Introduction

Small towns are widely regarded as a link between urban and rural areas that facilitate resource sharing, technology transfer, and information circulation. They play a crucial role in enhancing rural living standards (Kaufmann and Wittwer, 2019). Due to industrialization and urbanization, small towns in developed countries are generally fully urbanized areas with no farmland and other typical rural economic practices (Caselli et al. 2020). Meanwhile, in China, small towns continue to serve as spatial carriers for nearby urbanization (Farrell and Westlund, 2018; Zhu, 2000). Due to the continuous expansion of land for township construction and the consolidation of rural residential areas (Lu, 2015), the evolving urban–rural relationship has led to a mixture of urban and rural elements within small towns. This has led to a variety of residential areas exhibiting two distinct urbanization trends: urban- and rural-biased characteristics (Shi, 2018). These residential areas include urban communities and apartment resettlement areas (urban-biased) (Qiu et al. 2023) and homestead resettlement areas and rural settlements (rural-biased) (Gong and Zhou, 2007; Yan, 2010). Simultaneously, as farmers undergo a transition from a rural lifestyle to an urbanized one, involving the stages of local non-agriculturalization, passive urbanization, and gradual urban citizenship, residents of small towns are also in various stages of urbanization due to their varying abilities to adapt to different environments (Fan, 2015), with some residents experiencing either advanced (Li, 2018) or delayed urbanization (Qiu et al. 2021; Qiu et al. 2022a) compared to the spatial urbanization of their living areas. This complex human–land urbanization pattern poses difficulties and challenges to the construction of living environments in small towns in China.

The construction of public service facilities is a crucial leverage point to ensure and enhance the quality of the living environment. In the context of policies aiming to promote equal access to public services in urban and rural areas, China has intensified its efforts to construct living environments. Over the past decade, there has been a noticeable increase in the number of public service facilities in rural and township areas, leading to significant improvements in addressing facility shortages. Regarding the programming of spaces for public service facilities in small towns, China introduced the Standard for Planning of Town 2007. At the functional level, this standard adheres to the principle of comprehensively coverage of indicators in facility programming, emphasizing the construction of facilities according to rigid standards similar to those in urban areas. With respect to spatial planning, regulations have been established for site selection of facilities, ensuring minimum guarantees that are based on factors such as safety, transportation, and the environment. While this standard plays a positive role in the quantitative aspects of facility construction, there remains significant room for improvement in the meticulous development of facilities. Since the current standard does not consider the complex urbanization patterns in small towns, it fails to recognize the actual needs of residents at different stages of urbanization at the functional or spatial levels. Moreover, the classification guidance for facility programming for different urbanization patterns is insufficient, leading to a misalignment between supply and demand for public facilities and poor accessibility, resulting in the inefficient usage of idle and frequently used facilities that are not included in the public service system (Zhou et al. 2018). This inefficiency negatively affects the livability of residential environments in small towns and nearby rural areas (Ruth and Franklin, 2014). Therefore, in response to complex urbanization patterns in small towns, facility programming should address functional and spatial aspects. In prior research, the authors focused on facility functional programming. By analyzing residents’ needs and population attributes at different stages of urbanization, the study deduces the matching characteristics of the “residential area-resident-facility” relationship. Tailored to diverse human–land urbanization patterns, the study proposes the “required + optional item” public service facility guidance-control system (Appendix) (Qiu et al. 2023). As part of a series of publications on the programming of public service facilities in small towns, this study primarily focuses on the spatial level.

Many Western countries have adopted a perspective of time and spatial distance as the primary basis for the spatial layout of facilities. For instance, the Department for Levelling Up, Housing and Communities in the United Kingdom advocates walkability in the National Model Design Code: Part 2 – Guidance Notes, 2021, proposing that “people need to be able to meet most of their day-to-day needs within a walkable radius of their home.” Additionally, it emphasizes accessibility to green spaces, divides the time–space circle into layers, and presents surrounding walking distances in the form of circles and isochrones. In the Plan Melbourne 2017–2050, 2019, Australia integrated the concept of the 20 min neighborhood into its major infrastructure projects. Rather than adopting a single standard for the spatial arrangement of facilities, these Western countries have adopted a guidance-based approach. By contrast, Asian countries tend to regulate development through official standards and provide technical interpretations through guidance. Currently, in Asian countries, a method guided by the “life circle” theory has emerged for the circle partitioning mode and allocation of public resources (Li, 2019). This theory originated in Japan and was designed to reflect the movement of individuals from their residential areas to locations providing production and life services, presenting a layered form in space (Sun et al. 2012). In 2018, the life circle theory was introduced into China’s Standard for Urban Residential Area Planning and Design to explicitly guide the configuration of community public service facilities with regard to spatial–temporal walking distance, with a clear emphasis on human-centered values. Moreover, in 2021, the Ministry of Natural Resources issued Spatial Planning Guidance to Community Life Unit (2021). This guidance proposes the establishment of two levels of life circles for urban communities, namely, 15 min and 5–10 min, as well as for rural communities: “township centers” and “villages/groups.” Specifically, the former leans toward urban areas, whereas the latter is inclined toward rural settings. However, the guidance does not address planning methods for life circles in small towns that are semi-urban and semi-rural. In this context, recent guidelines, such as the Zhejiang Province Guidelines for Beautiful Towns and the Configuration of Life Circles (2019), provide direction for the planning of life circles in small towns. However, this guideline proposes a life circle radiating from a village–town–county coordinated region. It considers facility programming only as a component of the rural and township hierarchical configuration, rather than expanding it across the spatial plane. Additionally, it does not account for the complex urbanization patterns present in small towns. Furthermore, the guideline adopts a spatial–temporal distance model that is similar to that of urban areas. However, research has indicated that using a 15 min radius as the scope for a life circle requires the presence of an appropriate population density (Bian and Xi, 2018). For example, in 2017, the resident population density of established towns in eastern China was approximately 451 people/km², whereas it was approximately 329 people/km2 in central China (Feng, 2021). This is only about one-sixth of the population density in urban areas such as Shanghai. Therefore, the adoption of a single urban community life circle model between large cities and small towns is bound to cause inefficiencies. Given the uneven population density within small towns in China, life circle planning cannot be standardized with fixed, absolute spatial–temporal distances. Instead, it should be tailored to residents’ needs, indicating the relative distances between facilities. Adopting a resilient guidance approach to life circle planning, this study provides guidance for spatially categorizing public service facilities in a variety of residential areas in China. This approach further optimizes facility layouts, enhancing the overall quality of living environments in small towns.

Literature review

Urbanization development of small towns in China and challenges in the layout planning of their public service facilities

Small towns in China originated as markets for agricultural trade, gradually evolving into permanent communities with administrative management. This evolution has allowed small towns to integrate the characteristics of both urban and rural development (Fei, 1996). As urbanization progresses, some small towns have fully urbanized and resemble small cities, while others retain “semi-urban and semi-rural” characteristics (Yang et al. 2013). Taking two small towns in Zhejiang Province, China, as examples (Fig. 1), the different colored patches in the figure represent various types of residential areas. Both small towns exhibit mixed residential area types and show a polarization in the level of urbanization. Specifically, this includes urban community areas and apartment resettlement areas (urban-biased), as well as homestead resettlement areas and rural settlements (rural-biased). Due to the preemptive nature of planning, rural settlements exist even within the scope of township construction land. Geographer McGee was among the first to describe this pattern of element flow and reconfiguration between urban and rural areas as “Desakota” (an Indonesian term where “desa” means rural area and “kota” means town) (McGee, 1991), while other scholars refer to it as an urban-rural continuum (Halfacree, 2009). In residential areas with varying degrees of urbanization, there are also mixed residents from different stages of urbanization. Authors’ preliminary research found that the residents’ demand for two types of facilities, rural and non-rural, reflects their stages of urbanization (Qiu et al. 2023). Rural facilities refer to those that low-urbanization residents still rely on, which are specific to rural areas, while non-rural facilities are those available in both urban and rural areas. Based on this, the authors developed a classification framework dividing residents into four categories—A, B, C, and D (see Appendix-Fig. A3 for details on the classification and characteristics)—and clarified the matching relationship between residential areas and residents (Fig. 1- population percentage). Thus, the complexity of the human-land urbanization pattern in small towns poses challenges for layout planning. Internationally, relevant construction for the human living environment advocates a place-based approach (Atkinson, 2019) and a grassroots-driven development model (Bosworth et al. 2016). However, given China’s hierarchical political system and governance structure, which emphasizes top-down guidance and constraints (Cheng and Chen, 2023), it is impossible to fully implement a “one place, one policy” approach. Therefore, it is necessary to introduce the concept of “control + guidance” to direct the layout planning of facilities. This approach involves establishing baseline controls while allowing decision-making bodies with a certain degree of flexibility.

Fig. 1
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The mixed characteristics of diverse residential areas and inhabitants in small towns.

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Planning of differentiated life circles

The life circle theory has now been applied in areas such as optimizing urban spatial structures, improving infrastructure, and balancing public resource allocation (Xie et al. 2023). Given the diversity of goal orientations, the current life circle layered partitioning modes exhibit pluralism. In response to the need for optimizing facility configurations in small towns across China, the rational selection of a life circle layered partitioning mode is especially critical. This highlights the importance of analyzing current, well-developed, and practically proven life circle planning examples, in order to provide support for life circles planning in small towns. Life circle exploration in China initially aimed to optimize urban spatial structures. Over time, the focus has shifted to optimizing community public service facility configurations. The Standard for Urban Residential Area Planning and Design (GB50180-2018) proposed four levels of life circles within the community scale: 15-, 10-, and 5 min life circles as well as the life circle of the residential neighborhood. Urban community life circles, as delineated by the spatial–temporal distance division model, constituted a comprehensive reflection of humanistic values in urban development. This standard sets the maximum range based on individuals’ walking tolerance (Guo et al. 2016). Each layer precisely aligned community spaces with the distance that residents must travel to reach various facility locations, considering their travel habits. Urban communities, either with respect to type or quantity, exhibit much higher richness with multiple facilities offering similar functions than rural and township areas where most facilities only provide residents with a single choice. When their functional needs are satisfied, urban residents prioritize the principle of proximity (Lu, 2013). Therefore, the use of spatial and temporal distance as the division of life circles can be conducive for a fair and efficient distribution of resources, especially in urban communities. This model is more reasonable and feasible. Meanwhile, the characteristics of urban residential areas serve as fundamental conditions for the formation and development of life circles in the spatial–temporal distance partitioning mode. For urban residential areas, regulations for various types of residential land use are established at the overall planning level. The detailed planning level refines specifications based on relevant standards for residential areas (Huang et al. 2019). This standardized approach ensures the relative homogeneity of urban community spaces and enables the planning of distance standards for life circles for a relatively universal applicability. Urban areas exhibit a clear coherence in terms of spatial distribution (Salingaros, 2000). With a relatively concentrated and scalable population, this setup is conducive to a centralized and efficient allocation of public service facilities in the life circles layers.

In non-urban areas of China, many scholars also recognize that applying the partitioning mode of “spatial–temporal distance” to the planning of life circles is a practice of humanistic values (Kang, 2020; Wu, 2014). Since small towns differ significantly from urban residential areas in terms of population and density, considering allocation efficiency, most studies expand the scope of the life circle (Zhang, 2018). However, small towns are less standardized compared to cities, and the traditional “one-size-fits-all” approach to facility allocation overlooks the uneven degree of urbanization within residential areas of small towns. In addition to spatial–temporal distance, some studies advocate a hierarchical model for villages and towns (Liu et al. 2019), but this method merely uses the boundaries of residential units as the range for facility allocation, lacking a refined response. Compared to the residential areas in cities, small towns exhibit a mixed characteristic of both urban- and rural-biased residential areas. In rural-biased residential areas, due to the long-standing kinship and occupational ties in rural China, some residents exhibit a strong sense of “place attachment” (Karen et al. 2018). “Place attachment” refers to an emotional bond between an individual and a specific location; it involves the emotional attachment that people have to specific places, as well as to the relationships and objects related to these places (Diener and Hagen, 2022). The presence of place attachment allows residents to maintain traditional communal gatherings. This implies that certain facilities used for gathering, such as cultural auditoriums and ancestral halls, cannot break through residents’ psychological range (Shi, 2015). In addition, productive service facilities, such as those developed for the purpose of tourism, have transformed the traditional concepts of benefit distribution, gradually establishing a new universal ownership model involving the participation of all residents (Liu, 2015). The selection of the locations for such facilities also cannot break through residents’ psychological range, disrupting the traditional notion of non-exclusivity in public services (Cao, 2014). Thus, facilities that include a psychological range not only serve as venues for resident gatherings to maintain kinship relations, but also encompass the feature of residents spontaneously forming joint ownership. Even when these facilities are located in neighboring areas, they do not exert a radiating influence on other residential areas, and residents from those areas typically do not express a willingness to use them.

Given the widespread mixing of urban- and rural-biased residential areas in small towns, there is an urgent need to change perspectives and refine the layout of facilities for different residential areas. This requires understanding the “distance requirements” of residents within these areas. Additionally, some facilities are subject to specific limitations related to the “psychological range,” which should be identified during the determination of life circle models and the partitioning process. In summary, this study proposes a life circle partitioning mode that integrates both “distance” and “psychological range” dimensions, specifically for small towns in China.

Measuring residents’ distance requirements: distance sensitivity

In the distance-based partitioning mode of life circles, different layers correspond to residents’ distance preferences for facilities. Some facilities are preferred within closer layers, while others can be acceptable even at a greater distance. In such cases, considering the limitations of resources, facility siting only needs to ensure coverage within a certain “range.” Residents thus exhibit varying degrees of “sensitivity” to distances between different facilities. The concept of “sensitivity” is widely applied in research fields like geomorphology, with many scholars evaluating and measuring sensitivity for different subjects, such as landscape sensitivity and landscape visual sensitivity. “Landscape sensitivity” was first introduced by Brunsden and Thornes (1979), who defined it as a measure of a landscape’s responsiveness to external disturbances, including human-made and natural factors (Usher, 2001). “Landscape visual sensitivity” measures the extent to which changes in a landscape affect observers’ visual experience (Wang, 1993). Based on the above definitions, the term “sensitivity” can be summarized as “a measure of the system’s ability to respond to changes.” Specifically, in the context of distance sensitivity, it can be translated as “the change in people’s satisfaction as distance increases.” Some scholars have pointed out that the concept of sensitivity exhibits a certain pattern: “when a system’s ability to respond to changes reaches a certain range (quantitative change), it can trigger a condition that leads to a transformation (qualitative change) (Duan et al. 2023).” Distance sensitivity also reflects this characteristic, as some scholars have noted that residents have a certain acceptable range for the distance to facilities (Yu, 2019). Once this acceptable maximum travel distance is exceeded, residents may develop an intolerant attitude (Wu, 2014). By analyzing the definition and pattern of sensitivity, it can be inferred that for different facilities, the faster the rate at which the turning point is reached, the higher the distance sensitivity (Fig. 2). This implies that the facility should be located in a closer range. In light of this, this study takes distance sensitivity as the core consideration and uses it as the basis for the layered partitioning mode of life circles.

Fig. 2
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Illustration of the concept of distance sensitivity.

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Methods

Measuring distance sensitivity: indicator selection

The most direct way to determine residents’ psychological acceptance limits for different facilities is to inquire about their “tolerance distance” for these facilities. During the survey, the authors found that a “low tolerance distance” often reflects residents’ frequent use or a perception of high functional demand. Related studies have further proven that residents’ distance requirements for facilities are correlated with their usage frequency and functional demand (Chen, 2020). Scholars have summarized that residents’ behavioral rhythms gradually decrease from the inner to the outer layers of life circles. (Li, 2017; Liu, 2018). Studies have also pointed out that closer proximity should meet the most basic levels of need, with the distance from near to far reflecting a transition from core to peripheral needs (Zhu, 2017). This further supports the correlation between “usage frequency” and “functional demand” with distance sensitivity. Therefore, in cases where residents indicate a low tolerable distance, the life circle layers can be further subdivided based on these two indicators.

However, residents’ responses indicating a high tolerance distance can be categorized into two scenarios. First, a high tolerance distance may reflect infrequent use or lack of need for the facility. Second, it may result from “social desirability bias,” where respondents align their answers with societal expectations (Nederhof, 1985). For example, they may acknowledge that facilities cannot always be placed close due to distance or limited resources, or they may accept sacrificing proximity for important facilities (Li, 2018). Therefore, a reported “high tolerance distance” may not accurately reflect true distance sensitivity and should be evaluated based on actual usage and needs.

Construction of a model framework for suitable life circles in small towns

Based on the previously described distance sensitivity indicators, the study selects three indicators: tolerance distance, functional demand, and usage frequency. The latter two reflect actual needs and usage, helping to further subdivide life circle layers for low tolerance distance responses and correct high tolerance distance answers influenced by social desirability bias or cognitive limitations. Some facilities discussed in Section “Planning of differentiated life circles” have the psychological range that requires identifying the boundaries where residents form kinship and community relationships. This is typically reflected in the range of the residential area where residents live or in the combination of several residential areas. Other facilities need to be confined within the scope of township construction land.

For facilities with low tolerance distance, residents believe they need to be located nearby, reflecting high distance sensitivity. Therefore, these should be categorized into life circles based on distance levels, with this study designating this level as Distance Level 1/1’. Within the same level, due to the correlation between usage frequency, functional demand, and distance sensitivity, further subdivision of the layers can be made (1/1’−1, 1/1’−2, 1/1’−3).

For facilities with high tolerance distance, residents believe they can be located further away. If both usage frequency and functional demand are at a low level, this reflects residents’ low distance sensitivity. The configuration of such facilities can be within the psychological range or the scope of township construction land. If residents frequently use the facility or have high functional demands for it, this reflects that residents, influenced by inherent cognitive limitations, are willing to sacrifice some distance to access it, meaning it is not an absolute case of low distance sensitivity. Therefore, this study defines it as medium distance sensitivity and establishes the life circle as distance level 2/2’. At this level of high tolerance distance, the life circle is further subdivided based on usage frequency and functional demand (2/2’−1, 2/2’−2). Based on the above analysis, this study proposes the determining principles for the life circle layered partitioning mode of small towns (Table 1) and constructs a “tolerance distance-usage frequency-functional demand” model framework for suitable life circles (Fig. 3).

Table 1 Determining principles for the life circle layered partitioning mode of small towns.
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Fig. 3
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“Tolerance distance–usage frequency–functional demand” suitable life circle model framework.

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Establishment of the research framework

The research framework is shown in Fig. 4. The author’s preliminary research categorized residents at different stages of urbanization based on the differing functional demands of “rural and non-rural” facilities. Both existing literature and the author’s field interviews reveal a positive correlation between functional demand and distance sensitivity (Zhu, 2017). Therefore, residents with varying degrees of urbanization may exhibit different levels of distance sensitivity towards “rural and non-rural” facilities. Verifying this hypothesis will provide support for further exploration of the partitioning of life circles among different resident groups within this classification framework. Therefore, this study first validates whether there are significant differences in distance sensitivity indicators based on the previous classification of residents’ urbanization stages. Then, based on the determining principles for the life circle layered partitioning mode and the model framework for suitable life circles, an analysis is conducted on the life circle layered characteristics of residents at different stages of urbanization. Finally, through the principle setting of a flexible plan for “basic assurance + optimization enhancement,” a life circle layer program is proposed for rural- and urban-biased residential areas.

Fig. 4
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The research framework.

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Analysis and survey methods

Measurement methods for the Indicators

To identify residents’ cognitive understanding of the indicators of usage frequency, functional demand, and tolerance distance, this study uses separate scales.

Usage frequency

Considering the subjective ambiguity in people’s perception of usage frequency, this study categorizes usage frequency across four scales with fuzzy semantics: “almost daily use,” “frequent use,” “occasional use,” and “not in use at all,” with values of 4, 3, 2, and 1, respectively.

Functional demand

The prior research on function programming employed the Kano model to assess residents’ hypothetical levels of satisfaction with the provision or absence of certain facilities. It introduced a framework of “rural & non-rural” facility need coupling model, identifying four stages of urbanization among residents. It analyzed residents’ functional cognitive attributes for different facilities in the four urbanization stages. These functional attributes encompass four hierarchical levels, namely, must-be quality, one-dimensional quality, attractive quality, and indifferent quality. Must-be and one-dimensional quality imply that residents would be dissatisfied if the facility were not provided; therefore, this study categorized these two attributes as indicating high functional demand. In contrast, attractive quality indicates that the provision of the facility enhances satisfaction, but its absence is inconsequential, whereas indifferent quality indicates the presence or absence of the facility does not impact satisfaction. Consequently, this study classified these attributes as low functional demand.

Tolerance distance

Based on the correspondence between residents’ transportation choices and travel times in the pre-survey, and further estimating the corresponding distances based on the average speed of different modes of transport, the first level of tolerable distance is set as 0–1 km (walking within 20 min or electric scooter within 5 min), the second as 1–6 km (using an electric scooter within 5–20 min), and the third level as 6–20 km (10–40 min by bus). The preliminary analysis indicates that some facilities may exhibit characteristics of non-distance demand. This study, in addition to the division of tolerance distance levels, introduces an “indifferent” option. The four options are assigned values from low to high, relative to tolerance distances, with values of 1, 2, 3, and 4, respectively.

Subsequently, the study investigates the usage frequency, functional demand, and tolerance distance for residents in Groups A, B, C, and D to understand how the life circles of residents are stratified at different urbanization stages.

Classification of facility types

To clarify the research scope, this study constructed a public service facility type library for small towns by reviewing national and local regulations, policy guidelines, and relevant literature on public service facilities in rural and urban communities, and by conducting field observations of frequently used facilities that have not yet been incorporated into the public service facility system. Building on the author’s previous research, this study follows the classification of rural and non-rural facility types and uses the criterion of whether a facility is used by residents for gatherings, maintaining kinship, or forming self-organized shared ownership to further identify rural facilities with psychological ranges, creating a “rural and non-rural facility” type library (Table 2).

Table 2 “Rural and non-rural facilities” type library.
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Investigation process

This study uses survey samples from the previous study regarding the functional programming of public service facilities in small towns. The sample chosen is that of S town in Zhejiang Province, which exhibits the typical characteristics of a semi-urban and a semi-rural area (Appendix-Figs. A1, A2). The residential areas in S Town are diverse, covering all types of urban- and rural-biased residential areas, making it highly representative. The questionnaire survey was conducted alongside the previous investigation using a semi-structured interview approach to minimize biases from factors like residents’ education levels.

To ensure a good representation of the surveyed population, this study selected weekdays and weekends (weekday: July 7–8, 2022, weekend: July 9–10, 2022). Research personnel were assigned to conduct surveys in each residential area block. Efforts were also made to maintain a balance in data collection quantities between urban- and rural-biased residential areas. A total of 260 questionnaires were distributed, and after excluding incomplete responses, 252 valid questionnaires were considered in this study, with 112 from urban-biased and 140 from rural-biased residential areas.

Results

Characteristics of usage frequency and tolerable distance for residents at different urbanization stages

In section “Measuring residents’ distance requirements: distance sensitivity”, tolerance distance, functional demand, and usage frequency were selected as the three indicators to measure distance sensitivity. Previous research has already demonstrated the differences in functional demands for “rural and non-rural” facility types across different stages of urbanization. To verify whether there are significant differences in distance sensitivity to different facilities among people at different stages of urbanization, it is also necessary to validate whether their perceptions of usage frequency and tolerance distance for the two types of facilities exhibit similar grouping characteristics. In this study, a qualitative judgment of overall trends was employed. Coordinate axes were established adopting usage frequency as the X-axis and tolerance distance as the Y-axis. The average values of usage frequency and tolerance distance for each facility were calculated separately for Groups A, B, C, and D and were then mapped onto the coordinate system to create scatter plots. The contour lines of the concave polygons formed by the scatter points for each group were drawn (Figs. 5, 6) to identify overall trends in data distribution for the different groups. From the overall frequency and tolerance distance perceptions of the four groups regarding non-rural facilities (Fig. 5), the scatter points for Group C (low non-rural/low rural facility demand) are generally more toward the left-upper region compared with the other groups. This indicates a more negative perception of the frequency and distance requirements for facilities among those in Group C relative to those in the other groups. The enclosed area formed by scatter points for Groups B and D (high non-rural facility demand) is larger than that for Groups A and C (low non-rural facility demand), with the larger part distributed within the right- and left-bottom regions (low frequency, nearby layout). This suggests an association between functional demand and perceptions of usage frequency and tolerance distance among the four groups regarding non-rural facilities. The overall frequency and distance perceptions of rural facilities (Fig. 6) show that Groups C and D (low rural facility demand) have perceptions that are mostly distributed across the left-upper quadrant (low frequency, distant layout), whereas Groups A and B (high rural facility demand) have a relatively larger area, with the larger part distributed across the right-bottom quadrant (high frequency, nearby arrangement). This correlates with the high demand for rural facilities in Groups A and B.

Fig. 5
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Scatter plot for usage frequency and tolerance distance to non-rural facilities for four groups of residents.

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Fig. 6
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Scatter plot of usage frequency and tolerance distance to rural facilities for four groups of residents.

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Overall, there are differences in the trends for perceptions of usage frequency and tolerance distance among groups at different urbanization stages. This also indicates that there are significant differences in distance sensitivity to “rural and non-rural” facilities among these populations. Therefore, it is feasible to continue the exploration of life circles using this classification. Due to the shared characteristics within each group, it is reasonable to use average values to measure trends in frequency and tolerance distance for different groups. This study uses average values for frequency and tolerance distance as facility scores for each group, setting the overall mean (\(\bar{{\rm{f}}}\)) and (\(\bar{{\rm{d}}}\)) as the boundaries for high and low usage frequency and tolerance distance, respectively.

Residents’ life circle layers at different stages of urbanization

This study separately calculates average usage frequency and tolerance distance for 59 facilities for Groups A, B, C, and D. The overall mean is used to divide high from low levels. Integrating these results with the findings for functional demand from the previous study, the data are incorporated into the life circle model framework. This enables the generation of life circle hierarchies for residents at different stages of urbanization (Table 3, Fig. 7).

Table 3 Average usage frequency, average tolerance distance, functional importance, and life circle layers for individuals in Groups A, B, C, and D.
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Fig. 7
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Life circle layer of residents at different stages of urbanization.

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Discussion: proposal of a life circle layer program for rural- and urban-biased residential areas

Distinct from the traditional value system of urban public service facility layered layouts that fully adhere to the principle of proximity (Li, 2017), this study introduces a life circle model framework based on “distance-range” synergy, tailored to the complex patterns of human-land urbanization differentiation in small towns. In addition to facilities similar to those in urban areas that fully adhere to the proximity principle, there are two types of facilities whose layouts are constrained by “range.” The first type, while following the proximity principle, is also limited by a “psychological range.” This perspective not only responds to the “self-sufficiency” characteristic of rural and township areas proposed by relevant scholars (Xin, 2014; Guan, 2021) but also aligns with the concept of social life circles in rural and township areas (Wang, 2015). Building on these ideas, this study further analyzes the hierarchical distance demand within such “social life circles.” Another type of facility does not follow the principle of proximity at all. Instead, their locations can be within a defined regional range. The layered outcomes of “Township Construction Land” (abbreviated as TCL in Table 3) further validate the actual existence of such facilities. Results show that some of these facilities are unsuitable for placement near residential areas, such as temples (which may cause psychological discomfort for residents) and agricultural machine shops (which generate environmental noise pollution). These characteristics align with the concept of “NIMBY(Not in My Backyard)-related facilities” proposed by relevant scholars (Chiou et al. 2011). In addition, this category of facilities also includes those that serve specific groups, such as service stations for the disabled and broadcasting stations. Scholars have introduced the concept of “subsidiary facilities (Xu et al. 2020),” precisely because these facilities have low location requirements for most residents. Therefore, their placement can be based on their usage characteristics and attached to other facilities, providing further guidance for facility layout. The identification of whether a facility follows the proximity principle also addresses the issue raised by scholars regarding the lack of financial support for infrastructure construction in small towns in China, which has constrained their development (Shen et al. 2018). This study, based on this recognition and understanding, proposes a suboptimal solution under resource-constrained conditions.

In terms of spatial layout demand evaluation methods, this study uses distance sensitivity to measure residents’ facility spatial layout demand, establishing a coupling relationship among multiple indicators to reflect distance sensitivity. Considering the potential cognitive biases of the general public (Nederhof, 1985), this study improves upon the approach used by other scholars, who directly rely on tolerance distance (obtained through inquiries) as an indicator of residents’ spatial layout demand (Sun et al. 2012). Instead, this study corrects it by incorporating individualized, objective facility usage characteristics (usage frequency) and subjective perceptions of facility function importance (functional demand). The correctness of this approach was previously validated in the authors’ exploration of rural public service facility functional attributes (Qiu et al. 2022b). The life circle model (based on three indicators) established in this study not only determines the relative proximity of facilities but also reflects residents’ urbanization groups and differences. This is an advancement and refinement of past research, which tended to treat small-town residents as an indistinguishable whole, assuming that everyone’s needs converge (Shi, 2020; Huang et al. 2021). The study, particularly through analyzing the scatter points of facility usage frequency, tolerance distance, and functional demand to form the contour of concave polygons, verifies the clustering effect on the distance sensitivity to rural and non-rural facilities within groups of different urbanization levels. This further proves the feasibility and accuracy of the life circle model proposed in this study and provides a foundation for determining the life circle layers of four types of population groups.

The results in Section “Residents’ life circle layers at different stages of urbanization” show that 33 facilities (55.93%) have significantly different life circle layers across the four types of population groups. For Groups A and B, some rural facilities do not have the attribute of psychological range, especially those associated with agricultural industries, such as agricultural materials shops and product sales sites; these facilities can be arranged using a proximity pattern. For Groups C and D, rural facilities, excluding film screening venues and cultural auditoriums, can be organized using a distance pattern. Other facilities should be organized within the scope of township construction land or psychological range. Welfare-oriented non-rural facilities such as home aged care service centers and villager canteens should be situated nearby for Groups A and B that are low urbanization stages. Conversely, hospitals, specialized clinics, and department stores, as non-rural facilities should be positioned in close proximity for Groups C and D. In the life circle layers for Group D, no facilities exist at Distance Level 2, suggesting that individuals in this group do not entertain the idea of sacrificing spatial distance for facilities, even if they consider certain facilities as highly important. They maintain an attitude of intolerance toward spatial distance for facilities.

Appendix-Fig. A4 illustrates the composition of the four groups in different residential areas. Urban-biased residential areas are primarily occupied by Groups B, C, and D, whereas rural-biased residential areas are primarily occupied by Groups A, B, and C. To establish life circles for the two types of residential areas, a comprehensive solution must be derived that considers the life circle layers for all three groups.

For both residential areas, the three groups of residents exhibit similar or differing life circle layers. Where the layer is the same, this study adopts that level as the result for the life circle layer. For facilities with cognitive differences among residents, there are two sides with different levels of residents’ service expectations regarding layout. For minimum assurance for the layout, the first step should be avoiding the dissatisfaction of those with lower service expectations, rather than meeting the needs of all at once (Wu, 2019); subsequently, the life circle layers of those with higher service expectations should be met. Consequently, a flexible approach of basic assurance + optimization enhancement is employed. The specific steps are as follows:

It is assumed that the cognitive attributes of the three groups for n facilities are denoted as Cn1, Cn2, or Cn3 (n∈[1,59], C∈[1,6]). The cognitive attributes of the three groups regarding life circle are ranked from nearest to farthest (service expectations of facility layout from highest to lowest) as Cni, Cnk, and Cnj. The basic assurance plan is defined as meeting at least two groups’ life circle requirements for each facility (taking the value Cnk); meanwhile, the optimization enhancement plan is defined as meeting the life circle requirements for all groups (taking the value Cni). The formula for calculating these plans is as follows:

$${{\rm{C}}}_{{\rm{ni}}}=\,\min\, [{{\rm{C}}}_{{\rm{n}}1},{{\rm{C}}}_{{\rm{n}}2},{{\rm{C}}}_{{\rm{n}}3}]$$
$${{\rm{C}}}_{{\rm{nj}}}=\,\max \,[{{\rm{C}}}_{{\rm{n}}1},{{\rm{C}}}_{{\rm{n}}2},{{\rm{C}}}_{{\rm{n}}3}]$$
$${{\rm{C}}}_{{\rm{nk}}}={{\rm{C}}}_{{\rm{n}}1}+{{\rm{C}}}_{{\rm{n}}2}+{{\rm{C}}}_{{\rm{n}}3}-{{\rm{C}}}_{{\rm{ni}}}-{{\rm{C}}}_{{\rm{nj}}}$$

The final formation of the life circle for rural- and urban-biased residential areas is presented in the basic assurance + optimization enhancement plan (Fig. 8). Decision-makers can use this plan to first extract residential areas, identify the patterns of human–land urbanization and their evolution trends, and merge adjacent residential areas with similar levels of urbanization into residential patches. They should delineate the life circle range for each residential patch, integrate and adjust facilities based on the spatial proximity relationships proposed in this plan. Additionally, they should consider the collaborative sharing of facilities within overlapping life circle areas across different residential areas. For facilities that foster place attachment, protection should be ensured within the psychological range to meet the needs for group belonging and cultural identity.

Fig. 8
figure 8

The life circle basic assurance + optimization enhancement plan for rural- and urban-biased residential areas (dashed lines represent paths of optimization enhancement).

Full size image

At the practical level, considering the efficiency of facility allocation in low population density areas, existing research and guidelines for facility allocation in small towns generally tend to expand the life circle range based on the 15 min urban life circle and propose explicit spatial–temporal distances. For instance, the Guidelines for the Allocation of Town and Village Life Circles in Jining (2021) suggests a 5 min, 15 min, 30 min urban-rural life circle hierarchy. Scholars (Dong, 2021) propose a primary life circle of 1 km, an intermediate life circle of 3 km, and an advanced life circle of 8 km. The spatial–temporal distances and ranges proposed by different studies and current guidelines vary. Small towns exhibit significant heterogeneity in their geographical and socioeconomic development, displaying diverse characteristics while commonly facing the challenge of uneven development (Xiong et al. 2020). The application of specific spatial–temporal distances may lead to mismatches with real-world conditions during actual implementation. To address the extreme imbalance in small towns’ characteristics, this study controls and guides the differentiated life circles planning for urban- and rural-biased residential areas. It reveals the relative hierarchical relationships of facilities at the spatial level and proposes an operational method for facility spatial planning under the current theme of stock renewal.

Conclusions

China’s current standards for the programming of public service facilities follow a one-size-fits-all approach. This standard has successfully addressed the aspect of quantity over the past decade; however, currently, it is necessary to develop a targeted approach to enhance the quality of these facilities. Small towns, as transitional areas between urban and rural regions, have a strategic position in the urbanization process. Under the influence of urbanization, small towns may exhibit a dual urbanization that is characteristic of complexity among residents and residential areas, posing significant challenges to the construction of public service facilities. Methods of facility programming in small towns differ from those used in rural and urban areas and cannot be directly applied to relatively mature urban programming methods. In the context of China’s governance system, there is a need for standards that simultaneously constrain and enable flexibility in planning and construction. Considering the complexity of these dual urbanization patterns, in previous research, the authors proposed a required + optional item public service facility guidance-control system from a functional perspective. Adding to those contributions, this study, as part of a series, primarily focuses on the spatial dimension and is oriented toward local renewal, aiming to propose an appropriate spatial layout method with the guidance of a dynamic functional guidance-control system.

On the scientific level, this study finds that under the complex pattern of human–land urbanization in small towns, residents’ usage patterns of public service facilities do not strictly follow the principle of proximity. It further measures residents’ distance demands using distance sensitivity, establishes a coupling relationship based on three indicators—functional demand, usage frequency, and tolerance distance—and proposes a suitable life circle model framework. The study validates the clustering effect of distance sensitivity to rural and non-rural facilities among groups with different levels of urbanization, further proving the feasibility and correctness of the proposed life circle model. This provides a foundation for determining the life circles of various populations.

From the application and operational perspective, the study offers control and guidance on facility spatial layouts in residential areas with different levels of urbanization. It reveals the relative proximity of facilities for different residential areas, moving beyond the previous “one-size-fits-all” approach to facility layout. In the context of facility development and renewal in small towns, the study clarifies operational steps for improving spatial layouts. With limited resources such as funding, it specifies baseline requirements and optimization pathways to ensure that the standards are both broadly applicable and flexible. The resulting guidelines can provide theoretical support for optimizing the spatial layout of existing public service facilities in small towns across China and for improving relevant regulations on village and town development.

This study has certain limitations. As a pioneering exploration of the spatial suitability programming of public service facilities in small towns, it primarily investigates life circle layers in rural- and urban-biased residential areas, representing different levels of urbanization. Factors such as industrial structure may also influence the varied allocation of public service facilities for small towns in practice. Future research should expand upon the type of small towns to form a comprehensive and refined system for facility functions and spatial programming. Further, this exploration should continue, establishing methods that not only provide guidance from top to bottom perspectives but also provide local governments with flexible and operational approaches to facility construction. Furthermore, in facility spatial planning, site selection should not only center on the circles where the facilities are located but should also consider factors such as accessibility. Thus, the construction path for public service facilities in small towns at the spatial level continues to require exploration. When discussing how the findings of this study can extend beyond China’s borders to promote the development of other cities globally, it is essential to recognize that significant differences in political structures, levels of economic development, and social-cultural foundations exist between countries, along with the diversity in the scale and urbanization stages of small towns. Therefore, directly replicating findings from other studies for facility configuration in small towns is evidently neither reasonable nor feasible. Thus, in formulating strategies for the allocation of facilities in small towns, it is crucial first to clarify the objectives, problems, and challenges concerning public service facilities. At present, Chinese small towns often face the challenge of balancing resource coordination and public needs. This study aims to explore and reveal the underlying logic and effective pathways to achieving this balance, ensuring the maximization of social welfare under limited resource conditions. It seeks to provide “customized” public service facility development strategies for small towns, and this approach can be widely applied.