Analysis of Public Space Characteristics in Traditional Villages Along the Western Beijing Cultural Belt and Their Behavioral Adaptation to Residents: A Multi-Scale Perspective Study

Abstract

Under the accelerating urbanization, the evolution of public spaces in traditional villages increasingly diverges from social needs. The top-down governance model fails to adequately address the actual needs of indigenous residents, highlighting the necessity for structural analysis and optimization from an integrated physical–social perspective. This study, focusing on traditional villages in Beijing’s Fangshan District, constructs a three-tier model (village-street-node) by integrating Social Network Analysis (SNA) and space syntax theory. It analyzes the relationship between the accessibility and traffic potentiality of linear and point-based public spaces across the region and the frequency/scope of villagers’ daily activities. The findings reveal that within the linear belt-like spatial layout of traditional villages in western Beijing, historical spaces situated within the core residential areas demonstrate high stability and integrity, serving as primary venues for villagers’ daily activities. In contrast, historical spaces located at the periphery of settlements suffer from low utilization rates and even exhibit social segregation. Additionally, deficiencies in spatial choice, intermediary nodes, and functionality within settlements are identified as key factors contributing to social segregation in public spaces. Finally, the study proposes targeted policy recommendations for the preservation and sustainable development of traditional villages.

1. Introduction

Traditional villages are complex self-organizing systems that evolve from the bottom up through continuous interaction between human societies and their surrounding environments [1]. They preserve rich and diverse cultural heritage, embodying the dual nature of both tangible and intangible cultural assets [2]. Analyzing and articulating the localized characteristics manifested in their spatial structure not only provides a crucial foundation for understanding rural historical contexts and recognizing the material and social dimensions of rural spaces, but also serves as a key approach to advancing the protection of traditional villages in China since the release of the List of Traditional Chinese Villages in 2012—transitioning from single-village conservation to cluster-based conservation [3].

However, with the deepening of urbanization and the expansion of the tourism market, the relatively stable and self-contained socio-cultural and spatial systems of traditional villages have gradually eroded [4,5]. This has led to spatial homogenization, landscape degradation, and increasing hollowing-out trends, which in turn have intensified villagers’ loss of identity and sense of belonging [6,7]. In addition to spatial evolution, diverging needs among various stakeholders have further exposed the misalignment between spatial resource allocation and social demands. Consequently, traditional villages are finding it increasingly difficult to meet the diverse social needs of their residents, severely undermining both their livability and their path toward modernization [8]. Against this backdrop, in 2018, China’s State Council issued the *Rural Vitalization Strategy (2018–2022) [9], emphasizing the need to coordinate urban and rural territorial spatial development patterns and optimize the spatial arrangements for production, living, and ecological functions in rural areas. This has subsequently rendered the creation of intensive and efficient physical spaces, along with the optimization of rural development layouts, an urgent and critical scientific task for grassroots governance in China’s rural revitalization efforts.

As a vital component of traditional rural production, living, and ecological spaces [10], public space serves as a key site for villagers’ social life and public interactions, characterized by both cultural heritage and contemporary relevance [11,12], playing a significant role in fostering rural habitat harmony, spatial justice, and the cohesion of social relations [10,13]. However, the lingering inertia of “holistic” planning thinking from past urbanization efforts has overlooked the distinct needs between indigenous villagers—the actual builders, managers, and users of traditional villages—and urban residents [14]. Existing studies have proven that public spaces that do not meet daily needs are often left unused, resulting in significant resource waste and unsustainable long-term maintenance pressures [15]. In contrast, public spaces that align with villagers’ traditional behavioral habits, accommodate their evolving needs, and adapt to new users not only experience high utilization rates but are also voluntarily maintained by the users themselves [16,17]. Consequently, accurately revealing the morphological characteristics of traditional villages, scientifically analyzing the interactive mechanisms of their public spaces from the villagers’ perspective through a bottom-up approach, and precisely identifying inefficient and dysfunctional spaces hold significant theoretical and practical importance.

In recent years, research on rural public space has mainly emerged from disciplines such as geography, architecture, and planning. Geographic research, in particular, has focused on identifying spatial differentiation patterns and developing strategies for spatial structure optimization [18,19]. It also explores the spatial representation mechanisms of social issues, such as rural hollowing-out [20,21], and employs methods such as density analysis [22], GIS spatial analysis, and RS spatial analysis [23], integrating regional characteristics, temporal context, and socio-cultural needs to analyze the patterns and evolution mechanisms of rural public spaces [24,25,26]. This research explores the development patterns and restructuring models of different types of rural spaces, establishing a research paradigm for public space reconstruction based on four dimensions: “function, culture, space, and mechanism.” [27]. The research paradigm in architecture and planning has shown a clear shift from purely material spatial analysis toward a multidimensional “material–social–cultural” approach [28,29]. Research in this field has increasingly focused on the spatial representation of intangible cultural elements, along with strategies for their conservation and utilization. However, a systematic theoretical framework and comprehensive empirical findings are still lacking. Methodologically, geographers typically employ GIS spatial analysis and remote sensing image interpretation techniques [26,30,31], emphasizing quantitative spatial research at medium to macro scales. In contrast, architecture and related disciplines often utilize spatial geometry, fractal theory, and space syntax to investigate material attributes through spatial modularization analysis [32,33,34]. Although the aforementioned research methods have achieved significant progress within their respective fields, they are generally constrained by a unidimensional research perspective. Specifically, they tend to overemphasize the binary relationship between spatial form and either the social or natural environment, while overlooking the in-depth analysis of user’s behavioral patterns within space. In recent years, sociological research has increasingly employed social network analysis (SNA) to examine rural social structures and community relationships [35,36]. These studies not only visualize the relational structures within social networks but also integrate physical spatial configurations, offering new insights into the interaction mechanisms between social structures and spatial morphologies. Although planning and architectural disciplines have utilized SNA to address research gaps in the interrelationships between physical spaces and social demands [33,37,38], the traditional “node-line” topological model predominantly focuses on nodal spatial elements (“points”). While effective in quantifying nodal spatial characteristics, this approach fails to adequately capture the morphological features and functional attributes of linear alleyway spaces (“line” elements), which form the core components of rural public spaces [8]. This methodological limitation has impeded a comprehensive understanding of the structural essence of complex rural public space systems.

Therefore, the study integrates Social Network Analysis (SNA) and Space Syntax theory, focusing on the traditional villages in Fangshan District, Beijing. By analyzing the material spatial network and villager behavior network models of the villages through a “point-line-plane” approach, the research aims to achieve the following objectives: (1) Identify the structural characteristics of public spaces in traditional villages within the western cultural belt of Beijing. (2) Explore the interactive relationship between public spaces in traditional villages and villagers’ daily activities, identify potential factors influencing the use of rural public spaces, summarize existing issues, and assess the potential for enhancing traditional village spaces. This aims to provide scientific guidance for similar traditional villages to balance community needs, rationally allocate resources, and precisely optimize the structure of public spaces.

2. Methodology

2.1. Study Area

The study focuses on Fangshan District in Beijing as a representative case area (Figure 1). Located between latitudes 39°30′–39°55′ N and longitudes 115°25′–116°15′ E, Fangshan covers an administrative area of 2019 km² and has a resident population of 1.311 million as of 2024. Situated in the tectonic transition zone between the Taihang Mountains and the North China Plain, the district features a diverse and complex landscape, including typical landform units such as mountains, hills, and plains. As the core of the Western Beijing Cultural Belt, Fangshan preserves unique cultural remnants at the intersection of the Yanshan-Taiping Mountains corridor and the North China Plain, reflecting its significant regional cultural heritage.

According to data published by the Ministry of Housing and Urban-Rural Development of China in 2024, Fangshan District is home to five national-level traditional villages: Shuiyu Village (115°41′ E, 39°47′ N) and Nanjiao Village (115°43′ E, 39°48′ N) in Nanjiao Township, Heilongguan Village (115°45′ E, 39°55′ N) in Fozizhuang Township, Liulinshui Village (115°38′ E, 39°53′ N) in Shijiaying Township, and Baoshui Village (115°40′ E, 39°43′ N) in Puwa Township. However, due to severe damage caused by extreme precipitation events in July 2023, Liulinshui Village and Baoshui Village were excluded from this study sample.

Nanjiao Village, Shuiyu Village, and Heilongguan Village formed part of a settlement cluster in western Beijing that developed during the Qing Dynasty, relying on coal mining and trade with Mongolia. As China underwent rapid urbanization and resource transition, their original resource and locational advantages gradually diminished, leading to significant population outflow and village hollowing. Currently, the primary preservation approach for such traditional villages in western Beijing involves in situ relocation—resettling residents to newly built modern settlements on the periphery of traditional settlements to protect the original settlement fabric. Among these, Nanjiao Village is the largest and most structurally complex, with a permanent population of approximately 300 within its traditional core. In contrast, Shuiyu Village and Heilongguan Village are smaller in scale, with simpler and clearer structures, each having a permanent population between 100 and 200 people.

These three villages exhibit a southwest-northeast spatial distribution, forming the core framework for traditional village preservation in Fangshan District. They serve as excellent samples for studying the public space structures of traditional villages within the cultural belt of western Beijing.

Public Space Selection

According to previous research and policy documents from relevant Chinese authorities [39,40], the public space in this study is defined as spaces in traditional villages that are accessible to villagers for social activities, public affairs participation, and idea exchange. These spaces are found in villages with relatively intact preservation patterns and a strong sense of historical continuity, excluding the natural landscape areas on the outskirts of the villages. Through fieldwork, in-depth interviews, and behavioral observation, sample spaces were selected from three national-level traditional villages in Fangshan District. A total of 57 typical public spaces with regional characteristics and closely related to the daily production and life of villagers were selected. Drawing on previous research findings [41], public spaces are categorized into: (1) Historic type public spaces: public spaces formed around historical and cultural architectural facilities; (2) Living type public spaces: public spaces spontaneously formed or adapted through the daily activities of residents within the settlement; (3) Functional type public spaces: public spaces with a single specific function, created through village planning and construction (

Table 1. Basic attributes of public space sample points.

No	Name	Type	No	Name	Type	No	Name	Type
N1	Villagers’ activity square	functional type	N20	East entrance of the school	functional type	H13	Open space by the bridge	functional type
N2	Village committee	functional type	N21	Xuan Di Temple	historic type	H14	Dragon Temple	historic type
N3	Village entrance	living type	N22	Riverside parking lot	functional type	S1	Theater	historic type
N4	Health center	functional type	N23	East side old locusts	historic type	S2	Old locusts	historic type
N5	Fork in the village	living type	N24	A plank road	functional type	S3	Village committee	functional type
N6	Riverside Green	functional type	N25	Theater	historic type	S4	Public square	functional type
N7	Footbridge	functional type	N26	Parking lot on the south bank of the river	functional type	S5	Cross-street towers (west)	historic type
N8	Parking lot on the north bank of the river	functional type	H1	Village committee	functional type	S6	Cross-street towers (east)	historic type
N9	Theatrical platform	historic type	H2	Parking lots	functional type	S7	Footbridge	living type
N10	Cross-street towers	historic type	H3	Public square	functional type	S8	Niangniang Temple Square	historic type
N11	Niangniang temple	historic type	H4	Southside old locusts	historic type	S9	Niangniang Temple	historic type
N12	Old locust	historic type	H5	Riverside green space 1	functional type	S10	Yang family compound	historic type
N13	Entrance to the ancient street	living type	H6	Riverside Green Space 2	functional type	S11	Altar	historic type
N14	Fitness square	functional type	H7	Gallery Square	historic type	S12	Village ruins	historic type
N15	Vacant lot in front of the house	living type	H8	Northside old locusts	historic type	S13	Spring Plaza	historic type
N16	Riverside open space	living type	H9	Pavilion	historic type	S14	Senior center	functional type
N17	Open space in the village	living type	H10	Entrance Plaza	functional type	S15	Open space in the village	living type
N18	Kiosks	functional type	H11	Riverwalk	functional type	S16	Plank road	historic type
N19	West entrance of the school	functional type	H12	Parking lot by the bridge	functional type	S17	Entrance Plaza	functional type

(Note: NX denotes node X of Nanjiao Village, HX stands for node X of Heilongguan Village, and SX denotes node X of Shuiyu Village).

, Figure 2 and Figure 3).

2.2. Method Framework

This study innovatively combines SNA and spatial syntax methods to investigate the public space structure of traditional villages in the Western Beijing Cultural Belt. The overall research framework, illustrated in Figure 4, consists of four main steps: (1) Select indicators for the public space characteristics of traditional villages through a review of literature and previous studies, incorporate insights from experts and scholars, and establish a three-tiered analysis system of “village–street–node.” (2) Collect village public space data and villager preference data through satellite images, questionnaire surveys, and fieldwork, and develop the axial model of spatial syntax, along with the material spatial network and villager behavior network models using SNA. (3) Use spatial syntax and social network models to examine the material spatial characteristics of traditional villages at various levels and the behavioral characteristics of villagers. (4) Compare the results across different models, conduct an in-depth analysis of the public space characteristics of traditional villages in the Western Beijing Cultural Belt, as well as the behavioral patterns of villagers and the factors influencing them, and propose targeted recommendations for the protection and renewal of traditional village spaces, focusing on balancing social needs with physical space.

2.3. Social Network Analysis

SNA has gained widespread use in architectural planning in recent years. As a quantitative analysis method that integrates sociology, statistics, and mathematics [37], SNA views the interrelationships between subjects as a structural network made up of nodes and connecting lines. It offers a quantitative tool for measuring sociological concepts that are otherwise difficult to quantify [42,43]. In this framework, the “nodes” typically represent actors, while the “lines” signify the causal connections or interactions between them [44,45]. In this paper, using SNA, the study treats the public space nodes in traditional villages as “points” and the interrelationships between these nodes and the villagers’ daily behavior paths as “lines” within the material spatial network and the villager behavior network, respectively. A binary relationship matrix is constructed to establish both the material spatial network model and the villager behavior network model. The study selects four indicators (

Table 2. “Village–Street–Node” evaluation indicators.

Level	Indicator	Indicator Interpretation
Village	Network density	Measurement of overall network completeness
	Intelligibility	Measuring the degree to which the local is relevant to the global
Streets	Integration	Measuring the transportation potential of a space to attract arrivals
	Choice	Measuring the potential of space to attract through traffic
Nodes	Cliques	Measuring the characteristics of node distribution in a localized region
	Degree centrality	Spatial networks: measuring the accessibility of nodes Behavior networks: measuring villager use of nodes
	Key point	Measuring the importance of nodes and the stability of the network

)—network density, cliques, degree centrality, and key points—to analyze the objective material spatial patterns and the subjective usage needs of the villagers. The following section provides a description of the model formulas.

2.3.1. Network Density

Network density measures the overall completeness of the spatial network and the tightness of its connectivity. A higher network density value indicates a greater degree of connection between “points” in the network model, reflecting a more complete road network. The formula is as follows:

$$P={\displaystyle \frac{L}{\left[\frac{n\left(n-1\right)}{2}\right]}}$$

(1)

In the formula, P represents network density, L is the number of actual connections in the network, and n is the number of nodes present in the network.

2.3.2. Cliques

Cliques refer to well-connected subgraphs within a network model, where any two points within the subgraph are connected to each other, and there are no other points in the network model that are connected to all points in the sub-graph. They are used to characterize the local node distribution within the network.

In this study, the binary matrices constructed from the physical spatial network model and the villager’s behaviour network model were imported into the UCIENT6.0 software for clique classification.

2.3.3. Degree Centrality

In the material spatial network model, degree centrality measures the accessibility of spatial nodes; the higher the value, the greater the accessibility. In the villager behavior network model, degree centrality reflects the villagers’ preference for using spatial nodes; a higher value indicates more frequent use and greater preference for those nodes. The formula is as follows:

$$C\left(n_i\right)={\displaystyle \frac{d\left(n_i\right)}{n-1}}$$

(2)

In Equation, C(n_i) represents the degree centrality of point n_i, and d(n_i) denotes the degree of point n_i in a network of size ⁿ, indicating the number of points directly connected to n_i.

2.3.4. Key Point

A key point is a crucial node in a network that facilitates communication between groups. If it collapses, the entire network system will disintegrate into several independent spatial groups. Therefore, key points are used to measure the stability and vulnerability of the network system. Fewer key points indicate higher stability in the network.

2.4. Spatial Syntax

Spatial syntax is a quantitative spatial analysis technique based on spatial grouping theory and the illustration of spatial relationships [46]. It can be divided into axial analysis, convex space analysis, and visual field analysis [34,47]. Axial analysis is commonly used in research on traditional village structures to explore factors influencing spatial layout, the characteristics of public spaces, and the evolution of spatial morphology [28,48,49]. In this study, axial analysis is applied to translate traditional village street spaces into an axial model, enabling the analysis of spatial morphology and structural characteristics of the streets. This approach addresses the limitations of SNA in studying the spatial characteristics of the “line” elements. The following section provides the model formula.

2.4.1. Intelligibility

Spatial intelligibility measures the degree of correlation between the local and the overall system, reflecting how easily the network can be understood. Higher spatial intelligibility indicates stronger continuity in the spatial interfaces of the system, making the space easier to comprehend and suggesting a more cohesive overall form. The spatial intelligibility, R², is calculated as follows:

$$R^2={\displaystyle \frac{\left[\sum (I_{\left(3\right)}-I_{\left(3\right)}^{·}(I_{\left(n\right)}{I}_{\left(n\right)}^{·})\right]}{\sum {\left(I_{\left(3\right)}-I_{\left(3\right)}^{·}\right)}^2\sum {\left(I_{\left(n\right)}-I_{\left(n\right)}^{·}\right)}^2}}$$

(3)

In Equation, $I_{\left(3\right)}$ represents the global integration degree at step n = 3, while $I_{\left(3\right)}^{·}$ denotes the average value of the three-step integration degree. $I_{\left(n\right)}$ refers to the global integration degree at step n, and $I_{\left(n\right)}^{·}$ is the mean value of the global integration. The performance is classified as follows: $R^2<0.5$, indicates average intelligibility performance; $0.5\ll R^2\ll 0.7$, indicates good intelligibility performance; and $0.7<R^2$ indicates excellent intelligibility performance.

2.4.2. Integration

Integration is used to measure the accessibility of space and can be categorized into global integration and local integration. A higher integration value indicates stronger centrality, meaning greater potential for traffic and people gathering in that space. The formula is as follows:

$$I_i={\displaystyle \frac{2\left(\frac{1}{n-1}{\sum }_{i-1}^n{d}_i{N}_d-1\right)}{\mathrm{n}-2}}$$

(4)

Equation n represents the total number of axes or nodes within the spatial system; $d_i$ is the minimum number of connections from an axis to any other axis in the network; and $N_d$ denotes the number of connected axes.

2.4.3. Choice

The choice indicates the number of spatial connections between a space and other spaces and is used to measure the potential of a space to attract traffic. Higher choice values signify stronger spatial accessibility and greater frequency of use. The formula is as follows:

$$C={\displaystyle \frac{{\log }_2\left[\frac{1}{\left(n-1\right)\left(n-2\right)}{\sum }_{i=1}^n{\sum }_j^n{\sigma }_{\left(i,x,j\right)}+1\right]}{{\log }_2\left[{\sum }_{i=1}^{n}d\left(x,i\right)+3\right]}}$$

(5)

Equation C represents the choice degree of the traditional village; $i\ne x\ne j$; $d\left(x,i\right)$ is the shortest distance from space x to i; ${\sigma }_{\left(i,x,j\right)}$ denotes the shortest path between $x,i$ and $j$ spaces.

2.5. Data Sources and Processing

2.5.1. Data Sources

The data used in this paper were sourced from three main areas: First, panoramic camera recordings were collected during three successive in-depth visits to Nanjiao, Heilongguan, and Shuiyu villages between August 2023 and April 2024. These recordings documented the internal spatial patterns and villagers’ behavioral paths. Second, in April 2024, with the coordination of the village committees of Nanjiao, Heilongguan, and Shuiyu villages, questionnaires and semi-structured interviews were conducted with 47 residents from Nanjiao, 26 residents from Heilongguan, and 40 residents from Shuiyu. These interviews, combined with previously collected spatial images, were conducted during the time slots of 8:00–10:00 and 13:00–14:00 to gather information on the villagers’ living spaces, daily activity areas, and public space nodes. As a result, 26 public space nodes in Nanjiao, 14 in Heilongguan, and 17 in Shuiyu were identified. Third, high-definition satellite remote sensing images of Nanjiao, Heilongguan, Shuiyu, and Liulinshui villages from 2024 were used.

2.5.2. Spatial Syntactic Axial Model

The study used CAD software to convert high-definition images of Nanjiao, Heilongguan, Liulinshui, and Shuiyu villages, collected via Google Earth, into spatial blocks, dividing the street organization within the settlements. The spatial structure was then represented with axes, transforming the settlement’s spatial organization into an axial map. Finally, the axial model was imported into the Depthmap platform for quantitative analysis of the morphology and characteristics of the built environment within the settlement.

2.5.3. Material Spatial Network Model

Combining field investigations with high-definition images of Nanjiao, Heilongguan, and Shuiyu villages collected via Google Earth, the study treats the existing 54 public space nodes as “points.” If a direct path exists between two points without detours or indirect connections through other points, a “line” is defined and assigned a value of “1”; otherwise, it is assigned a value of “0.” Given the unique characteristics of rural areas, which differ from urban settings, the semantic “point-line” model is modified. For this study, based on the small scale of the target villages, the walking distance for a “line” is adjusted from the standard 5-min walking distance (600 m) to a range more suitable for villagers walking patterns (70–120 m) [50]. A 1-min walking distance (120 m) serves as the basis for determining whether an interrelationship exists between points [8]. This establishes the binary relationship matrix, which is imported into the UCINET 6.0 platform, and the results are analyzed in NETDRAW software to construct the material spatial network model.

2.5.4. Villager Behavior Network Model

The study collects data on villagers’ daily behavioral paths and primary activity spaces through questionnaires, semi-structured interviews, and on-site observations. It defines spatial nodes where villagers frequently engage in daily activities as “points,” while direct movement paths between these “points” are defined as “lines.” If a “point” is merely passed through without stopping, no “line” is formed with the preceding or following nodes. If villagers are within a comfortable walking range (120 m) [50], the path between two points is assigned a value of “1”; otherwise, it is assigned a value of “0.” The resulting binary value matrix is imported into the UCINET 6.0 software for network structure calculations, and the results are then analyzed in NETDRAW software to construct the villager behavior network model.

3. Results

3.1. Characterization of Public Space at the Village Level

The dichotomous matrix was imported into UCINET software to calculate the network density of both the material spatial network and the villager behavior network for each village. The results revealed that the material spatial network densities for Nanjiao Village, Heilongguan Village, and Shuiyu Village were 0.1076, 0.1758, and 0.1471, respectively, indicating a low level of connectivity. This suggests that the public spatial structure in these villages is loosely organized, with insufficient connections between the nodes. Additionally, the behavior network density was lower than the spatial network density, with decreases of 28.5%, 31.2%, and 30% in Nanjiao Village, Heilongguan Village, and Shuiyu Village, respectively. This indicates that public space nodes are not being fully utilized by the villagers, leading to social segregation in all three villages. Nanjiao Village exhibited the smallest decrease, suggesting the highest utilization rate of public space nodes among the three traditional villages, while Heilongguan Village had the lowest utilization rate.

As illustrated in

Table 3. Results of the analysis of village area indicators.

Indicator	Nanjiao Village	Hilongguan Village	Shuiyu Village
Material spatial network density	0.1076	0.1758	0.1471
Villager behavior network density	0.0769	0.1209	0.1029
Intelligibility	0.44661	0.62026	0.287157

, the spatial intelligibility R² of Nanjiao Village is 0.44661, of Heilongguan Village is 0.62026, and of Shuiyu Village is 0.287157. These values indicate that the continuity of the spatial interfaces of the streets and alleys in Heilongguan Village is stronger, while the continuity of the spatial interfaces in Nanjiao and Shuiyu Villages is less satisfactory.

3.2. Characterization of Public Space at the Street Level

In the global integration map (Figure 5), all three villages exhibit distinct major and minor axes. Nanjiao Village and Heilongguan Village have well-connected streets and alleys, with highly accessible areas centrally distributed along the major and minor axes in a fishbone-like pattern, creating a belt-shaped spatial structure. In contrast, Shuiyu Village’s street network is more staggered, featuring sparse and short branch alleys. The main axis of Shuiyu Village does not exhibit the high integration characteristics seen in the other villages but instead shows significant centralization in localized areas.

By setting the axial topological radius (n) to 3, the axial map of the local integration degree is derived, reflecting the settlement’s ability to gather people (Figure 5). Heilongguan Village exhibits a simple spatial structure, where the global and local integration degrees align closely. In Nanjiao Village and Shuiyu Village, the local integration degree bears a notable similarity to the global integration degree. Specifically, in the southwestern part of Nanguo Village, the area around the Temple of the Goddess and the theatre (N9, N10, N24, N25, and N26), the area around the Cross-street towers and the old locust tree on the west side of Shuiyu Village (S2 and S5), and the area around the old locust tree and the gallery square in Heilongguan Village (H4 and H7), the local integration degree is significantly higher. This indicates that these spaces have a strong ability to concentrate pedestrian flow.

The choice graph (Figure 5) reveals that the main streets of Nanjiao Village and Heilongguan Village, as well as the street areas with high integration in Shuiyu Village, have significantly higher choice values. This includes the spatial connections of nodes related to key areas such as the villagers’ activity center, the village committee, and the fork in the village (N1, N2, and N5) in Nanjiao Village; the old locusts on the south side, the gallery square, and the old locusts on the north side (H4, H7, and H8) in Heilongguan Village; and the theater, public square, and cross-street towers on the east side (S1, S4, and S6) in Shuiyu Village. These prominent nodes reflect the strong connectivity between these spaces and their surrounding environments.

3.3. Characterization of Public Space at the Nodal Level

As seen from the results of the degree centrality calculations (Figure 6), most of the spatial nodes with high point degree centrality in the material spatial network and villager behavior network of the three traditional villages are coupled. The nodes with the highest degree of centrality are the theatrical platform in Nanjiao Village (N9), the old locust tree on the south side of Heilongguan Village (H4), the old locust tree in Shuiyu Village, and the Yang Family Compound (S2, S10), all of which are historical nodes. This indicates that historical nodes not only play a crucial role in the spatial structure of traditional villages in the Western Beijing Cultural Belt but also exhibit significant social attraction. Meanwhile, the point degree centrality of individual nodes in the material space (e.g., points N6, N13, N16, N17, N24, H6, H11, H13, L8, L15, L16, L17, S12, S13, S15, S16) is 0%, indicating social isolation within the villager behavior network. This reflects a misalignment between the material spatial network and the needs of the villagers in traditional villages in the Western Beijing Cultural Belt.

At least three spatial nodes are used as the division criteria for cliques, with strong spatial connections between nodes within cliques and weak cohesion among regional spatial nodes that do not form cliques. The division results are illustrated in Figure 7. The material spatial network of Nanjiao Village contains seven groups of cliques, five of which are distributed in the North Street area, while two are in the theatrical platform area (Figure 8). Compared with the material spatial network, the number of cliques in the North Street area has decreased, while the total number of cliques in the theatrical platform (N9) area remains unchanged. Both the material spatial networks of Heilongguan Village and Shuiyu Village contain three groups of cliques, with a decrease of one group in their respective behavioral network cliques. The distribution of both material and behavior network cliques shows that nodes in the main transportation areas are more likely to form cliques; however, the stability of these cliques in actual villagers’ social activities is weak. In contrast, spatial cliques formed in historical and cultural areas exhibit stronger stability in social activities. This suggests that villagers’ activities in the traditional villages of the Western Beijing region are more inclined towards historical and cultural spaces.

Further observation of the key points revealed that the proportion of material spatial network cut points in Nanjiao Village, Heilongguan Village, and Shuiyu Village were 50%, 57.1%, and 47%, respectively, while the rate of villager behavior network cut points were 52.3%, 63.6%, and 53.8%, respectively (Figure 6). This indicates a low degree of connectivity between the ancient street space and the surrounding street and alley spatial nodes, with a single path for internal behaviors. The internal spatial nodes tend to serve as the only and essential routes for villagers’ movements. For example, if a node in S7–S8 or S2–S3 on the main street of Heilongguan Village becomes congested or abandoned, the public space at both ends of the main street will be divided into two parts.

4. Discussion

4.1. Characteristics of Public Spaces in Traditional Villages in Western Beijing and Their Interaction with Villagers’ Spatial Behavior

A comprehensive comparison of the results from spatial syntax and SNA (Figure 9) reveals that the distribution of spatial nodes overlaps, with street spaces exhibiting high values of integration and choice. The settlement form is influenced by the natural landscape, with development centered around historical and cultural landmarks such as the Niangniang Temple, the theater, and the cross-street towers. Additionally, the village structure follows a belt-shaped, herringbone pattern, extending along the river or valley.

Further observation of the spatial nodes and the spatial conditions of their respective streets and alleys reveals that although the ancient streets of Nanjiao Village and the main streets of Heilongguan Village and Shuiyu Village possess favorable integration and choice, the internal spatial nodes fail to form effective connections. For example, no effective connection has been established between S5 and S6 in Heilongguan Village or between N15 and N21 in Nanjiao Village. This contradiction runs counter to their superior spatial potential. A 2024 spatial study on Nanjiao Village has shown that this issue stems from an insufficient number and uneven distribution of spatial nodes, resulting in excessive distances between them. Consequently, the service radius of these nodes is limited, leading to incomplete coverage of the ancient and main street spaces and an inability to form a fully integrated network [8].

It is worth noting that Shuiyu Village exhibits distinct characteristics in terms of global integration compared to the other two villages, with its main axis area showing no signs of high integration. This is due to the later construction of the main street intersecting with the ancient street, thereby weakening the spatial continuity of the ancient street. In contrast, the main streets and national highways constructed later in Nan Jiao Village and Hei Long Guan Village did not interfere with the texture of the ancient streets, thereby causing Shuiyu Village’s ancient street to lose its original spatial dominance within the settlement. This spatial impact caused by the later construction of the village is also reflected in the node network.

For example, under the influence of urbanization and tourism-driven development in traditional villages, the traditional architecture and courtyards in the historical settlements of the Jingxi region have undergone large-scale economic development during renovation and restoration processes. Newly constructed enclosed accommodations, restaurants, and courtyards have encroached upon the original street spaces, altering their morphological structure to varying degrees [41]. This has caused the connecting interfaces between areas such as N17 and S15 and other public spaces to become narrow, winding, and even interrupted, rendering them no longer able to draw the attention of users [51].

On the other hand, settlements contain spatial nodes such as N13 and S6, which exhibit high street and network accessibility yet still experience social isolation. This phenomenon diverges from the assumption proposed by Fang Q. and Meng S., who asserted that accessibility has the greatest impact on the quality of public spaces in traditional villages and more easily attracts villager activities [41,52]. This indicates that while the accessibility of spatial nodes is important, it is not the decisive factor in villagers’ daily choices of social spaces. This aligns with the conclusion drawn by Zhang C. and Shi Y. who noted that villagers in traditional settlements prioritize the social and functional attributes carried by spaces when selecting social spaces [53,54].

In previous research, Meng S’s quantitative study on the spatial elements of public spaces in traditional villages in western Beijing using machine learning revealed that spaces with the highest quality and strongest appeal and sense of identity for villagers were primarily concentrated near historical and cultural relics such as the Niangniang Temple, cross-street towers, and ancient trees [41]. Chen Y’s earlier study on the public spaces of Nanjiao Village also emphasized the dominant role of historical and cultural spaces in the public spaces of traditional villages in western Beijing [8]. However, in this study, the Dragon Temple (H14) in Heilongguan Village and the Spring Plaza (S13) in Shuiyu Village did not exhibit the expected clustering features in the physical spatial layout or villagers’ activities within the settlements. Instead, they displayed signs of social isolation, which contradicts previous conclusions. Analysis of the village layouts of Heilongguan and Shuiyu reveals that in increasingly hollowed-out traditional villages, houses within the settlements are gradually becoming abandoned, leading to a contraction in the actual inhabited area and the scope of villagers’ activities. As a result, historical and cultural spaces that once served as regional spatial nodes have gradually become marginalized within the settlements. Even though such nodes possess unique conditions to attract people, their excessive distance from the main settlement areas prevents them from fully realizing their spatial and cultural potential, leading to social isolation. Within the main settlements, areas of historical and cultural significance, such as the Niangniang Temple, the old locusts, and cross-street towers, continue to play a central role in the physical spatial structure of traditional villages in Beijing’s western cultural belt. These areas remain the most frequented venues for villagers’ daily activities.

4.2. Practical Implications

Based on the evaluation results from the case study area, this study proposes specific spatial planning and management strategies applicable to the Beijing Western Cultural Belt and other similar regions facing severe challenges in the protection and renewal of traditional villages.

At the village scale, the findings reveal that Nanjiao Village and Shuiyu Village exhibit weak street continuity. This aligns with the actual situation, as their street spaces have been impacted by government-led development and self-built activities by villagers during urbanization and tourism development. This has led to insufficient connections between public space nodes and low utilization rates, resulting from compressed, fragmented, and disconnected street spaces. In contrast, Heilongguan Village, which demonstrates the strongest spatial continuity, suffers from severe hollowing out and shrinkage of settlement space, leading to low utilization of public areas. Therefore, it is essential to delineate cultural preservation zones and daily living zones based on each village’s historical evolution, resource conditions, spatial potential of public spaces, and villagers’ activity preferences. This approach balances heritage conservation with development, ensuring targeted and practical spatial planning and resource allocation to meet the growing material and cultural needs of villagers.

At the street and alley scale, the results indicate that traditional villages face a misalignment between the potential of public spaces and social demands due to reduced spatial choice caused by tourism-oriented development. Thus, leveraging the historical fabric and resource distribution of the villages, it is necessary to further standardize spatial conservation regulations in a top-down manner. Within cultural preservation zones, measures such as clearing and reclaiming spaces should be implemented to restore the spatial fabric. In daily living zones, villager-led governance models, such as the “street chief system,” should be introduced to foster villagers’ sense of ownership in maintaining the street environment. Additionally, establishing clear guided tour routes within cultural preservation zones can enhance the continuity and directional flow of spatial interfaces in traditional villages, effectively connecting various spatial nodes. This will strengthen the cohesion between core nodes and surrounding areas, improving connectivity and ultimately forming more vibrant and attractive thematic node clusters.

At the node scale, the findings show that while accessibility determines the capacity of public spaces to attract crowds, it is not the decisive factor for villagers’ social activities. Attributes such as functionality, culture, and history are crucial in determining the usability of nodes. Therefore, landscape design elements that reflect the unique character of the region can be integrated to enrich node functions—providing spaces for rest, recreation, cultural exchange, and social interaction—while enhancing comfort and appeal. To address uneven node distribution and low utilization, movable modular design installations can be introduced to strengthen the use of small-scale, daily public spaces, such as street corners, alleys, and areas around houses.

4.3. Limitations

Although this paper couples SNA and spatial syntax to study the public space structure from the perspective of the indigenous people, focusing on the interaction between street space, public space nodes, and villagers’ social activities, both methods are limited by their topological representation of space, ignoring its morphological characteristics and the influence of spatial elements such as terrain, altitude, and enclosure degree. This prevents the identification of specific factors affecting the use of public spaces. Additionally, field data collection, street mapping information, and historical planning data. The modeling of material space is also affected by the accuracy of satellite imagery, particularly when addressing internally encroached street spaces, leading to errors in material space modeling. Additionally, the quantitative research and analysis of motivational factors remain insufficient. In addition, since most of the resident villagers interviewed were middle-aged and elderly individuals over 50 years old, the study could not fully capture the daily behavioral trajectories of villagers across all age groups. This limitation affected the comprehensive study of the interaction between material spatial and behavioral networks. Future research should expand the scope and precision of the study population, reduce model errors by integrating historical images, planning data, and aerial images captured by drones, and better understand the needs and expectations of various groups, such as villagers and tourists, regarding traditional village spaces. This can be achieved by combining big data and participatory mapping. The goal is to provide a precise optimization of historical heritage spaces for multiple space users and establish a feedback mechanism for the configuration of spatial resources, promoting efficient allocation. Ultimately, this approach will support green planning, green construction, and sustainable development in traditional villages while enhancing their spatial resilience.

5. Conclusions

To address the issue of mismatch between spatial resource allocation and social needs during the evolution of traditional villages, this study takes traditional villages in Fangshan District, Beijing, as its research subject. By combining axis analysis from spatial syntax with social network analysis (SNA), this study visually presents and systematically compares the physical spatial characteristics of three villages with the social spatial preferences of their indigenous residents. From the perspective of local residents, it reveals the interactive mechanisms between public space nodes and their surrounding neighbourhood networks, providing valuable insights for the precise optimisation and sustainable development of traditional villages. Key findings include:

(1) In the traditional villages of the Beijing Western Cultural Belt region, public spaces are primarily characterized by historic public spaces such as the Niangniang Temple, opera stages, and ancient locusts serving as cores. The main streets typically follow linear, belt-like distributions along valleys or mountain slopes, with branch alleys extending outward in a fishbone-like pattern. This understanding will assist local governments in clarifying settlement textures and identifying core conservation zones during the renewal process of traditional villages in western Beijing.

(2) Research validation demonstrates that while historic public spaces within settlements function as focal points for both the physical space and daily activities in traditional villages, those affected by village spatial contraction and located on the periphery suffer from low utilization rates among villagers and even exhibit social isolation. This finding will help governments develop more targeted classification-based optimization and conservation policies during traditional village preservation efforts.

(3) The study indicates that within public spaces located inside traditional villages, deficiencies in alleyway space choice, intermediary nodes within the nodal network, and the functional capacity of the nodes themselves are also key factors contributing to social isolation in public spaces. This insight will assist governments in addressing the most prominent issues and shortcomings of public spaces.

Furthermore, the study integrates space syntax with social network analysis to reveal the spatial-social relationships in traditional villages of Beijing’s Fangshan District, thereby constructing a dual-dimensional analytical framework of “space-society” that can be applied across cultures and regions. This provides empirical cases for international research on traditional villages. The study not only highlights the universal phenomenon that historical public spaces may trigger social isolation in the context of village shrinkage but also emphasizes the critical role of node connectivity, the cultivation of intermediate functional nodes, and the quality improvement of small-scale spaces in public space governance. These findings offer valuable insights for the renewal of traditional villages in East Asia and globally that face similar challenges such as population decline, aging, and spatial decay. They particularly provide theoretical foundations and practical pathways for developing countries to balance spatial preservation and social integration in rural sustainable development.