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Article

Identifying Spatiotemporal Circles of Residents’ Daily Walking in Historic and Modern Districts: An Empirical Study in Nanjing, China

by
Rui Wang
1,2,3,
Hengliang Tang
1 and
Yue Chen
1,2,*
1
School of Architecture, Soochow University, Suzhou 215123, China
2
China-Portugal Belt and Road Joint Laboratory on Cultural Heritage Conservation Science, Suzhou 215123, China
3
Urban Planning and Transportation Group, Department of Urban Science and Systems, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
*
Author to whom correspondence should be addressed.
Land 2025, 14(7), 1321; https://doi.org/10.3390/land14071321 (registering DOI)
Submission received: 26 April 2025 / Revised: 9 June 2025 / Accepted: 19 June 2025 / Published: 21 June 2025
(This article belongs to the Special Issue Planning and Designing Livable and Sustainable Regions: Integrating Urban and Regional Perspectives)
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Abstract

:
The study explores the features of spatiotemporal circles of residents’ daily walking. Through a survey of residents’ walking activity in 16 residential communities, the walking purpose, distance, time, and speed of different residents were analyzed, and the circles of residents’ walking activities in historic and modern districts were identified. It is found that residents’ walking activities showed obvious spatiotemporal and individual differences. Walking activities on weekdays mainly focus on short distances (0.5–1 km) and short duration (5–15 min) for commuting and basic needs, while walking activities on weekends tend to be longer distances (more than 2 km) and longer duration (15–40 min) for leisure purposes. There are significant differences in distance and speed between walking activities in the historic and modern districts, with residents of the historic districts walking a smaller range but more diverse destinations, and residents of the modern districts walking to a wider range but fewer types of destinations. The study provides a scientific basis for multi-circle planning strategies of community life units, and it contributes to the localized adaptation of the “15-minute city” concept by revealing how historical and modern districts shape distinct spatiotemporal circles for walkability in Chinese cities.

1. Introduction

In the context of sustainable development and accelerated low-carbon transformation, how to improve the quality of urban walking environment has become an urgent and challenging issue. As the most environmentally friendly way of transportation, walking not only plays an advantageous role in short-distance travel but also reduces noise and air pollution, increases opportunities for communication and interaction, and improves mental and physical health. In recent years, with the rise in the construction of the “15-minute city”, more and more cities have begun to pay attention to the spatiotemporal characteristics of residents’ walking activities and their implications for urban community planning [1,2], and walkability has gradually become one of the key indicators of sustainable urban development [3,4].
Since the beginning of the 21st century, numerous new urban humanism theories and practices have emerged in response to the uncontrolled expansion, environmental pollution, and traffic safety issues caused by car-centric cities [5]. They advocate for buses, bicycles, and walking as primary modes of transportation, promoting fair, healthy, and sustainable lifestyles. In addition to prioritizing the planning of pedestrian-related facilities and pathways, they also suggest ensuring the accessibility and comfort of walking activities through appropriately scaled residential communities and street spaces, emphasizing the significant role of improving walking space quality in enhancing urban vitality and social development [6]. With the emergence of ideals such as traffic calming, shared space, complete communities, as well as the spread of low-carbon mobility ideas, the contributions of walking to physical health, environmental protection, and neighborhood vitality have also been recognized and valued [7].
The development of walkable communities echoes the 11th Sustainable Development Goal (Sustainable Cities and Communities) proposed by the United Nations, which focuses on making cities more livable, green, and inclusive, with the aim of ensuring that urban development provides a safe, healthy, and inclusive living environment for all. Improving walkability at the community level can bring many benefits in terms of living, social, economic, cultural, and ecological aspects, and is conducive to enhancing the safety, comfort, and livability of the living environment [8]. The construction of walkable communities can make use of the opportunity of urban renewal to improve the neighborhood environment, and satisfy the residents’ desire for better lives [9]. At an international level, the implementation of urban agendas can trigger walkability on an integrated and place-based approach that could be inspired by adopting innovative proximity models, such as superblock-based approach that can guarantee the fulfillment of this relevant goal [10] because it aims to create healthier, more inclusive, and resilient environments [11,12]. In China, high-quality development and sustainable communities are at the core of urban construction, and the national and local governments are actively supporting the development of walkable communities through policy measures [13]. In 2022, China released the “Guidelines for the Construction of Complete Residential Communities”, which outlined standards for the appropriate scale of residential communities and the layout of facilities, advocating for the planning of 15 min and 5 min community life units.
Although community planning has taken into account the time costs of residents’ daily commutes, it rarely aligns with the walking characteristics of different groups, instead relying on average estimates based on time, distance, or speed [2,14]. It is evident that different districts within a city, due to variations in urban planning methods, result in diverse forms of residential communities and should not adopt the same facility layout strategies. Research has shown that the existing 15 min community living circle facility layout exposes issues of inequality [15] and still has limitations in supporting elderly walking activities [16,17]. Therefore, it is necessary to expand the survey population to include different age and gender groups and conduct comparative studies between historical and modern districts.
The spatiotemporal circle refers to a community planning approach that determines the appropriate size of life circles and the layout of facilities based on the spatiotemporal characteristics of people’s walking activities. The study aims to establish a basic model that considers factors such as walking destinations, departure times, duration, and speed, while emphasizing differences in population and districts, to further guide and validate the rationality of urban planning or design. First, by conducting an activity log survey in 16 communities in Nanjing, China, the group differences in residents’ daily walking activities are analyzed. Then, the spatiotemporal circles of residents’ walking activities in historic and modern districts are identified. Finally, the implications of the walking activity patterns of different districts, times, and objects for urban planning and construction of community life units are discussed.

2. Literature Review

2.1. Purpose of Walking

Two forms of daily walking can be distinguished according to their purpose: walking to and from specific destinations is known as utilitarian walking, and walking for recreation and exercise is known as leisure walking [18]. Utilitarian walking is walking to reach a specific destination, with a greater emphasis on travel efficiency and destination accessibility. Leisure walking is more focused on physical health, social interaction, and environmental aesthetics.
Diverse destinations were found to be strongly associated with different types of walking behaviors [19], e.g., the abundance of residential, retail, office, healthcare, recreational, and cultural amenities were all strongly associated with utilitarian walking, and public space and sports facilities were more likely to affect leisure walking [20]. Improving the connectivity of the road network is an effective way to improve the accessibility of walking [21] and has a positive effect on both utilitarian and leisure walking [22]. Sense of security affects participation in different types of walking activities and has a greater impact on leisure walking [23]. Conveniently accessible parks and green spaces can help increase the frequency of walking activities [24], and green open spaces can also promote the occurrence of leisure walking [25]. In addition, the density of pedestrian amenities is more correlated with the frequency of leisure walking in more economically advantaged locations [25], while aesthetic features were found to be one of the factors significantly correlated with leisure walking in less developed neighborhoods [26]. Increasing the number of stores, streetlights, and cameras can reduce pedestrians’ fear of crime [27], contribute to the promotion of leisure walking [28], and nighttime walking [29], and improve the mental health of older adults [30]. Air pollution and traffic noise are also important factors affecting the comfort of leisure walking [31].

2.2. Walking Speed

As a critical metric of mobility, walking speed reflects both individual health status and environmental constraints [32,33]. It has been found that the average walking speed of a normal human is about 4 to 5 km per hour, although this is highly dependent on subjective factors such as height, weight, and age [34,35], as well as objective factors such as traffic flow, road surface, and terrain [33,36]. For example, younger people tend to walk faster than older people, men of the same age will walk faster than women, people who have an exercise and fitness routine may also walk more quickly, and factors such as limb length, body mass index, and dietary and medical conditions can also affect walking speed [37]. Walking on sandy beaches or along rocky trails may be slower than walking on flat sidewalks, and people may slow down to observe (about 0.44 m/s) or speed up (about 1.32 m/s) when crossing roads with faster traffic speeds [38].
Walking speed also varies by country/region, with Americans averaging the fastest walking speed (1.32 m/s), Singaporeans averaging a moderate speed (0.73–0.78 m/s), and Australians averaging the slowest speed (0.44 m/s) in large cities with a population size of at least 4.1 million. A study comparing pedestrian walking speeds in 31 countries/regions around the world showed that Western Europe and North America, which are predominantly developed countries, have relatively fast walking speeds, while developing countries and regions have relatively slow walking speeds [39].

2.3. Walking Distance

Distance to destinations is one of the most important factors influencing willingness to walk [40]. Mailboxes, bus stops, convenience stores, newsstands, shopping centers, and transit stops within 400 m walking distance, and schools, transit stops, newsstands, convenience stores, and shopping centers within 1500 m were found to be associated with regular walking [41]. Increased distance between neighborhoods and central business districts decreases levels of walking activity [42], and amenities or public spaces within a 15 min walk of a home are more likely to be visited [43]. Acceptable walking distances vary across countries and regions, e.g., the average acceptable walking distance to school or work for Indians is 714 m, most Japanese over 65 are willing to travel within 1 km to their destination [44], and acceptable walking distances for middle-income households in Thailand are shorter than for low-income households [45]. Research in China shows that people who usually walk more are willing to accept an average commuting distance of 2.6 km, while those who usually walk less are willing to accept a commuting distance of 3.4 km [46].
Acceptable walking distances are also an important consideration in Transit Oriented Development (TOD) for determining station locations and service areas. Planners typically use a walking distance of 400 m (about a 5 min walk) for bus stops and 800 m (about a 10 min walk) for train stations. This criterion varies from place to place, e.g., the average walking distance for subway and train stations in Bangkok, Thailand, is 320 m [47], in Delhi, India, it is 590 m [48], and in Munich, Germany, it is 1500 m [49].

3. Materials and Methods

3.1. Practice of the “15-Minute City” in China

Based on the idea of “Chrono-urbanism”, Carlos Moreno proposed a polycentric model of the “15-minute city” consisting of a series of walkable neighborhoods in 2016, with the aim of enabling urban residents in highly populated areas to meet most of their daily needs within a short walk or bike ride. The aim is to make it possible for urban residents in highly populated areas to meet most of their daily needs within a short walk or bike ride. The concept was developed from the idea of the “life unit” proposed by Japanese scholars in the mid-20th century, and it has been widely disseminated and applied in Asia (Table 1). In 2021, after observing the challenges of epidemics in different cities around the globe, Moreno further proposed a “15-minute city” polycentric model that includes the four dimensions of density, proximity, diversity, and digitization [1].
In China, the “community life unit” and “15-min life unit” are the main forms of the “15-minute city” [17]. The “Spatial Planning Guidance: Community Life Unit (2021)” defines the community life unit as a basic unit that meets the needs of urban and rural residents for work and life throughout their life cycle within a suitable daily walking distance, integrating the diversified functions of being suitable for work, residence, tourism, health, and schooling, and leading a future-oriented, healthy, and low-carbon better lifestyle. The “Guidelines for Building Complete Residential Communities (2022)” defines the 15-min life unit as “an area surrounded by urban arterial roads or site boundaries with a residential population of 50,000 to 100,000, a service radius of 800–1000 m, and connected with the management and service area of the neighborhoods and streets”. The “15-min Community Life Circle Planning Guidelines in Nanjing (2023)” defines 15-min life unit as a basic unit for ensuring people’s well-being, enhancing residents’ sense of belonging, promoting community governance, and building, sharing, and governing beautiful and livable homes. Based on the principle that residents can satisfy their physical and cultural needs within 15 min on foot, services and spaces for public activities are arranged to form a convenient, safe, comfortable, livable, and colorful environment for residents’ daily lives. In recent years, cities such as Shanghai, Chongqing, Wuhan, and Nanjing have carried out a series of useful explorations in the planning and construction of 15-min life units, and many practical cases have emerged [14,50].

3.2. Data Collection Through Walking Activity Logs

Early studies focused on residents’ perceived features of the built environment, collected subjective feedback through questionnaires and scales, and used mathematical models to explore the factors influencing walking activity [51]. Subsequently, measures such as the Walk Score have been used to objectively evaluate the walkability of urban spaces and have been found to correlate with residents’ subjective perceptions [52]. With the application of multi-source big data, the accuracy and extensiveness of walkability evaluation have been further improved [53,54]. However, less attention has been paid to the spatiotemporal characteristics of walking activities, especially the matching mechanism between the built environment and walking activities in community life units has not been fully explored.
The activity log is a systematic method of data collection in environmental behavioral research, which can provide insights into people’s behaviors, activity choices, and time allocation in different environments. By comprehensively analyzing the activity logs of multiple participants, researchers can attempt to identify common behavioral patterns or types of behaviors, which can help reveal the interactions between the environment and behaviors and provide a scientific basis for environmental design, planning, and management.
The investigation of residents’ walking activities was conducted from February to March 2022 in 16 residential communities selected from Xuanwu, Qinhuai, Jianye, and Gulou districts in Nanjing, China (Figure 1). The log asked random respondents to fill in their gender and age (111 males and 112 females were divided into four age groups according to quartiles: 24–29, 30–32, 33–38, and 39–55 years old), and to fill in the most recent day of walking activities on a weekday and a weekend day, respectively, in the order of occurrence, including the walking purpose, departure time, duration, and distance of each walking activity (Table 2). Fifteen logs were distributed in each community, and finally 223 valid logs were recovered, with an effective rate of 92.9%, containing 446 valid walking records (one each on a weekday and a weekend day).

4. Results

4.1. Spatial Features of Residents’ Walking Activities

4.1.1. Destination

Residents’ destination choices for walking activities reflect their daily needs and the rationality of the distribution of neighborhood amenities. As shown in the results (Figure 2), the proportional distribution of the types of destinations for walking activities on weekdays is relatively close for both male and female residents. In walking activities on weekdays, residents of both genders have work as their main destination and use the subway for commuting. However, female residents are more likely to use public transportation as a supplementary mode of travel, while male residents are more involved in walking to pick up and drop off their children. In terms of walking activities on weekends, residents of both genders prefer to engage in shopping. Male residents are more likely to spend time outdoors relaxing and exercising, while female residents prefer beauty treatments or getting together with family or friends for a meal. The smallest differences between the two in the proportion of walking activity destination types were leisure walks and cafes/bars, suggesting that they also share some options on weekends.
Walking destinations for residents of different ages show significant diversity (Figure 3). Walking activity on weekdays is related to residents’ occupational status, with younger residents using the subway for commuting more often, while the middle-aged group chooses to travel by public transportation more often. Walking activity on weekends is related to residents’ health and leisure needs, with the younger group preferring to walk to commercial places such as shopping streets and Chinese restaurants, while the middle-aged group prefers to go to parks for leisure walking.

4.1.2. Distance

The distance of walking activities reflects the convenience of residents’ daily travel, as well as the spatial accessibility. As can be seen from the results of the analysis (Figure 4), residents of both genders are similar in terms of walking distances, they both tend to walk a shorter distance, specifically 0.5–1 km on weekdays, and the proportion of women walking a shorter distance is slightly higher than that of men, which may be related to the factor of needing to save time on the way to work. On weekends, residents of both genders tended to walk longer distances, with significantly higher proportions at 1–2 km and 2 km away, suggesting that people are more willing to spend time walking to longer distances on weekends, especially those located within 1–2 km of the walking distance.
Walking distances also vary considerably for residents of different age groups (Figure 5). Younger and older residents are more likely to walk shorter distances less than 0.5 km during weekdays. Residents aged 30–32 years old walk more at a distance of 1–2 km, while residents aged 33–38 years old walk more at a distance of 0.5–1 km. The percentage of residents walking beyond 2 km on weekends shows an increasing trend with age, indicating a preference for longer distances. Compared with weekdays, there is almost no walking activity within 0.5 km, and the percentage of 0.5–1 km is significantly reduced, indicating that the need for short-distance walking on weekends decreases, while 1–2 km becomes the main walking activity distance for young people.

4.2. Temporal Features of Residents’ Walking Activities

4.2.1. Departure Time

Certain types of walking activities occur at specific times of the day, such as going to work, going to school, and taking meals, etc. Therefore, it is necessary to understand the distribution pattern of walking activities by counting the time periods during which they occur. Data analysis shows (Figure 6) that walking activities of residents of different genders on weekdays mainly take place between 7:00 pm and 8:00 pm, which is in line with the prevailing time of going to work. A slightly higher proportion of female residents set off on foot at 7 o’clock than males, while a larger proportion of males went out after 9 o’clock. Unlike weekdays, walking activity on weekends occurs at scattered times throughout the day, with the highest percentages at 10:00 and 11:00, followed by 14:00 and 16:00, and with a larger percentage of females than males.
The characteristics of the time period when walking activities occur for residents of different ages are as follows (Figure 7). On weekdays, the proportion of residents walking out at 7:00 p.m. shows a decreasing trend with age, while the proportion of residents walking out after 8:00 p.m. shows an increasing trend. On weekends, the highest proportion of walking departures occurs at 10:00 and 11:00 and shows a decreasing and then increasing trend with age. The proportion of residents’ walking departures before 8:00 and around 12:00 decreases with age, which may be related to the need for more sleep. The proportion of walking departures between 12:00 and 16:00 reaches its maximum among 33–38-year-olds, suggesting that people in this age group prefer to participate in walking activities in the afternoon.

4.2.2. Duration

The duration characteristics of walking activities reflects the time spent by residents on daily trips. As can be seen from the statistical results (Figure 8), female residents have a slightly higher percentage of walking activities of less than 5 min on weekdays than males, indicating that they are more inclined to commute for short periods of time. The percentage of male residents in the time periods of 5–10 min and 10–15 min is higher than that of female residents, indicating that they are more likely to perform some short to medium distance walking activities. Residents of both genders have a smaller percentage of time periods of 15 min and above, suggesting that neither of them is willing to spend a longer time commuting on foot. In contrast, the walking activity characteristics of residents of different genders on weekends are closer to each other, with a concentration in the 10–40 min time period, suggesting that they all prefer to do some moderate or longer walks on weekends. Compared to weekdays, the proportion of residents who walk for less than 5 min and 5–10 min on weekends is significantly lower, and the proportion of residents who walk for more than 40 min was more than 10%.
There are also differences in the time residents spend on walking activities by age (Figure 9). As age increases, residents show an increasing trend in the share of weekday walking activities in the 5 min or less and 5–10 min time periods, and a decreasing trend in the 15 min or more time periods, suggesting that younger people are putting in more time on their walking commute. Residents in the 33–38 age group had higher percentages of both 10–15 min and more than 20 min than residents in other age groups, suggesting that they are more likely to participate in moderate and longer walks on weekdays. On weekends, older residents were willing to spend more time participating in walking activities, especially in the 15 min and longer time periods, but a significantly lower percentage in the less than 15 min time periods. In addition, residents in the 24–29 and 30–32-year-olds had a higher percentage of 15–20 min and 10–15 min walks than other age groups, suggesting that they more often walk for a moderate length of time.

4.3. Spatiotemporal Circles of Residents’ Daily Walking in Historic and Modern Districts

4.3.1. Walking Distance in Historic and Modern Districts

All respondents are categorized into historic and modern districts according to their location. Then the proportion of different walking activity distances on weekdays and weekends is separately counted. The results show (Figure 10) that residents of the historic district mostly (71%) need to walk less than 500 m on weekdays, while this proportion is only 20% in the modern district. Residents of the modern district need to spend more time and physical effort on their walking commute, as the percentage in the 0.5–1 km distance range is higher than that of the residents of the historic district, and 40% of them need to walk 1–2 km to reach their destination. For walking on weekends, residents of the historic district have a higher percentage of 0.5–1 km walking distance than residents of the modern district, while residents of the modern district have a higher percentage of 1–2 km and above 2 km walking distance than residents of the historic district.
There may be several reasons for the differences in walking activity distances in different districts. First, historic and modern districts differ in planning, e.g., historic districts are more compact and dense with more small-scale commercial and amenity facilities, so residents can meet their needs with shorter walking distances. Second, historic and modern districts differ in terms of transportation modes. As roads in historic districts are more congested, residents may prefer to walk to their destinations or reach the surrounding public transportation stations and bike-sharing parking spots by walking, while residents in modern districts may prefer private cars as a means of commuting. Thirdly, there are differences in lifestyles between historic and modern districts. Residents in historic districts may prefer to live near their workplaces or in places that are convenient for them, whereas residents in modern districts may prefer to live within their neighborhoods or in places with a better quality of the surrounding environment.

4.3.2. Walking Speed in Historic and Modern Districts

By calculating and comparing the speed of walking activities, it can be further revealed that there are significant differences in the walking speed of residents in different areas of Nanjing (Figure 11). The average walking speeds on weekdays are all faster than those on weekends, about 0.35 km/h, probably because there is a strict time limit for commuting, which motivates people to walk quickly. The walking speeds of residents in the modern districts were all significantly higher than those in the historic districts, with a difference of about 1.2 km/h, which may be related to factors such as population density, traffic conditions, and urban planning in the two areas. Generally speaking, modern districts have lower population density, more rational urban planning, smoother walking paths and better-maintained facilities, so residents can walk faster without much interference or obstruction when walking. Historic districts have higher population densities and relatively confined sidewalk space, so residents may encounter more obstacles and difficulties when walking. In addition, the historic districts have more cultural landscapes and distinctive shops along the streets, which can draw the eyes of pedestrians and thus slow down their walking speed.

4.3.3. Spatiotemporal Circles of Residents’ Daily Walking

Based on the above analysis, it can be seen that residents’ daily walking activities show obvious group differences. These differences are influenced by physical and psychological factors, and on the other hand, they are also the result of the combined effects of the neighborhood-built environment, including facilities, road network, landscape, etc. Depending on the differences in needs, the range of walking activities can often be divided into circles, usually determined by the appropriate walking distance, which in turn depends on walking speed and time spent. In order to further understand the spatiotemporal characteristics of residents’ walking activities, the types of walking destinations included in the modern districts and the historic districts according to the four walking distance-limited intervals of 0.5 km or less, 0.5–1 km, 1–2 km, and 2 km or more, are counted, respectively (Figure 12).
In the modern district, the spatiotemporal circle within 0.5 km mainly contains walking destinations such as subway stations, bus stops, snack bars, breakfast stores, and commercial streets, which are closely related to daily commuting, and the proportion of subway stations is the largest (57%), suggesting that transfer convenience needs to be met within a shorter distance. In the 0.5–1 km range in the modern district, the subway station is the most dominant walking destination (47%), followed by bus stops, office buildings, Chinese restaurants, shopping streets, kindergartens, and primary schools. In comparison, there is a decrease in transfer destinations within the 1–2 km time-circle range, with a significant increase in the proportion of shopping streets and office buildings. For walking distances over 2 km, the types of walking destinations in the modern districts are mainly composed of three categories: parks, stadiums/playgrounds, and places for leisure walking, indicating that people are more willing to walk long distances for recreation and exercise.
In contrast, the historic districts are characterized differently, with the most obvious feature being the availability of a richer variety of destinations through short walks (Figure 13). In particular, public transportation transfer stops are largely concentrated in the spatiotemporal circles within 0.5 km, and the proportion of subway stops (52%) is higher than that of bus stops (24%), suggesting that transfer trips are more dependent on subway transportation. Walking activities within this range also involve a certain number of commercial, dining, education, and workplaces, suggesting that short walks in the historic district fulfill most of the needs of daily life. Within the 0.5–1 km range, in addition to the characteristics described above, the historic district has a higher proportion of Chinese restaurants and shopping streets, which is associated with a more dense population and commercial activity, and access to a proportion of parks and stadiums. Residents of the historic district mainly walk medium and long distances for recreation and exercise, as the proportion of parks as walking destinations in the 1–2 km spatiotemporal circles accounts for 90% of the total, whereas the walking range beyond 2 km has only one type of activity, namely leisure walking, indicating that the daily walking range of residents of the historic district is significantly smaller than that of residents of the modern district.

5. Discussion

5.1. Optimization of District-Level Walking Environments Based on Residential Equity

Planning of urban communities should be closely integrated with the differences in walking needs based on districts and time. As a supplement to existing findings [55], this study further compared the spatiotemporal characteristics of walking activities of different types of residents in historical and modern urban areas. Due to the compact built environment of the historic district, commuting and basic living needs can be met by short-distance walking, but the dense facilities also lead to confined pedestrian space and slower walking speed. Therefore, the optimization of the historic district should focus on improving the comfort and safety of the walking environment. For example, widening sidewalks, installing more barrier-free facilities, reducing interference from motor vehicles, and optimizing the layout of commercial and cultural landscapes along streets are measures that can improve the walking experience [51]. At the same time, attention needs to be paid to the efficiency of the connection between subway stations, bus stops, and the surrounding facilities. There should also be attention paid to the design of three-dimensional traffic organization or underground passages to alleviate the travel pressure during peak hours [56]. In contrast, residents in modern districts walk more widely but to fewer destinations, at faster speeds, and mostly for longer commuting and recreational activities. Therefore, modern districts should enhance the diversity and accessibility of facilities to reduce the walking distance of residents, optimize the connection between public transport stops and the surrounding pedestrian system, and increase recreational facilities, such as parks and stadiums, to meet the leisure walking needs of residents.
Consistent with previous studies, it is found that urban morphology has an impact on walking behavior [57], but this factor is usually overlooked in existing planning of community life units in China [58]. Based on the analysis of walking speed, it can be inferred that residents of historical and modern districts can walk different distances in the same amount of time. Taking a 15 min walking activity as an example: Based on the average speed (4.18 km/h), the walking distance is about 1045 m; based on the average speed in historic districts (3.73 km/h), the walking distance is about 933 m; based on the average speed in modern districts (4.95 km/h), the walking distance is about 1238 m, which is 305 m longer than in historic districts. This demonstrates that, from the perspective of walking efficiency in community planning, historical and modern districts should be designed with different densities of facilities to balance distance and time costs. In practice, people consider directness when choosing walking paths [59], and environmental quality also influences the subjective perception of time spent [60]. The findings demonstrate that multiple factors should be considered when determining the scale of community living circles in different urban districts.

5.2. Planning of Walkable Community Life Units Based on Spatiotemporal Circles

Previous studies in other countries have found significant differences in walking demand between weekdays and weekends [61,62]. This study not only validated this pattern but also identified the temporal specificity of walking activities among the Chinese population. Unfortunately, current policies and practices have not adequately considered the temporal variation in walking activities in planning of community life units. Walking activities on weekdays mainly focus on short distances and duration for commuting and basic living needs, while walking activities on weekends tend to be longer distances and duration for leisure purposes. Therefore, the urban facilities should be dynamically managed according to residents’ actual usage and changes in demand. For example, the opening hours of parks, stadiums, and other recreational facilities on weekends should be increased to meet the demand of residents for leisure walking. In addition, there are significant differences in the purpose, distance, and time of walking activities among residents of different age groups and genders. For example, younger residents are more inclined to walk short distances to meet their commuting and basic living needs, while middle-aged residents are more inclined to walk long distances to meet their leisure and exercise needs. Therefore, the planning of community life units should fully consider the use of facilities at different times and enhance the dynamic adaptability of the community’s walking environment through differentiated configuration of facilities.
Based on the spatiotemporal circle analysis of walking distance and purpose, a multi-circle planning strategy for community life units can be proposed. It is found that the walking range of residents can be divided into multiple circles, and the functions and needs of each circle has its own focus. In the circle within 0.5 km, residents mainly satisfy their daily commuting and basic living needs, and should be equipped with basic living facilities such as subway stations, bus stops, stores, etc. It is recommended to locate public transportation stations near the entrances and exits of residential areas to maximize efficiency and reduce walking transfer distances, thereby providing more convenient walking transfer conditions. In the 0.5–1 km circle, residents’ walking activities are mainly related to shopping, dining, and education, etc. The layout of commercial streets, Chinese restaurants, primary schools, and kindergartens should be increased, and the connectivity and safety of the walking path should be optimized. In the 1–2 km circle, residents are more inclined to leisure and recreational activities, and parks, stadiums, and other public spaces should be arranged to meet their leisure walking needs. Green spaces can be divided into three types based on their size and location: street-level spaces, neighborhood-level spaces, and courtyard-level spaces, offering more options. In the circle of distance over 2 km, walking activities mainly focus on leisure and exercise, so it is recommended that an orderly landscape system be established. The walking system of communities should be connected to large parks and public green spaces to form a healthy and livable city [63].

5.3. Potential Applications

The spatiotemporal differentiation of daily walking behavior observed in this study offers multiple avenues for real-world applications. The multi-circle model not only provides a novel analytical framework but also serves as a functional tool for improving livability and efficiency of urban communities.

5.3.1. Urban Renewal and Community-Building Tools

The spatial patterns of walking intensity can guide targeted urban renewal strategies [64]. Districts with consistently low walking activity may indicate deficiencies in accessibility, public amenities, or environmental quality [65]. Urban planners can leverage this data to implement focused planning of community-level mixed-use facilities. Furthermore, the insights from spatial circle differentiation can support the planning and optimization of 15 min cities aiming to ensure that residents can access essential services within a short walking distance. These findings contribute to shifting the planning paradigm from car-oriented development to human-scale urbanism, which enhances both mobility equity and community cohesion [14].

5.3.2. Walking-Based Health Intervention Strategies

The integration of spatial and temporal dimensions of walking allows for more precise public health interventions [66]. Rather than adopting broad or static policies, city health departments can identify specific districts and time periods where walking activity is lower through life cycle assessments [67]. Customized interventions, such as organizing neighborhood walking campaigns, creating temporary pedestrian zones, or installing walking prompts, can be implemented to encourage daily walking activity. Health promotion programs can incorporate behavioral insights and align with the daily living rhythms of urban residents. For example, targeting afternoon low-activity periods in high-density residential areas with poor walkability can help reduce sedentary behavior and improve long-term health outcomes at the population level.

5.3.3. Data Integration and Evidence-Driven Planning

The spatiotemporal model of residents’ daily walking also serves as a foundational layer for integrating multisource urban data across sectors [54]. Walking activity maps can be combined with data on public transportation, air quality, and street view images [62]. This enables the construction of spatial decision support systems that serve multiple goals. In practical terms, urban managers can use the integrated system for simulation, such as estimating the impact of new infrastructure on walking behavior or testing interventions under different land-use or demographic scenarios. This data fusion empowers evidence-driven and forward-looking urban governance.

5.4. Limitations and Future Work

The study provides new insights into community living unit planning based on walking behavior, but there are still some limitations. First, the sample coverage was limited to 16 communities in Nanjing, which may not fully reflect the walking activity characteristics of residents in other cities. Second, the data collection period was focused on weekdays and weekends, and the potential effects of holidays, seasonal changes and extreme weather on walking behavior were not considered. Third, to ensure the efficiency of filling and protect privacy, respondents were only required to report their gender and age, which may not adequately reflect the diversity of the population.
Future studies will expand the sample to cover more cities and communities to verify the universality of the findings. The dynamic relationship between the spatiotemporal circles of walking activities and the spatial structure of cities will be explored in depth by analysis through Geographic Information System and multi-source big data. To construct walking-inclusive community life units, more individual attributes such as physical condition, income, and car ownership will be included in the activity logs, as these factors have been found to influence walking behavior [51]. Another question is what are the spatiotemporal characteristics of walking activity among people of different ages when they travel together? For example, there are significant differences in walking speeds between children and older adults, but they often travel together in China, so further investigation is necessary. In addition, the compatibility of different modes of travel in a 15 minute city will be explored, especially the mix of walking and other transportation.

6. Conclusions

The study systematically analyzed the characteristics of residents’ daily walking activities and the patterns of spatiotemporal circles in historic and modern districts through a log-based survey in Nanjing, China. The walking activities of residents in 16 communities show obvious spatiotemporal and group differentiation. Walking activities on weekdays are mainly short-distance and short-duration, which mainly satisfy the needs of commuting and basic life. Walking activities on weekends tend to be longer-distance and longer-duration, which are aimed at leisure and recreation. Walking activities in the historic and modern districts differ significantly in terms of distance, speed and purpose. The walking activity range of residents in the modern district is smaller but the destination choices are more diverse, while the walking activity range of residents in historic districts is wider but the destination choices are relatively fewer. The compact layout and abundance of walking facilities in the historic districts allow residents to meet most of their daily needs by walking short distances, while the low-density layout and fewer walking facilities in the modern districts force residents to rely on longer-distance walking or motorized trips. It was found that due to differences in walking speed, the average 15 min walking distance in modern districts is 305 m longer than in historic districts, indicating that the range of the community life unit needs to be adjusted according to its location in the city. In addition, the purpose, distance, and duration of walking activities vary according to the age and gender of the residents, with younger residents preferring short-distance walking for commuting needs and middle-aged residents preferring longer-distance walking for leisure and exercise. These findings provide a scientific basis for optimizing urban facility layout, formulating multi-circle planning strategies for life units, and building walkable communities. Moreover, the study offers practical guidance for creating equitable and dynamic urban environments that accommodate diverse walking patterns across different districts and demographic groups, thereby enhancing the overall quality of urban life and promoting sustainable development.

Author Contributions

Conceptualization, H.T. and Y.C.; methodology, H.T. and Y.C.; software, R.W.; validation, H.T. and Y.C.; formal analysis, R.W.; investigation, R.W.; resources, H.T. and Y.C.; data curation, R.W.; writing—original draft preparation, R.W.; writing—review and editing, H.T. and Y.C.; visualization, R.W.; supervision, H.T. and Y.C.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 52108058.

Data Availability Statement

The data are proprietary or confidential in nature and may only be provided with restrictions. The data presented in this study are available on request from the corresponding author.

Acknowledgments

We are grateful for help from the China Scholarship Council and Urban Planning and Transportation Group, Department of Urban Science and Systems, Eindhoven University of Technology.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Selected residential communities in the study area.
Figure 1. Selected residential communities in the study area.
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Figure 2. Gender differences in walking activity destinations.
Figure 2. Gender differences in walking activity destinations.
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Figure 3. Age differences in walking activity destinations.
Figure 3. Age differences in walking activity destinations.
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Figure 4. Gender differences in walking activity distance.
Figure 4. Gender differences in walking activity distance.
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Figure 5. Age differences in walking activity distance.
Figure 5. Age differences in walking activity distance.
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Figure 6. Gender differences in walking activity periods.
Figure 6. Gender differences in walking activity periods.
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Figure 7. Age differences in walking activity periods.
Figure 7. Age differences in walking activity periods.
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Figure 8. Gender differences in hours of walking activity.
Figure 8. Gender differences in hours of walking activity.
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Figure 9. Age differences in hours of walking activity.
Figure 9. Age differences in hours of walking activity.
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Figure 10. Comparison of walking distances in historic and modern districts.
Figure 10. Comparison of walking distances in historic and modern districts.
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Figure 11. Comparison of average walking speeds (km/h) at different times and districts.
Figure 11. Comparison of average walking speeds (km/h) at different times and districts.
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Figure 12. Spatiotemporal circles of residents’ daily walking in the modern district.
Figure 12. Spatiotemporal circles of residents’ daily walking in the modern district.
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Figure 13. Spatiotemporal circles of residents’ daily walking in the historic district.
Figure 13. Spatiotemporal circles of residents’ daily walking in the historic district.
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Table 1. Forms of “15-minute city” in different countries or cities.
Table 1. Forms of “15-minute city” in different countries or cities.
ServicesWalking TimeWalking DistancePopulation
Small life unit (Republic of Korea)Junior and senior high school, a small amount of employment and shopping<15 min1–2 km30–60,000 people
Fixed life unit (Japan)
15-minute life unit (Shanghai)Meeting physical and cultural needs of residents<15 min0.8–1 km50–100,000 people
Residential community life unit (Nanjing)A functional system for residents’ daily lives10–15 min0.5–1 km30–100,000 people
Basic community life unit (Nanjing)Services for the elderly and children5 min200–300 m0.5–10,000 people
Table 2. Survey form of walking activity log.
Table 2. Survey form of walking activity log.
PurposeDeparture TimeDurationDistance
Weekdays/Weekends1□ To or from a destination __________
(choose from the following options)		____:__________ minutes□ <500 m
□ 500 m–1 km
□ 1 km–2 km
□ >2 km
2□ Leisure walking____:__________ minutes□ <500 m
□ 500 m–1 km
□ 1 km–2 km
□ >2 km
1-store, 2-supermarket, 3-commercial street, 4-Chinese restaurant, 5-fast food restaurant, 6-snack bar/breakfast restaurant, 7-cafe/bar, 8-library, 9-hospital/clinic, 10-pharmacy, 11-barber shop, 12-bank/post office, 13-stadium/playground, 14-park, 15-high school/junior high school, 16-primary school/kindergarten, 17-bus stop, 18-subway station, 19-office building, 20-others __________
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Wang, R.; Tang, H.; Chen, Y. Identifying Spatiotemporal Circles of Residents’ Daily Walking in Historic and Modern Districts: An Empirical Study in Nanjing, China. Land 2025, 14, 1321. https://doi.org/10.3390/land14071321

AMA Style

Wang R, Tang H, Chen Y. Identifying Spatiotemporal Circles of Residents’ Daily Walking in Historic and Modern Districts: An Empirical Study in Nanjing, China. Land. 2025; 14(7):1321. https://doi.org/10.3390/land14071321

Chicago/Turabian Style

Wang, Rui, Hengliang Tang, and Yue Chen. 2025. "Identifying Spatiotemporal Circles of Residents’ Daily Walking in Historic and Modern Districts: An Empirical Study in Nanjing, China" Land 14, no. 7: 1321. https://doi.org/10.3390/land14071321

APA Style

Wang, R., Tang, H., & Chen, Y. (2025). Identifying Spatiotemporal Circles of Residents’ Daily Walking in Historic and Modern Districts: An Empirical Study in Nanjing, China. Land, 14(7), 1321. https://doi.org/10.3390/land14071321

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