 (the theoretical minimum value of the VIF is 1), the weaker the multicollinearity. Generally, VIF < 10 means that the independent variables have weak multicollinearity.

Results Analysis

Results and Analysis

Public spaces and public activities analysis

Public spaces

The survey documented the environmental elements of the samples in seven aspects. The findings reveal significant variations between the two types of micro spaces in terms of the area, street height-width ratio, degree of greenery, degree of maintenance, and public facilities, including seats and shelter facilities.

(1) Spatial scale

It is found that 75% and 50% of the samples of independent MUSs are respectively larger than 1800 m² and 2250 m². Regarding the dependent MUSs, 75% of the samples are smaller than 600 m², and all samples are smaller than 2000 m². More than 75% of the dependent MUSs have a height-to-width ratio (H/D) larger than 0.64, with the highest value being 4.50, whereas the ratio of independent MUSs is less than 2.45, and over 50% of the samples have an aspect ratio of less than 0.74. This demonstrates that independent MUSs typically have a larger area and provide a wider perception.

(2) Degree of greenery

The maximum value of the lawn coverage in the independent samples is 0.85, the average value is 0.37, and the green shadowing rate in more than 50% of the samples nearly reaches 0.30 with a maximum value of 1. Regarding the dependent samples, 25% have a lawn coverage of 0, 25% have a green shadowing rate of 0, and the values of both were found to be less than 0.1 in more than 50% of the samples. More than 75% of the dependent samples have a green visual rate of less than 0.35, and the maximum value and median of the green visual rate in the independent MUSs are higher than those in the dependent MUSs. According to the investigation, independent MUSs generally have higher levels of greenery than dependent MUSs.

(3) Degree of maintenance

Among the independent MUS samples, 50% have tidiness and pavement integrity scores greater than 3.30. Among the dependent MUS samples, the median scores of the two indicators were respectively found to be 2.72 and 2.87, whereas those for independent MUSs were respectively found to be 3.28 and 3.38. Generally speaking, independent MUSs are better maintained than dependent MUSs (Figure 1).

Figure 1. The analysis of public spaces

(4) Public facilities

Among the 11 public facilities surveyed, for eight of them, the proportion of their appearance in independent MUSs was found to be 10% higher than the proportion of their appearance in dependent MUSs (Figure 2). Therefore, public facilities in independent MUSs are more complete than those in independent MUSs. Monitoring facilities, signs, informal seats, and sanitary facilities are also far more numerous than other facilities, whereas formal seats and amusement facilities are relatively rare.

Figure 2. The analysis of public facilities

Public activities

The survey documented 7437 activities in total, 4186 of which occurred in independent MUSs and 3251 of which occurred in dependent MUSs. The average number of public activities per MUS for the two types was calculated. In general, the vitality intensity was found to display a time-dependent M-shaped distribution (Figure 3). Beginning at 06:00, the morning exercise crowd gradually appeared, and more business activities arose as a result of the morning street market. The morning rush then arrived by 08:00, and the crowds gradually grew but the pace of public activities slowed. The number of public activities increased in the morning, primarily for the elderly and children. Around 13:00, the number of public activities was reduced due to the elderly's propensity to take a lunch break, and it gradually began to pick up around 15:00. The number of mobile vendors progressively increased during the evening peak period. The number of evening events rose, and the majority finished at 20:00, including group fitness, taking a walk with family and friends, catering, etc. The busiest periods were between 10:00 and 12:00 and between 14:00 and 16:00.

Figure 3. The number of activities in different periods

Distinct age groups had different micro-environment activities (Figure 4). People over the age of 40 accounted for around 82% of activities in both types of MUSs, while youth under the age of 18 accounted for 5%. Elderly people over 60 years old were the most active group in the independent MUSs, whereas middle-aged people between 40 and 60 years old were the most active group in the dependent MUSs.

Figure 4. The proportions of users of different ages

In the independent MUSs, the frequency of different types of public activities, from most to least frequent, was as follows: social activities (52%) > leisure activities (48%) > business activities (0). In the dependent MUSs, the frequency of different types of public activities, from most to least frequent, was as follows: business activities (41.1%) > leisure activities (32.6%) > social activities (26.3%) (Figure 5).

Figure 5. The numbers of different types of public activities

In the independent MUS samples, the short viewing stays had the lowest percentage at 10.2%, while the long behavior stays had the highest percentage at nearly 50%. In the dependent MUS samples, about 58.1% of activities were short behavior stays, while only 15% were long behavior stays. The analysis reveals that people prefer to stay for an extended period of time in independent MUSs and for a shorter period of time in dependent MUSs (Figure 6).

Figure 6. The proportions of different types of public activities

Correlation analysis of built-environment and space vitality

First, a correlation study was conducted between continuous variables such as the area of the space, the lawn coverage, the total functional formats, and the vitality in independent and dependent MUSs (Table 4). Table 5 displays the results of the independent sample t-test used to verify categorical variables such as the existence or absence of fixed vendors and amusement facilities. The environmental elements that were found to have a strong link with the vitality intensity of microorganisms in both the independent and dependent MUSs were eliminated.

Among the variables of the degree of greenery, the lawn coverage and green visual rate were found to have strong positive relationships with the vitality intensity in independent MUSs. The same was found to be true for the three public facility factors of shelter facilities, informal seats, and amusement facilities. The vitality intensity of dependent MUSs was found to be related to the two dimensions of functionality and public facilities, including the total functional formats, the number of retail and shopping formats, the distance to the nearest bus stop, fixed vendors, mobile vendors, commercial seats, self-contained seats, and landscape facilities. Among these, the distance to the nearest bus stop was found to have a negative correlation.

Table 4. The correlation analysis

Main	Secondary	Correlation	Independent	Dependent
Functionality	Total functional formats	Pearson correlation	-0.038	0.310*
	Total functional formats	Sig. (two-tailed)	0.837	0.015
	Number of retail and shopping formats	Pearson correlation	0.108	0.405**
	Number of retail and shopping formats	Sig. (two-tailed)	0.557	0.001
Degree of greenery	Lawn coverage	Pearson correlation	0.386*	0.185
	Lawn coverage	Sig. (two-tailed)	0.029	0.154
	Green visual rate	Pearson correlation	0.593**	-0.004
	Green visual rate	Sig. (two-tailed)	0.000	0.977
Public facilities	Distance to the nearest bus stop	Pearson correlation	-0.127	-0.631**
Public facilities	Distance to the nearest bus stop	Sig. (two-tailed)	0.487	0.000

** significant at the 0.01 level;

* significant at the 0.05 level.

Table 5. The t-test analysis

Variable	Independent					Dependent
Variable	Sample	Mean	Standard deviation	t	p	Sample	Mean	Standard deviation	t	p
Without fixed vendors	28	8.275	12.467	-0.689	0.496	43	6.464	9.118	5.023	0.000*
With fixed vendors	4	13.123	18.241	-0.689	0.496	18	20.322	11.389	5.023	0.000*
Without mobile vendors	20	9.823	15.939	0.521	0.606	36	6.518	9.279	3.548	0.001**
With mobile vendors	12	7.312	6.048	0.521	0.606	25	16.363	12.400	3.548	0.001**
Without sheltered facilities	18	4.383	9.244	2.525	0.007**	50	9.857	11.395	0.996	0.323
With sheltered facilities	14	14.664	15.169	2.525	0.007**	11	13.719	12.791	0.996	0.323
Without informal seats	6	-0.677	1.023	0.840	0.045*	40	9.897	12.036	0.605	0.548
With informal seats	26	1.167	1.922	0.840	0.045*	21	11.804	11.032	0.605	0.548
Without commercial seats	25	10.217	14.360	-1.098	0.281	45	7.664	10.089	3.551	0.001**
With commercial seats	7	4.111	4.546	-1.098	0.281	16	18.679	12.174	3.551	0.001**
Without self-contained seats	26	6.011	6.735	1.518	0.188	44	7.513	9.669	3.592	0.001**
With self-contained seats	6	21.320	24.495	1.518	0.188	17	18.422	12.881	3.592	0.001**
Without landscape facilities	19	8.022	9.732	0.445	0.660	43	8.330	10.939	2.394	0.020*
With landscape facilities	13	10.138	17.169	0.445	0.660	18	15.864	11.850	2.394	0.020*
Without amusement facilities	22	5.214	6.953	2.562	0.016*	56	10.513	11.842	0.090	0.928
With amusement facilities	10	16.950	19.191	2.562	0.016*	5	11.008	10.237	0.090	0.928

** significant at the 0.01 level;

* significant at the 0.05 level.

Mathematical model of vitality

The variables with a substantial association with the vitality of the MUSs were identified via a correlation analysis. First, the vitality intensity was taken as the dependent variable, and linear regression was carried out via stepwise or input regression. Then, the equation with the highest R2 value was chosen, resulting in a multiple regression mathematical model, as shown in Table 6. In addition, the VIF values of several factors were computed, and the findings demonstrate that they are independent of one another with no significant linear correlation. A data analysis revealed that the green visual rate (0.458) > informal seats (0.201) > lawn coverage (0.170) > shelter facilities (0.117) > amusement facilities (0.095) are significantly correlated with the vitality intensity of the independent MUSs. Moreover, the distance to the nearest bus stop (-0.377) > mobile vendors (0.196) > the number of retail and shopping formats (0.182) > fixed vendors (0.136) > landscape facilities (0.122) > total functional formats (0.115) > self-contained seats (0.090) > commercial seats (0.040) are significantly correlated with the vitality intensity of the dependent MUSs. Finally, the mathematical models of MUS vitality during the transition seasons of cold regions were obtained as follows:

The vitality of independent MUSs:

S₁ = 27.101X₁+11.256X₂+5.155X₃+3.032X₄+2.645X₅; (4)

The vitality of dependent MUSs:

S₂ = 4.957X₆+3.190X₇+3.097X₈+2.324X₉+1.051X₁₀+0.097X₁₁+0.030X₁₂-0.044X₁₃, (5)

where X₁ is the green visual rate, X₂ is the lawn coverage, X₃ represents whether there are informal seats, X₄ represents whether there are shelter facilities, X₅ represents whether there are amusement facilities, X₆ represents whether there are mobile vendors, X₇ represents whether there are fixed vendors, X₈ represents whether there are landscape facilities, X₉ represents whether there are self-contained seats, X₁₀ represents whether there are commercial seats, X₁₁ is the number of retail and shopping formats, X₁₂ is the total functional formats, and X₁₃ is the distance to the nearest bus stop.

Table 6. The regression models

Model	R	R²	Adj. R²	Std. Error	D-W	Variable	B	Beta	t	p	VIF
Vitality intensity of independent MUSs	0.719	0.517	0.424	9.902	1.750	(constant)	-7.853		-1.831	0.079
						Green visual rate	27.101	0.458	2.309	0.005	1.225
						Lawn coverage	11.256	0.170	1.620	0.302	1.407
						Informal seats	5.155	0.201	0.632	0.208	1.302
						Shelter facilities	3.032	0.117	0.292	0.477	1.421
						Amusement facilities	2.645	0.095	0.132	0.553	1.359
Vigorous intensity of dependent MUSs	0.776	0.603	0.542	7.882	1.485	(constant)	5.026		1.177	0.245
						Mobile vendors	4.957	0.196	1.795	0.079	1.559
						Fixed vendors	3.190	0.136	1.294	0.202	1.444
						Landscape facilities	3.097	0.122	1.255	0.215	1.244
						Self-contained seats	2.324	0.090	0.816	0.418	1.599
						Commercial seats	1.051	0.040	0.378	0.707	1.471
						Number of retail and shopping formats	0.097	0.182	1.883	0.065	1.225
						Total functional formats	0.030	0.115	1.107	0.273	1.411
						Distance to the nearest bus stop	-0.044	-0.377	-3.498	0.001	1.521

Discussion and Inspiration

Theoretically, small-scale urban public spaces at the micro level effectively complement medium- and large-scale urban public spaces and play a significant role in the development of a multi-level urban public space network. Due to their small scale, dispersed distribution, and reflection of usage equity, MUSs in cold regions facilitate different kinds of public activities, and a good built environment may effectively enhance vitality in transitional seasons. This study investigated the relationship between the vitality intensity and spatial environment elements of MUSs in cold regions. It was discovered that three factors, namely functionality, the degree of greenery, and public facilities, have significant effects. These findings were revealed via the statistical analysis of environmental elements and public activities research data in the following seven dimensions: spatial distribution, functionality, spatial scale, interface design, degree of greenery, public facilities, and degree of maintenance. Because the distribution of MUSs is discrete, and because the public activities of users in outdoor spaces are frequently chosen sporadically and are more determined by functional elements, the factors of the spatial distribution and degree of maintenance do not correlate with activity intensity, and the public activities in dependent MUSs, which are closely related to the building interface, are not influenced by the interface design.

Independent micro urban spaces

Independent MUSs are mainly used for leisure and social activities, and their vitality intensity is mainly influenced by the degree of greenery and public facilities. The increase in lawn coverage and the green visual rate can attract people to approach or even enter the space, which makes the MUSs more attractive and positively affects the psychological state of users. Shelter facilities and seats can improve the proximity and convenience, enhance the sense of security, and provide a place to rest for a while. Amusement facilities enrich the functionality and playability of the whole area. In terms of functionality, the locations of the independent MUS samples show that they are far away from stores, and the field research revealed that the users do not have commercial needs; thus, the distribution of businesses and the presence of vendors do not have significant impacts. In the spatial scale dimension, independent MUSs tend to have an area that meets the community green space design standard, so there is no significant correlation between the vitality intensity and area, since the calculation index includes activity density. In the public facilities dimension, the distance between bus stops and parking spaces does not affect the vitality intensity, further indicating that users of independent MUSs tend to be residents on foot; these are mainly elderly people over 60 years old who tend to use the MUSs closest to their residential area for leisure and social activities due to physical limitations. Regarding the seat design, people in independent MUSs prefer to sit on informal seats such as flower terraces, which are low in height and easy for people to use with their own cushions. Formal seats distributed in a parallel pattern are not convenient for users to sit around and chat or play cards, so the vitality is weakly influenced by formal seats.

Thus, the construction goal of independent MUSs can be summarized as enhancing leisure and entertainment, and the optimization strategy should be carried out from the two main aspects of green landscape design and the composite design of shelter and rest facilities. For MUSs with a relatively limited area, the accessibility of the landscape should be improved, and green pavement and seats should be placed in areas to allow people to stay and talk for a short period. Moreover, public spaces with different degrees of privacy should be created with low wall greenery in MUSs. In winter, the space can be converted into a place for ice sculptures or a pocket park for snow recreation. Studies have found that tree ponds, steps, parking stakes, and other types of seats with heights close to sitting height more significantly promote social activities. As an offshoot of post-modernist landscape, micro-architecture plays a role in outdoor public spaces, and, in cold cities, it also plays a role in improving climate comfort. Thus, sitting and resting facilities can also be combined with temporary installations to create spaces that provide shelter from the wind and rain, where people can rest and chat.

Dependent micro urban spaces

Dependent MUSs are mainly used for commercial and leisure activities, and they are dependent on the adjoining buildings. The total functional format, the number of retail and shopping formats, and the number of fixed and mobile vendors can enhance the functionality of these MUSs, and the setting of commercial seats provides diversity for business activities. Abundant commercial contents can better meet the consumption needs and promote social and business activities. Factors in the spatial scale dimension were not found to have any influence on vitality, which indicates that dependent MUSs are essentially more demanding in terms of functionality and practicality, and have no special requirements for the spatial scale and interface design. In practice, however, a certain activity area can form a pleasant and relaxed environment and support more functions, thus promoting public activities. In the public facilities dimension, bus stops bring more opportunities for activities, and the vitality intensity gradually increases as the distance from the nearest bus stop decreases. The presence of bus stops provides more residents with the opportunity to discover the existence of dependent MUSs and stay there for a short period. In addition, people have a lower need for formal seats because of the presence of self-contained seats and dependent objects such as walls. At the level of greenery, because dependent MUSs place more emphasis on functional needs and contain more human-built-up landscapes, the presence of landscape facilities can improve the appreciation and walkability, but the lawn coverage and green visual rate do not have a significant impact on the vitality intensity.

Thus, the construction goal of dependent MUSs can be summarized as enhancing functionality, and the optimization strategy should mainly be carried out from the two aspects of site selection in locations with sufficient existing resources and commercial atmosphere creation. First, MUSs that are close to city bus stations and that facilitate informal business activities should be given priority for renovation. In addition, the area can be guaranteed by combining the existing space with traffic stabilization transformation. The space created by narrowing the road section can be used as a place for a "parklet" in good weather, parking at night, and snow piling in winter. By reducing the turning radius around intersections, the curb extension will reduce the speed of traffic and the distance pedestrians have to walk on the road. The outward space not only expands the original outdoor public space, but also allows the installation of seating compounded with landscape facilities, thus enhancing the interaction between users and public spaces under the area limitation.

Conclusion

As land resources become tight and scarce, people's demands for urban public spaces are becoming stronger, and urban public spaces must be transformed into having high quality and refinement. In the process of stock optimization and refinement, MUSs should not be neglected, but should be triggered and utilized to facilitate public activities and enhance spatial value. Because of their discrete distribution and large number, MUSs can provide a more equitable public space and make significant contributions to the public activities of urban residents. This study analyzed the collected data via multiple linear regression models to explore the factors that affect the vitality of urban MUSs in cold regions during transition seasons by constructing an MUS vitality measurement method and an index system of environmental elements. According to the results, design strategies were provided to optimize different types of MUSs. During the research process, the main limitation was the small sample. In the future, this method can be used to model and predict the MUSs vitality for different urban contexts, and further, the vitality changes can be investigated under different seasons to form urban design guidelines for MUSs in cold cities. In addition, spatial and activity data collection methods should be developed for small-scale public spaces, where the existing manual collection efficiency is low and the accuracy of big data capture is insufficient.

Author Contributions

Conceptualization, S.L. and Yang Y.; methodology, S.L. and Yang Y.; software, S.L.; investigation, S.L., H.C., Yuhan Y. and Y.H.; resources, Yang Y.; data curation, Z.W.; writing—original draft preparation, S.L., H.C., Yuhan Y., Y.H. and Z.W.; writing—review and editing, S.L. and Yang Y.; supervision, Yang Y..

Ethics Declaration

The authors declare that they have no conflicts of interest regarding the publication of the paper.

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