Town-village Spatial Restructuring in Developed Regions of China from the Perspective of Resident Travel: A Case of Lin'an District, Hangzhou

Town-village Spatial Restructuring in Developed Regions of China from the Perspective of Resident Travel: A Case of Lin'an District, Hangzhou | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Town-village Spatial Restructuring in Developed Regions of China from the Perspective of Resident Travel: A Case of Lin'an District, Hangzhou Lin Tian, Yao Cheng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5733130/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Jun, 2025 Read the published version in Humanities and Social Sciences Communications → Version 1 posted 9 You are reading this latest preprint version Abstract The organization of town-village space in developed regionsof China is undergoing profound restructuring, which has resulted in fundamental changes in the daily travel patterns of rural residents. However, current studies often focus on the static space itself, neglecting the dynamic interactions and functional shifts driven by the “users” of space. This study fills the gap by analyzing residents’ inter-village commuting and non-commuting travel links using mobile phone signaling data, combined with field research and questionnaire surveys. The findings reveal that the town-village spatial structure exhibits a combination of hierarchical and network patterns. First, the traditional “central place” model remains dominant, with central town centers forming radial connections to surrounding villages. However, localized networked structures have emerged, characterized by horizontal links between villages. Second, both commuting and non-commuting travel links have extended spatially, forming self-balanced clusters with strong internal connections that do not strictly follow administrative boundaries. The linkages between rural and urban areas have also strengthened, following a logarithmic distance decay trend. Finally, the study highlights that technological advancements, industrial upgrading and diversification, and policy interventions are the main drivers of spatial restructuring. The findings provide valuable insights for town-village spatial planning and policy-making, emphasizing the need to consider actual functional relationships and resident behavior. It is important for rural areas in China and beyond in the context of rural transition. Humanities/Complex networks Social science/Geography Social science/Science technology and society town-village spatial structure spatial networks resident travel links mobile phone signaling data Rural China Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction Towns and villages in China's developed regions have undergone profound spatial structural changes over the past decades (Zhang et al., 2022). It shows a faster pace and unique features under the national system, which has attracted the world’s attention (Chai et al., 2007, Long and Liu, 2016). From the 1980s to the 1990s, township enterprises[1] have successively sprung up in China's eastern coastal areas, which has greatly promoted the industrialization of towns and villages from the bottom up. A typical example is the so-called “Zhejiang Model” (“浙江模式”) - originating from Zhejiang Province, China, it is a regional growth pattern driven by the private economy and grassroots entrepreneurship through market-oriented reforms (Zhao, 2009). With the growth of foreign trade and the implementation of the coastal opening policy, these township enterprises are increasingly integrated into the regional division of labor. Since the new century, the strengthening of the link to the global production system and intensive spillovers from metropolises to the surrounding areas has led to industrial specialization and spatial separation in rural areas, promoting the flows such as labor, capital, logistics, and information in a larger range (Woods, 2007, Yang et al., 2016). In addition, benefiting from the natural resources of the countryside and the huge urban demand for leisure and culture, rural tourism has developed rapidly, with pioneering regions starting as early as the 1990s. It further drives the shift in rural space use from production to consumption (Wu et al., 2024). With these macro trends, the functions of towns and villages have been transformed from a single agricultural form to a agriculture-industry-service integration model, which has further drove the rural space to become diversified, interactive, and dynamic, distinct from the traditional, homogeneous, and isolated form (Tian et al., 2014, Yang et al., 2016, Wu et al., 2024). The urban-rural relationship has also gradually changed from unilateral connection to bilateral interaction with complementary functions (Zhang et al., 2022, Qian et al., 2025). Under such a transforming context, the town-village spatial structure and the mechanisms behind it need to be re-recognized. From a micro perspective, these changes result in a fundamental transformation of residents’ working and living modes in town and village areas. It is because the economic, social, traffic, and other functional flows between regions foster people’s travel or movements, while in turn, they promote the reconstruction of the rural spatial structure (Woods, 2012, Chai et al., 2016). Moreover, due to the improvement of transportation and the increase in car ownership, rural residents now have greater accessibility and initiative to travel across villages, towns, and even cities, mainly stimulated by higher wages, public services, and consumer demand. Regarding the policy context in China, 2017 witnessed a shift in emphasis towards the countryside when the Rural Revitalization Strategy[2] was put forward by the central leadership, with a series of strategies covering spatial configuration, industrial development, land management, human settlements, governance systems, etc., to support it (Liu et al., 2020). Local rural planning has become more multifunctional, targeted, and implemented, from the focus on single land use and facility allocation to people-centered ideology (Liu et al., 2020). Examples include the plan of the “beautiful rural cluster” in Guangzhou (Tang et al., 2024), the “rural functional unit” in Wuhan (Xiong, 2021), the “rural group” in Wuxi (Yuan and Wang, 2021), and the “urban-rural integrated development units” in Chengdu (Chen et al., 2020). They are similar in the idea that villages and towns can be merged into clusters and classified according to the 3 dimensions of “industry-residence-services” to achieve spatial control, resource sharing, industrial collaboration, and construction management. It helps reshape the rural spatial configuration and further promotes the free flow and rational allocation of urban and rural resources (Chen et al., 2020, Li et al., 2023). Therefore, residents’ activities, especially cross-regional travel, are considered to be an important reflection of spatial structure and are widely used to reveal spatial patterns (Niu and Li, 2022, Gao et al., 2023). However, previous studies on rural space often focus solely on the physical space itself or rigid town-village hierarchical systems, ignoring their openness, connections, and dynamics under the functional shift. One of the main reasons is that the spatial relation or connection is difficult to measure, especially in rural areas where data is limited. On the other hand, the in-depth mechanisms of space evolution in research using big data are still vague due to the lack of qualitative analysis. Thus, this study proposes a novel approach that combines mobile phone signaling data to map spatial linkages and field research to uncover the mechanisms of the phenomenon, and tests it in an empirical case context. The remainder of this paper is organized as follows: Section 2 is the literature review, elaborating on the spatial cognition evolution, the study of town-village space from the behavioral perspective, and the transformation of rural planning in China. Section 3 introduces the study area, data sources, and methodology. In section 4, town-village spatial structure is quantitatively measured using commuting and non-commuting travel links identified by mobile phone signaling data, including the characteristics of the network structures, clusters, and rural-urban links. In section 5, we explore the drivers of town-village spatial restructuring and the mechanisms through questionnaire data analysis and qualitative field research. Based on the research results, section 6 discusses how the town-village spatial restructuring connects to Western theories and the implications for the town-village spatial planning. [1] Township enterprises refer to collective, cooperative or individual enterprises established in the rural area. [2] The national “Rural Revitalization Strategy” aims at achieving five broad goals before 2050: economic vitality, ecological liveability, civilized rural communities, effective governance, and prosperous livelihoods. It broadens the definition of rural areas to encompass both towns and villages, advocating that towns play a leading role in village development, while villages contribute to the growth of towns. 2 Literature review 2.1 Spatial restructuring: cognitive shift towards hybrid relations With the deepening of the regional division of labor from the mid-20th century (Krugman, 1991), the understanding of space has evolved from an initial static, undifferentiated entity to a dynamic, interconnected, and hybrid construct rooted in the continuous (re-)shaping of relationships. Ullman (1957) suggests that no region can exist and develop in isolation, but through the material exchange and mutual collaboration between regions can obtain a win-win situation. The central place theory proposes the spatial relationships that central places with different orders provide goods and services for their corresponding rural hinterland, though the relationships between central places and regions beyond the hinterland were not established (Christaller and Baskin, 1966). Friedmann's (1966) work on core-periphery dynamics further highlights the evolving spatial interactions within regional systems. Harvey (1973) introduces a social production idea that space is shaped by the relationships it contains, which vary across scales and are constantly in a process of reshaping. Under the “time-space compression” brought about by globalization and advanced communication technologies, Castells's (1996) “space of flows” concept marked a more significant shift, emphasizing the dominance of relational networks (the “space of flows”) over geographical proximity (the “space of places”). This paradigm change has been supported by subsequent empirical studies on city networks (Alderson and Beckfield, 2004, Derudder and Witlox, 2009, Taylor et al., 2013), which highlight the importance of various flows - traffic, economic, information, and population - in shaping spatial networks. The above changes also influence the realm of rural studies, as the countryside has gradually become open and has been reconstructed with the diverse material exchanges with the outside world (Woods, 2007, Fink et al., 2013, Yang et al., 2016). The relational perspective views rural space as a multi-authored, multi-faceted, and co-constituted space, shaped through local-global interconnections and their place-specific manifestations (Heley and Jones, 2012). It advocates for a relational rural epistemology that recognizes the co-constitutive production of rural space through material and discursive phenomena, processes, and practices, highlighting the theoretical pluralism in comprehending new rural space in its multidimensional complexity (Heley and Jones, 2012, Qian et al., 2025). Similarly, the “global countryside” illustrates that the full picture of rural space can only be seen through a hybrid and networked approach at the interregional level, rather than through a single site or urban-centric approach (Woods, 2007, Woods, 2009). With the rural transition began in the Global North before progressing to the Global South (Wu et al., 2024), the rural space in China is also increasingly understood as a dynamic and multifaceted phenomenon that transcends static, predefined socio-economic and cultural attributes, and is constantly being redefined and reimagined through its socio-spatial interactions with the urban (Qian et al., 2025). However, Hoggar and Paniagua (2001) criticize the indiscriminate use of the term “rural restructuring,” which has become a catch-all phrase in academic discourse. To more accurately determine whether and to what extent rural restructuring has genuinely occurred, they propose viewing restructuring as an “approach” rather than a pre-set “fact”, and this approach necessitates a holistic and thorough examination of various dimensions, encompassing economic diversification, social stratification, cultural evolution, and spatial reorganization (Hoggar and Paniagua, 2001, Long and Liu, 2016). Collectively, rural spatial restructuring is a complex process manifested through the interplay of multiple dimensions such as infrastructure networks, production and lifestyle changes, the mobility and heterogeneity of socio-spatial relations, and the dynamic nature of space itself (Long and Liu, 2016), which challenge traditional understandings of rurality (Qian et al., 2025). Yet the restructuring concept often lacks precision and theoretical depth, or the support of empirical evidence. Therefore, an up-to-date spatial interpretation framework for rural space should be established with the hybrid connections between spaces and the logic of functional organization behind them. 2.2 Rural spatial analysis from the behavior perspective Building on the cognitive shift discussed in Section 2.1, the understanding of rural space has long been enriched by examining the dynamic activity space composed of residents’ daily behavioral activities (Chai et al., 2016). These activities, with their diverse functions, continuously (re-)shape the rural space (Wang et al., 2021). This perspective traces back to the emergence of behavioral geography and spatiotemporal geography in the 1960s and 1970s under the Western humanist trend, which emphasized the spatial and temporal manifestations of human behavior, highlighting individual agency and the relationship between activities (especially travel or movement) and space (Hägerstraand, 1970, Massey, 1999). Studies in this area cover daily space-time patterns of residential, commuting, consumption, recreation, social visits, and public service access, in which great regularity is found (Ahas et al., 2010, Gao et al., 2023). Some research explores spatial organization through diverse travel behaviors (Asakura and Iryo, 2007, Verhetsel et al., 2018) or identifies different zones based on activity patterns (Fu and Wang, 2021). These studies highlight the functional connectivity patterns revealed by different types of travel links, reveal the rapid transformation of urban lifestyles, as well as people’s decision-making mechanisms in undergoing socio-economic transition. In rural contexts, research often examines the living and production spaces formed by residents’ daily activities in various natural and cultural settings (Guo et al., 2020). Studies in China often aim to inform planning, focusing on identifying patterns, evolution, and drivers of change under considerations of human-land relationships (Wang et al., 2021). The impact of globalization, urbanization, and informatization on rural living space has also garnered increasing attention (Zhang et al., 2022, Wang et al., 2023). However, traditional data collection methods, such as activity diaries, questionnaires, interviews, and censuses, often fail to capture the complexity of activity space in the face of rural population diversification and spatial heterogeneity (Gao et al., 2023). The advent of mobile phone signaling big data has significantly enhanced spatial-temporal granularity, overcoming limitations of low spatial accuracy, small sample size, and poor timeliness, offering advantages in investigating rural spatial structure (Liu et al., 2020, Gao et al., 2023), especially given the widespread mobile phone ownership among rural residents. While mobile phone signaling data has been widely used in urban research since 2010, its application in rural areas remains limited. Notable studies include Eagle et al. (2009), who compared behavioral dynamics in rural and urban societies using mobile phone data, finding that rural and urban communities differ dramatically in terms of personal network topologies and behavioral characteristics such as travel. Using the same data, Liu et al. (2020) analyzed rural residents’ daily activity patterns by frequency, diversity, and the spatial range of activities. Through movement links measured by mobile phone signaling data, Zhao and Xu (2019) identified complex network characteristics and cluster-form spatial connections in a town of Zhongshan City, China. Niu and Li (2022) also used this data to measure inter-town commuting and non-commuting travel linkages in the Shanghai suburb and identified clusters within, from which they proposed to optimize the town circles’ spatial configuration in a networked manner. The above explorations demonstrate the feasibility and potential of mobile phone signaling data in rural spatial analysis. 3 Study area and methods 3.1 Study area Lin’an District is located in the outer suburbs of Hangzhou metropolis, Zhejiang Province, eastern China (Figure 1). It includes 18 town- (street-) level administrative units, covering an area of 3126.8 km 2 . It had 635 thousand permanent residents in 2020, including 258 thousand rural residents. Since 2017, Lin’an’s administrative level has been upgraded from county level to city level, meaning it officially joined the Hangzhou city district. Due to the location of the developed areas and the solid historical industrial foundation, Lin’an’s rural economy is relatively prosperous. The per capita disposable income of rural residents is higher than the average value of the eastern region and far higher than that of the central, western, and northeast regions in China. Under the guidance of the “Two Mountains Theory” (“两山理念”)[3], Lin’an’s development mode is in the process of a shift from extensive expansion to more emphasis on green development and quality improvement. Thus, Lin’an’s new economy, especially the e-economy and eco-tourism, has developed vigorously in the past 10 years. Moreover, promoted by the rich local governments, the construction of settlements, public service facilities, and infrastructure in rural Lin’an is also at a high level, forming a new model of “beautiful towns and villages”. In summary, rural Lin’an has been transforming from self-organized development relying on natural resources to spatial reconstruction under the influence of external forces such as urbanization, industrialization, informatization, and radiation of the metropolis. Whilst, it also retains rurality in geography, society, and industry. Therefore, with a diverse urban-rural-dual nature, the Lin’an rural area makes a typical case for our study. Towns and villages in China are regarded as closely interconnected and indivisible systems that are often studied as a whole. The town-village area studied in this paper covers 13 towns or 298 administrative villages in Lin’an District. Among them, Yuqian Town and Changhua Town are the two central towns (“中心镇”) with comprehensive functions, assuming the central and western sub-centers of Lin’an, respectively. The Lin’an city area (the 5 street-level administrative units) located in the east is the main center, which is depart from the town-village area. Under a town-level administrative division, there are two levels of administrative villages (“行政村”) - town center village(s) (“镇区”) and other general villages. 3.2 Methods and data 3.2.1 Data source and link identification In this study, we use mobile phone signaling data to identify two kinds of resident travel links - commuting links and non-commuting links. The former refers to travel from home to the workplace. The latter involves travel from home to a variety of public services, mainly including out-of-class education, medical care, shopping, and recreation. The mobile phone signaling data was obtained from China Mobile[4] for 30 consecutive days in April 2017, including 20 working days and 10 rest days. The data fields include user ID, time, and base station code. The total number of communication base stations within the study area is 2126, with an average spatial coverage of 1.47 km2 each, covering 90.1% of the villages. 25 villages with no base stations distributed were excluded from the follow-up calculation. In the 30 days, when a user stayed for the longest time and at least greater than 2 hours from 19:00 to 8:00 the next day, and this routine had the largest number of repeated days and at least 60% of the total days, then the location of this base station was taken as the user's home. The location identified in the same way from 9:00 to 18:00 during the daytime was regarded as the user’s workplace. When a user traveled from home and then stayed within the range of a destination base station for more than 30 minutes, and this base station was neither the home nor workplace base station, then this base station was defined as a non-commuting destination. We considered a link between the user's home and workplace as a commuting link, and a link between home and the non-commuting destination as a non-commuting link. A total of 79,500 commuting links and 1,159,500 non-commuting links were identified within the study area. 3.2.2 Travel networks building and analysis To depict the spatial distribution of resident travel, we built commuting and non-commuting networks by drawing on the complex network analysis approach (Niu and Li, 2022, Gao et al., 2023). Specifically, the geometric center points of villages served as network nodes, the linking lines among them as edges, and the sum of two-way travel links as the weight of the edges. The one-way movement trajectories from Village A to Village B, and from Village B to Village A, were summed into a single two-way link between Village A and Village B. Only inter-village links were retained, and intra-village travel links were excluded. Moreover, the links between villages and urban areas (Lin’an City and Hangzhou Central City) were summed up in the same way. To quantify the hierarchical characteristics of inter-village travel links, we defined an indicator - “proportion of top town center links (PTCL)” - for each village, i.e., the proportion of links between a village and the maximum-link town center to the total amount of external links to the village. For a village, the larger the PTCL, the more dominant the village's linkage with the top town center, and vice versa, for a more evenly split linkage with neighboring villages. For all the villages studied, the more villages with high PTCL, the more centralized and hierarchical the whole linkage structure is, and vice versa, the more decentralized and flatter it is. All linkage values here refer to two-way linkages. The formula is as follows: 3.2.3 Network cluster identification We employed the Louvain method, a community-detecting algorithm proposed by Blondel et al. (2008), to detect clusters in the networks. The algorithm goes through several iterations, trying to add individual nodes to the communities (clusters) that can maximize modularity until no node change in the network can improve the modularity[5], and the algorithm automatically stops. As the iteration proceeds, smaller clusters are gradually merged. We substituted the commuting network and the non-commuting network into the algorithm. Both the two networks eventually went through three iterations and demonstrated 12 and 10 clusters, respectively. The final modularity reached 0.77 and 0.67, respectively. The modularity is high, meaning that the intra-cluster links are very tight and the inter-cluster links are relatively weak. 3.2.4 Field research and questionnaire distribution After big data mapping, we further dig into the drivers of town-village spatial restructuring and the mechanisms behind them. Firstly, we selected 4 representative towns in the Lin’an district: Yuqian, Changhua, Tianmushan, and Taihuyuan. Next, 6-8 villages in each town, including town-center villages and general villages at varying distances from them (32 villages in total), were selected for in-depth field research. We visited the town governments, village committees, typical rural households, and some enterprises to investigate details of local industries, town and village construction, and residents' daily lives. Meanwhile, a questionnaire was distributed to a random sample in these villages from 12 July to 20 July 2021. Questionnaires were distributed to rural residents face-to-face by members of the investigation team, with about 20 questionnaires in each town-center village, and 6-10 questionnaires in each general village. The questionnaire mainly included questions on the respondents’ basic personal and family information, employment, and frequency of travel for various purposes. A total of 307 questionnaires were collected, with 299 valid ones. The valid questionnaire rate was 97%. In addition, another questionnaire was distributed to city residents of Hangzhou via Wenjuanxing - a Chinese professional questionnaire online platform - between 27 July and 31 July 2021. This questionnaire mainly contained aspects such as respondents' basic information, and frequency and purpose of traveling to the countryside. A total of 210 questionnaires were collected. After excluding the samples of respondents living outside Hangzhou urban areas, 164 questionnaires were considered valid. The questionnaire validity rate was 78%. [3] As a guide to action for national ecological civilization, the “Two Mountains Theory” holds that lucid waters and lush mountains are invaluable assets, revealing the dialectical unity between economic development and ecological protection. [4] As the No. 1 of China's three major mobile phone service providers, China Mobile has a 52.54% market share in 2020, which can fulfill the sample size requirement for our data sampling. Considering user privacy issues, the users’ information is hidden in the original dataset. [5] The Louvain method is a modularity optimization-based algorithm that iteratively assigns nodes to different communities to maximize the modularity value of the network. Modularity is a measure of the strength of division of a network into communities, reflecting the density of connections within communities compared to connections between communities. A higher modularity value indicates stronger internal connections within communities and weaker connections between different communities, suggesting a more distinct and well-separated community structure in the network. 4 Characteristics of the town-village spatial structure 4.1 The hierarchical form dominates, while the network pattern appears From the commuting and non-commuting networks of the Lin’an town-village area (Figure 2), their patterns both primarily show a hierarchical “central place” form, where the centers of each town form radial connections with the surrounding villages. Among them, the linkage patterns of the two central towns - Yuqian and Changhua - are more central. And they are linked to a larger range of areas beyond their township boundaries. Whereas, a networking trend has simultaneously emerged. Some villages have formed closer horizontal links with each other, especially in the areas adjacent to Lin’an City, where relatively dense and flat networks formed. In other words, residents travel to and from villages of the same level to a great extent, not just between general villages and town centers. this finding suggests a mismatch to the traditional “central place” model of town-village spatial structure. The results in Figure 3 show that in commuting and non-commuting networks, villages with PTCL greater than 0.3 accounted for 40.0% and 8.3%, respectively; while villages with PTCL less than 0.1 accounted for 31.6% and 60.4%, respectively. It indicates that although there are still some villages that form major links with a single town center, some have built evenly matched links with other town centers or villages. Therefore, the dominance of the town center, with which they have major links, is not clearly shown. Specifically, commuting links are more confined within the township, similar to the “central place” system within each township. In contrast, non-commuting links are more extensive, more dispersed, and less hierarchical. It is worth noting that for a village, the top-linked town center is not necessarily in the town to which it belongs, i.e., a village may exceed its township to form its major link with other town centers (mainly the two central towns). This is the case for 16% and 74% of the commuting and non-commuting networks, respectively. This result is somewhat contrary to the conventional notion of the hierarchical town-village system in China, also deviating from the assumptions of the central place theory, which we will elaborate on in the discussion section. 4.2 Links extend on a large scale while forming clusters at the local level 4.2.1 Analysis of travel distances In the Lin’an town-village area, the average non-commuting travel distance[6] is longer than that of commuting (see Table 1): when all links are calculated, the average commuting distance is 1322m, while the average non-commuting distance is 1397m - slightly higher than the former. When only inter-village links are considered, the average non-commuting distance (2045m) is significantly higher than the average commuting distance (1625m). This result indicates a higher proportion of long distances in non-commuting travel, though this may be influenced by the different identification algorithms of the two types of trajectories. Next, we do the horizontal urban-rural comparison. Firstly, the second section in Table 1 shows that the average distance for both types of travel in Lin’an City is lower than that in the Lin’an town-village area. One possible reason for this is that the Lin’an City itself is small in size so long-distance travel is mainly linked to the Hangzhou central city. Secondly, the average commuting distance in the Hangzhou central city is considerably higher than that in the Lin’an town-village areas, regardless of whether the calculation includes intra-village links. Only for the inter-village non-commuting average distance, the former is lower than the latter. This is possible because the distribution density of various public service facilities in the rural area is lower than that in the city, making it unavoidable to travel longer distances to access the services. As the work-residence relationship is considered an important aspect in judging the spatial structure configuration, we take the commuting distance as a key indicator. From Table 2, the daily commuting distances of rural residents are mostly short, i.e., links of less than 3 km account for the majority. It is worth noting that longer-distance commuters are also beginning to appear and have become non-negligible in number. When all links are calculated, the proportion of commuting links longer than 3 km is as high as 33.2%, those larger than 5 km are 17.9%, and those larger than 10 km still make up 4.8%. A total of 11.2% are inter-town links. Whilst among inter-village links, the proportions of all the above long-distance links are even higher. Tab. 1 Average commuting and non-commuting travel distances in different regions Town-village area of Lin’an Lin’an City Hangzhou Central City All links, including intra-village links Inter-village links only All links, including intra-village (community) links Inter-village (community) links only All links, including intra-village (community) links Inter-village (community) links only Commuting 1322 m 1625 m 1313 m 1581 m 2483 m 2787 m Non-commuting 1397 m 2045 m 414 m 462 m 1417 m 1516 m Tab.2 Percentage of commuting links of different distances in the Lin’an town-village area >3km >5km >7km >10km Cross-town All links 33.2% 17.9% 10.2% 4.8% 11.2% Inter-village links only 41.7% 22.7% 13.1% 6.1% 14.3% 4.2.2 Analysis of network clusters Clusters in our study can be interpreted as network substructures formed by the self-organized people flow, representing rural functional zones promoted by the demand of residents. The commuting clusters are indicators of the work-residence balance situation, while the non-commuting clusters illustrate the pattern of linkages between homes and rural public services and consumption places. Corresponding to the structure of the linkage networks in Figure 1, each cluster often contains a core (usually the town centers) and a hinterland that are closely interconnected. Figure 4 shows that the clusters identified from the commuting and non-commuting networks differ in spatial pattern. There are 12 smaller and more equitable-in-size clusters identified from the commuting network. Each cluster has a balanced work-residence relationship within it, with shorter commuting distances. By comparison, the non-commuting network forms 10 clusters with greater variation in size. Among them, the boundaries of the two clusters with Yuchen and Changhua towns as the cores, respectively, noticeably extend beyond the town boundaries and include the surrounding villages of other towns. While the rest of the clusters are smaller. Interestingly, the clusters of both commuting and non-commuting networks do not completely match town administrative boundaries. A few clusters, especially the two central clusters, break through their town boundaries and extend outward, while some split into two clusters within a township. This finding indicates that the administrative factor plays an inconclusive role in separating the cluster organization of resident travel in rural areas. Instead, it may be influenced by a variety of other factors. Additionally, the modularity of the commuting network (0.77) is higher than that of the non-commuting network (0.67), indicating that the former has a more distinct feature of clustering. 4.3 Linkages to the city strengthen, following the distance decay law From the analysis above, the daily travel ranges of rural residents have extended far beyond a walkable range, so it is necessary to analyze the links between rural and urban areas. Figure 5 illustrates the results of the regression analysis on the two indicators: 1) the distance between each village and the city, and 2) PLC. It is found that the farther the distance between a village and Lin’an City, the lower the percentage of its commuting and non-commuting links with Lin’an City is, indicating that the geographical proximity of residents’ travel has not been surpassed to a large extent. In other words, rural residents living close to the city rely more on the city for access to jobs and higher-level public services, thus having greater cross-border mobility. Whereas villages farther away from the city mainly form a stable work-residence and services-residence balance with neighboring towns and villages. Furthermore, this distance decay is not linear but approximates a logarithmic function curve. It means that when the distance increases to a certain degree, the regression curve gradually flattens out, so the travel proportion to Lin’an City does not decrease much with the distance increase. The goodness of fit of commuting links is better than that of non-commuting links, with the R square of 0.60 and 0.56, respectively. It indicates that the commuting decay trend is more obvious, while the latter is more insensitive to geographic distance, probably due to the greater occasionality in service and leisure travel. However, for the regression analysis of the villages to the Hangzhou Central City, no such decay pattern is shown. It is presumably because when the travel distance exceeds a certain threshold, the travel is very low in frequency, depending more on the random personal demand without a daily pattern. We further calculated the proportion of the scale of the rural-urban link. Of residents living in the Lin’an town-village area and having a stable workplace outside of the same village, 8.6% of them have their workplace in Lin’an city. For the non-commuting links, 16.7% of rural residents have travel destinations in Lin’an City and 2.8% in Hangzhou Central City. Moreover, the scale of the urban-to-rural links is also considerable: the number of commuters living in Lin’an City and employed in the town-village area is about twice that in the opposite direction. The number of non-commuting travelers from Lin’an City to the town-village area is about 40% higher than that in the opposite direction; the number of non-commuting travelers from Hangzhou Central City to the Lin’an town-village area is nearly four times that in the opposite direction. It is shown that with the overall improvement of urban and rural economy, the urban-rural dualism is gradually broken, and regular daily travels across urban and rural areas have been formed. [6] The (non-)commuting distance here refers to the Euclidean distance between the two base station points. Considering that the base station layout makes it difficult to identify short-distance travel within 1 km, the actual average distance may be shorter as links within the same base station radiation range are discarded. 5 Drivers of town-village spatial restructuring Multiple exogenous and endogenous factors are driving the changes in the town-village area revealed above, including natural resources, economic, social, policy, and transportation. This section summarizes major drivers from the spatial relational perspective into three aspects: transportation and information technology improvement, industrial reconstruction, and the changes in physical space resulting from policies. 5.1 Time-space compression caused by technology development Limited by the backward productivity level and traffic conditions, previous villages were often centered on settlements, with the farming distance determining the village range. Therefore, the traditional rural landscape in China featured homogeneous, independent, and was greatly affected by natural factors such as mountains and rivers. Nowadays, however, the significant improvement of transportation infrastructure and communication technology has greatly weakened the geographic frame of village and town development (Yang et al., 2016), which is described as “time-space compression”, triggering the reconstruction of town-village landscapes and the formation of town-village networks. Firstly, the improvement of rural transportation has provided residents with long-distance accessibility, which has significantly expanded the scale of live-work-service cells. By 2016, the motorized rate of rural roads in Lin’an reached 100%, and the public transport accessibility of natural villages (the lowest division level under the administrative village) in the region reached 99%. Since 2020, an east-west expressway has been constructed crossing Lin’an District and a subway line connecting to Hangzhou Central City. The private car ownership rate of rural residents has also been greatly improved. According to our questionnaire data, over 70% of the rural families in Lin’an own their cars and can easily travel between towns and villages, even to Lin’an City and Hangzhou Central City. However, it is worth noting the shortage and long intervals of rural public transport, and some natural villages still do not have public transport stations. This results in inequity of accessibility for the elderly, juvenile, low-income earners, and other vulnerable groups without cars or driving capability. Secondly, informatization has indirectly influenced spatial restructuring by changing the way of production, consumption, and social interaction of rural residents. The first point to mention is rural production in the network era. Towns and villages have greater chances to explore their talented resources and comparative advantages, therefore easily participating in the regional division of labor and creating more rural employment (Wu et al., 2021, Wang et al., 2023). Typical cases are “ Taobao village” and “internet-famous village”[7] emerging in recent years. Some towns and villages play the leadership role and reorganize their surrounding areas. For example, Bainiu Town in Lin’an has become a base of e-entrepreneurship incubation, e-commerce training, and sightseeing. To support Bainiu, the nearby Daoshi Town serves as the main production base, Longgang Town and Qingliangfeng Town are the main processing and logistics bases, and Changhua Town is the exhibition and tourism center. Thanks to online shopping platforms and logistics networks, these town group’s products are sold nationwide. Another point is about rural life. Online shopping has partly replaced the commercial functions of town centers and urban areas. Our questionnaire shows that the rural residents in Lin’an, especially young and middle-aged groups, have already become accustomed to online shopping. In addition, the prevalence of online chatting has not only expanded the social network but also transferred kinship and geographical ties in rural areas. In addition, Figure 6 illustrates that travel for “visiting relatives and friends” is still frequent among the Lin’an rural residents. Hangzhou urban residents with family members who live or work in towns and villages have a higher travel frequency between urban and rural areas (see Figure 7). It is suggested that though the urban-rural gap is sewn by modern technologies, the traditional rural social relations have not disintegrated, but to some extent, been strengthened. 5.2 Upgrading and diversification of industry structure Since the 1980s and 1990s, substantial bottom-up industrialization in rural Lin’an has promoted the transformation of industry structure and formed local industrial clusters. It is not a rare case in the developed regions of China (Zhang et al., 2022). The original single agricultural production has evolved into a comprehensive industrial structure integrating agricultural production, agricultural product processing, cultural tourism, e-commerce, scientific research, etc. For example, originated from bamboo planting, the bamboo shoot industry in Taihuyuan Town has developed into an industrial cluster including bamboo seeding research and breeding, bamboo shoot gardening technology research and promotion, bamboo science popularization, ecological teaching, and rural technicist training. The pecan industry in the west of Lin’an has also extended from original planting and processing to e-commerce platform sales, leisure agriculture, and cultural tourism. The reconstruction of the industry has changed local labor markets and the connectivity between work and residence, which in turn have also reshaped the rural spatial structure. The advancement of the new economy, especially the e-commerce, has been proven to intensify the expansion and integration of rural land use and the spatial network connections between towns and villages (Wang et al., 2023). In our study, on the one hand, different from urban areas, the locality and informality of town and village industries determine that the distance between Lin’an rural residents’ occupation and residence is mainly short. From our questionnaire data, about 95% of rural employees live nearby. Among them, about 26.8% work part-time in enterprises near their home, and meanwhile operate small shops, farmhouse restaurants, homestays, online shops, or cultivate their own farmland. But on the other hand, some long-distance commuters, even across urban and rural areas, have already appeared. Specifically, people living in rural areas find their jobs in city enterprises, institutions, or governments, commuting in the “pendulum” mode, which used to be characterized as the urban commuting pattern. 5.3 Concentration of built-up space driven by policies First of all, this spatial concentration is manifested in industrial land use. Like most rural areas in the Chinese developed region along the southeast coast, with the advantages of a loose policy environment, cheap land rent, and low labor prices, Lin’an has been industrialized for decades. The early rise of the private economy in towns and villages has led to the point-like sprawl of industrial land. However, in recent years, guided by top-down policies encouraging industry agglomeration, township industries have begun to relocate to industrial parks mainly neighboring town centers, especially in central towns. A similar concentration trend is seen in the spatial layout of public service facilities. The allocation of public service facilities in rural Lin’an traditionally follows the hierarchical model, so as to match the settlement layout. However, a myriad of policies in recent years have contributed to the rapid and large-scale implementation of the merging of townships and the relocation and combination of rural settlements. From 2001 to 2011, the number of townships in Lin’an was reduced from 39 to 13, and the number of administrative villages was reduced from more than 600 to around 200. A typical example of a response to it is that most of the village-level kindergartens and primary schools have been or will be revoked. The two central towns, Yuqian and Changhua, own public service facilities of larger scales and better quality in rural Lin’an, equipped with senior middle schools, junior middle schools, district-level hospitals, hub bus stations, large shopping malls, and entertainment facilities. They attract more people from surrounding towns and villages with medical, shopping, entertainment, and travel needs. In contrast, other general towns mostly own only town governments and farmers' markets. Thus, their importance in the service or even the overall centrality has been greatly weakened. The above changes in physical space have led to a concentration of daily flows towards the two central towns. The results are presented in the mobile phone signaling data mapping in Section 4.1. The central place form is dominant viewed from the regional level, within which the hierarchical transformations and structural distortions occur. As the industrial parks, residential communities, and commercial centers of the two central towns are more clearly zoned, the intra-core network densification is also significant. [7] A Taobao Village is an administrative village where a significant number of local residents operate e-commerce businesses on the Taobao platform, with at least 10% of households engaged in online sales or an annual e-commerce transaction volume of over RMB 10 million. An “internet-famous village” or “ Wanghong village” is a village that has leveraged its unique natural landscapes, cultural heritage, or innovative development models to attract a large number of visitors through social media platforms, thereby becoming a popular tourist destination. 6 Discussion The spatial restructuring of the town-village area is not a singular transformation of land functions but also involves changes in spatial functional relationships, which are closely related to the work and life of rural residents. From agricultural civilization to industrial civilization and then to the informatization era, the towns and villages in the developed regions have experienced earlier and more drastic spatial changes in China, challenging and extending traditional central place theory. There are two points to discuss in this section. The first point addresses the trend of networked restructuring in modern rural spaces. In Christaller’s central place model, central places of different orders provide commercial, administrative, and transportation functions of different levels, while the hinterlands or “complementary regions” are in the position of receiving services (Christaller and Baskin, 1966). Aligning with this hypothetical framework, the long-standing town and village planning in China has built a hierarchical system of “central town - general town - central village - general village”. Most of the previous studies on China’s town-village system and village layout planning also follow this logic, but limited by its strict assumptions, static nature, and lack of consideration for natural-human interactions, it struggles to fully explain the observed spatial patterns in modern rural areas (Wang and He, 2014, Cao et al., 2020). Thus, a mixture of hierarchical and networked spatial structures in rural Lin’an calls for a more dynamic and linkage-oriented approach to understanding spatial organization, which should not be limited to hierarchical patterns, not only in scale but in function. This is especially true for the developed regions, where the flow of factors is more frequent and hybrid (Zhang et al., 2022). The spatial restructuring of Lin’an originated from a reform of rural residents’ production and living approaches. Therefore, there is no unitary spatial model, such as the central place or the spatial network, that can precisely and comprehensively depict its town-village spatial organizations. Moreover, the strong interconnected clusters suggest that spatial interactions are not solely dictated by hierarchical relationships but are also influenced by functional interdependencies and social networks. This is consistent with the shift towards a more macro and networked view of spatial organization, as noted by Castells (1996) and Woods (2007). The expansion of residents’ daily reach found in our study is also in line with the observations by Harvey (1973) that technological progress leads to “time-space compression,” reducing the constraints of geographical distance. It highlights the need to incorporate technological factors into spatial analysis and policymaking. Spatial planning should focus on the cluster characteristics in networks - integrate towns and villages by the three major functions of living, production, and services into functional clusters. The second point concerns the human-centered perspective and the value of human flow in re-depicting the rural spatial structure. The functional connection is reflected in human mobility. The logic of this lies in that various internal and external factors drive people’s movements. In turn, people and various flow elements such as capital, labor, information, and social relations they “carry,” reshaping spatial structures. Our study shows that residents’ travel links, both commuting and non-commuting, extend beyond traditional hierarchical boundaries, forming self-balanced clusters with strong internal connections. This highlights the importance of human behavior and mobility in shaping spatial structures. The relationship between people and land in rural areas has long been the core issue studied. However, top-down town and village planning in China is often oriented to arranging land functions and town-village hierarchies, with insufficient consideration for the actual land “users” and the fundamental changes in spatial relationships. Entering into the people-centered New Urbanization process, meeting people’s needs is the premise of spatial configuration. How people “use” space rather than the space (land) itself is what calls for the most attention. In the case of Lin’an, most rural residents transferred their working and living ways while continuing to live in their rural houses. Accordingly, the towns and villages areas did reshape to accommodate their new demands, which were mainly observed in the central towns, county-level cities and even beyond. For some residents who still kept traditional rural farming life, the policies and rural planning guaranteed basic facilities and infrastructure to ensure their daily work and living. By prioritizing people’s daily needs, planners can better accommodate the lived experiences and requirements of the population, leading to more effective and sustainable spatial planning outcomes. In summary, Lin’an is a glimpse of the towns and villages that are economically developed, highly accessible, and working-living modernized in China. The rural area landscape becomes complex and cannot be summarized as restructured or not restructured. This study has made some advancement, perhaps on at least one side, in understanding the interplay between human activities and changes in the rural spatial organization. The technical approach promoted can better accommodate this hybridity and dynamism and help promote sustainable spatial development. 7 Conclusion This study investigates the spatial restructuring of town-village areas in developed regions of China, using the Lin’an District of Hangzhou as a case. By analyzing residents' travel links derived from mobile phone signaling data and combining them with questionnaire surveys and field research, we draw the following conclusions. 1) The spatial structure of the town-village area exhibits a combination of hierarchical and network patterns. While the “central place” model still dominates, with central town centers forming radial connections to surrounding villages, some localized networked structures have emerged, characterized by horizontal links between villages. This indicates a partial deconstruction of the traditional hierarchical model, as villages are increasingly connected to multiple centers and other villages rather than being solely dependent on a single town center. 2) Both commuting (home-work) and non-commuting (home-service) travel links have extended spatially, forming self-balanced clusters with strong internal links. These clusters do not strictly follow administrative boundaries, suggesting that functional connections play a more significant role in shaping rural spatial structure than administrative divisions. The commuting network forms 12 smaller and more equitable-sized clusters, while the non-commuting network forms 10 clusters with greater variation in size, indicating different patterns of work-residence balance and service access. 3) The linkages between rural and urban areas have strengthened, following the law of distance decay. Rural residents living closer to urban areas rely more on cities for jobs and higher-level services, forming regular daily travel patterns across urban-rural boundaries. However, this relationship is not linear, with a logarithmic decay trend observed for commuting links, indicating that the influence of distance diminishes as it increases. The proportion of rural-urban commuting and non-commuting links is significant, highlighting the increasing urban-rural integration. 4) The drivers of town-village spatial restructuring are multifaceted. “Time-space compression” led by technological advancements has enabled residents to travel longer distances and establish remote communication, weakening the constraints of natural conditions and making networked connections possible. Industrial restructuring and diversification have transformed local labor markets, creating new employment opportunities and changing work-residence relationships. Policy interventions aimed at concentrating built-up space, such as relocating industries to parks and consolidating public service facilities, have directly influenced residents’ travel patterns. This study makes several contributions to the understanding of town-village spatial restructuring in the context of socio-economic transformation. Firstly, it provides a novel methodological approach by utilizing mobile phone signaling data to quantify and map resident travel links, revealing the underlying spatial networks and clusters. This method offers a more detailed and dynamic view of spatial structure compared to traditional approaches. Secondly, the combination of quantitative data analysis with qualitative field research and questionnaire surveys allows for a comprehensive exploration of the drivers and mechanisms behind spatial changes. This integrated approach provides a deeper understanding of the complex interactions between human activities and spatial organization. Lastly, the findings offer valuable insights for town-village spatial planning and policy-making, highlighting the need to consider actual functional relationships and resident behavior in addition to physical land use arrangements. However, this study has some limitations. One crucial concern is that the mobile phone signaling data cannot fully capture the complex travel patterns of rural residents in China. These patterns, influenced by multiple, part-time, and informal employment, and tied to household roles, lack fixed or regular space-time commuting characteristics - men typically engage in agricultural or industrial work, while women manage household tasks and service-oriented activities. The current data cannot fully capture the underlying purposes of these travel patterns. Additionally, the questionnaire data has a relatively small number of responses and limited geographic scope, which may affect the representativeness and generalizability of causal mining. Future research could focus on validating and refining the methods with data of larger coverage and more cases to assess their applicability and robustness. The development of models that incorporate the diverse factors influencing spatial restructuring would also be beneficial. The dynamic nature of space suggests that continuous monitoring and adaptive planning approaches will be essential for achieving balanced and sustainable urban-rural development in China and beyond under the transformation context. Declarations Data availability The data that has been used is confidential. Acknowledgements No funding to declare. The authors would like to express special thanks to Xinyi Niu of Tongji University for data support. Many thanks would also like to give to the members who participated in the survey of Lin'an Towns and Villages for their hard work, and the four town governments of Yuqian, Changhua, Tianmushan, and Taihuyuan who provided great assistance for our survey. Author contributions Conceptualization, LT and YC; methodology, LT; software, LT; visualization, LT; formal analysis, LT; investigation, LT and YC; resources, YC; data curation, YC; writing—original draft preparation, LT and YC; writing—review and editing, LT and YC; supervision, YC; project administration, YC. Competing interests The authors declare no competing interests. Ethical approval All procedures performed in this study adhered to the ethical standards outlined in the Declaration of Helsinki and its subsequent amendments. Ethical approval was granted on July 1, 2021, by the Institution Review Board of Department of Urban Planning, College of Architecture and Urban Planning, Tongji University. All research activities complied with applicable guidelines and regulations for studies involving human participants. The approved project was titled “Survey on Travelling Activities of Town and Village Residents in Lin’an District and Urban Residents in Hangzhou City.” The review documents included the Ethics Review Approval Form and Investigator’s Manual. Informed consent During the first questionnaire survey conducted from 12 July to 20 July, 2021, trained survey assistants distributed written informed consent forms to all respondents, which were signed by each participant on a voluntary basis. During the second online questionnaire survey conducted from 27 July to 31 July, 2021, the questionnaire was set up to inform participants of the research purpose, and that “submitting answers” was considered informed consent. The two surveys did not involve vulnerable groups or minors. All participants were assured that their anonymity and confidentiality would be strictly protected, and all data would be used solely for academic research purposes. All participants were fully informed about the research objectives, procedures, data usage, potential risks, and their rights. Participants could exit at any time during the questionnaire-filling process. References Ahas R, Aasa A, Silm S, Tiru M (2010) Daily rhythms of suburban commuters’ movements in the Tallinn metropolitan area: Case study with mobile positioning data. Transportation Research Part C: Emerging Technologies 18(1): 45-54 Alderson A, Beckfield J (2004) Power and Position in the World City System. American Journal of Sociology 109: 811-851 Asakura Y, Iryo T (2007) Analysis of tourist behaviour based on the tracking data collected using a mobile communication instrument. Transportation Research Part A: Policy and Practice 41(7): 684-690 Blondel V D, Guillaume J-L, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008(10) Cao Y, Li G, Cao Y, Wang J, Fang X, Zhou L, Liu Y (2020) Distinct types of restructuring scenarios for rural settlements in a heterogeneous rural landscape: Application of a clustering approach and ecological niche modeling. Habitat International 104 Castells M (1996) The rise of the network society. Blackwell Publishers, Malden Chai Y, Ta N, Ma J (2016) The socio-spatial dimension of behavior analysis: Frontiers and progress in Chinese behavioral geography. Journal of Geographical Sciences 26(8): 1243-1260 Chai Y, Zhou S, Cai Y, Zhang Y, Wu L, Weng G (2007) Recent Progress of Human Geography in China: Retrospect and Prospect. Japanese Journal of Human Geography 59: 2-22 Chen J, Gao M, Fu Y, Ruan C (2020) Research on the New Development Path of Towns and Villages Based on the Concept of Urban-Rural Integration: Taking Chengdu Urban-Rural Integration Unit as an Example. City Planning Review 44(8): 120-128 Christaller W, Baskin C W (1966) Central places in southern Germany. Prentice-Hall, Englewood Cliffs, N.J., Derudder B, Witlox F (2009) The impact of progressive liberalization on the spatiality of airline networks: a measurement framework based on the assessment of hierarchical differentiation. Journal of Transport Geography 17(4): 276-284 Eagle N, de Montjoye Y-A, Bettencourt L M A (2009). Community Computing: Comparisons between Rural and Urban Societies Using Mobile Phone Data. 2009 International Conference on Computational Science and Engineering : 144-150 Fink M, Lang R, Harms R (2013) Local responses to global technological change — Contrasting restructuring practices in two rural communities in Austria. Technological Forecasting and Social Change 80(2): 243-252 Friedmann J (1966) Regional development policy. M.I.T. Press, Cambridge Fu Y, Wang D (2021) Living space structural pattern of typical residential areas in Shanghai. Progress in Geography 40(4): 565-579 Gao X, Liu L, Ou D, Yuwu H (2023) Using mobile phone data to probe the mobility‐related well‐being of rural residents: A case study of Chengdu, China. Regional Science Policy & Practice 15(9): 1893-1907 Guo X, Yu B, Zhuo R, Zeng J, Yan M (2020) Change of farming households' employment and influencing factors on the Jianghan Plain. Progress in Geography 39(12): 2094-2104 Hägerstraand T (1970) What About People in Regional Science? Papers in Regional Science 24(1): 7-24 Harvey D (1973) Social Justice and the City. Edward Arnold, London Heley J, Jones L (2012) Relational rurals: Some thoughts on relating things and theory in rural studies. Journal of Rural Studies 28(3): 208-217 Hoggar K, Paniagua A (2001) What rural restructuring? Journal of Rural Studies 17(1): 41-62 Krugman P (1991) Increasing Returns and Economic Geography. Journal of Political Economy 99(3): 483-499 Li H, Lai W, Xiao W, Gao L (2023) Practical Directions, Theoretical Logic, and Methodology of Rural Contiguous Planning: An Analysis in the "Function-Network" Perspective. Urban Planning Forum(3): 47-55 Liu L, Gao X, Zhuang J, Wu W, Yang B, Cheng W, Xiao P, Yao X, Deng O (2020) Evaluating the lifestyle impact of China’s rural housing land consolidation with locational big data: A study of Chengdu. Land Use Policy 96: 1-9 Liu Y, Zang Y, Yang Y (2020) China’s rural revitalization and development: Theory, technology and management. Journal of Geographical Sciences 30(12): 1923-1942 Long H, Liu Y (2016) Rural restructuring in China. Journal of Rural Studies 47: 387-391 Massey D (1999) Space‐Time, 'Science' and the Relationship between Physical Geography and Human Geography. Transactions of the Institute of British Geographers 24(3): 261-276 Niu X, Li Z (2022) Spatial Organization of Shanghai Suburb Town Circles Based on the Characteristics of Resident Activities. Shanghai Urban Planning Review(1): 80-86 Qian J, He S, Smith D (2025) Rural-urban interfaces and changing forms of relational and planetary rurality. Journal of Rural Studies 116 Tang S, Wang F, Ye H, Lu X (2024) Rural Clustering Development Strategies Based on Symbiosis Theory, Guangzhou. Planners(4): 55-63 Taylor P, Derudder B, Hoyler M, Ni P, Witlox F (2013) City-Dyad Analyses of China’s Integration into the World City Network. Urban Studies 51(5): 868-882 Tian G, Qiao Z, Gao X (2014) Rural settlement land dynamic modes and policy implications in Beijing metropolitan region, China. Habitat International 44: 237-246 Ullman E L (1957) American Commodity Flow. University of Washington Press, Seattle Verhetsel A, Beckers J, De Meyere M (2018) Assessing Daily Urban Systems: A Heterogeneous Commuting Network Approach. Networks and Spatial Economics 18(3): 633-656 Wang C, Zhou T, Ren M (2023) Driving spatial network connections in rural settlements_The role of e-commerce. Applied Geography 159 Wang D, Xie D, Wang C, Yin Z (2021) Regularity and predictability of individual spatiotemporal behavior: A case study of residents working day activities in Shanghai. Progress in Geography 40(03): 433-440 Wang D, Xie D, Wang C, Yin Z (2021) Regularity and predictability of individual spatiotemporal behavior: A case study of residents working day activities in Shanghai. Progress in Geography 40(3): 433-440 Wang J, He S (2014) From Tree Structure to Interactive Network: A Preliminary Study on Transit-Oriented Spatial Development Patterns of Village-Town Communities. China City Planning Review 23(4): 41-47 Woods M (2007) Engaging the global countryside: globalization, hybridity and the reconstitution of rural place. Progress in Human Geography 31(4): 485-507 Woods M (2009) Rural geography: blurring boundaries and making connections. Progress in Human Geography 33(6): 849-858 Woods M (2012) New directions in rural studies? Journal of Rural Studies 28(1): 1-4 Wu J, Luo Z, Qian J (2021) Research on the Driving Mechanism of Human Urbanization in the Internet Age: Based on the Empirical Evidence of the Individual Life Course of the Taobao Village Elite. Shanghai Urban Planning Review(02): 1-7 Wu M, Zhang Q F, Donaldson J (2024) Post-productivism and rural revitalization in China: Drivers and outcomes. Journal of Rural Studies 110 Xiong W (2021) Rural Functional Unit Planning of Non-concentrated Construction Area, Wuhan. Planners(3): 78-84 Yang R, Xu Q, Long H (2016) Spatial distribution characteristics and optimized reconstruction analysis of China’s rural settlements during the process of rapid urbanization. Journal of Rural Studies 47: 413-424 Yuan X, Wang X (2021) Exploration of the Development Path of Rural Groups in the Early-Developing Regions: A Case Study of Rural Group around Nanqing Lake. Modern Urban Research(12): 6-11 Zhang R, Li H, Yuan Y (2022) Analyzing space-time evolution of rural transition in a rapidly urbanizing region: A case study of Suzhou, China. Journal of Geographical Sciences 32(7): 1343-1356 Zhao M, Xu Y (2019) Exploring the Spatial Network of Rural and Urban Settlements through the Lens of Mobile Phone Signaling Data: A Case Study of Sanxiang Town in Zhongshan. Shanghai Urban Planning Review(6): 38-45 Zhao W (2009) Zhejiang Pattern: A Multifold Transitional Way of the Chinese Regional Economies. Zhejiang Social Sciences(2): 22-31 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Jun, 2025 Read the published version in Humanities and Social Sciences Communications → Version 1 posted Editorial decision: Revision requested 13 May, 2025 Editor assigned by journal 13 May, 2025 Reviews received at journal 27 Apr, 2025 Reviewers agreed at journal 27 Apr, 2025 Reviews received at journal 27 Apr, 2025 Reviewers agreed at journal 27 Apr, 2025 Reviewers invited by journal 26 Apr, 2025 Submission checks completed at journal 14 Apr, 2025 First submitted to journal 04 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5733130","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":448568624,"identity":"6edf0024-1b1b-4679-9916-fdf6879446be","order_by":0,"name":"Lin Tian","email":"","orcid":"","institution":"Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Tian","suffix":""},{"id":448568625,"identity":"94bea5cb-1dcf-42e0-81f9-c240178feb12","order_by":1,"name":"Yao Cheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYDACCSjNDyZ5QNwEIrVItpGsxeAYXIiAFv7Zzccefm2zkzO+D2R8kbFg4GfPMWD4uQOPJXeOpRvLtiUbmx1jSzeWATpMsueNAWPvGdxaDCRyzKQl25gTtx3jMZOWAGoxuJFjwMzYhk9L/jeglvrEzW1QLfaEteSwSX5sO5y4gY3HTPIDyBYJAlokbqSZSTOcO24scSwtTRoYyDwSZ54VHOzFo4V/RvIzyR9l1XL8zYePSf7sqZPjb0/e+OAnHi0gwMzLBmP0MPCAGAfwa2BgYPzxB8b4QUjtKBgFo2AUjEQAAL7yR1GdlntZAAAAAElFTkSuQmCC","orcid":"","institution":"Tongji University","correspondingAuthor":true,"prefix":"","firstName":"Yao","middleName":"","lastName":"Cheng","suffix":""}],"badges":[],"createdAt":"2024-12-30 06:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5733130/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5733130/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1057/s41599-025-05136-9","type":"published","date":"2025-06-16T15:57:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82048369,"identity":"f10e21d4-fd4d-4ed1-9b5d-6059eae3b676","added_by":"auto","created_at":"2025-05-06 09:46:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2822712,"visible":true,"origin":"","legend":"\u003cp\u003eThe study area\u003c/p\u003e\n\u003cp\u003e(Based on 2017 administrative divisions)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/7874dd0ce4e75f6c5459c1f9.png"},{"id":82045699,"identity":"f93f5650-c970-44f1-a270-1e2d92175d37","added_by":"auto","created_at":"2025-05-06 09:38:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2643069,"visible":true,"origin":"","legend":"\u003cp\u003eCommuting and non-commuting networks based on resident travel links\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/db431cc7073a08ef68c4a135.png"},{"id":82044485,"identity":"3149a6d4-2e5d-4da1-9534-dd38f4aea269","added_by":"auto","created_at":"2025-05-06 09:30:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":994530,"visible":true,"origin":"","legend":"\u003cp\u003eNumerical distribution of PTCL of the commuting and non-commuting network (in descending order according to the PTCL of each village)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/d81e51b0a9a8ccd8a01435ef.png"},{"id":82044492,"identity":"0fd53d2d-fc07-4dc4-9b43-fe536e936b66","added_by":"auto","created_at":"2025-05-06 09:30:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2941721,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of clusters after the third iteration of the commuting and non-commuting network\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/84b78aca98d769734d9edc04.png"},{"id":82045701,"identity":"5b08c162-3c90-4b0a-afae-b1fbaafcb0b0","added_by":"auto","created_at":"2025-05-06 09:38:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1821442,"visible":true,"origin":"","legend":"\u003cp\u003eThe regression analysis on villages’ urban-rural distance and PLC\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/eafd105090514a821365b04c.png"},{"id":82044480,"identity":"241a56ad-8f3b-464d-97a2-60c9dc2ea2d7","added_by":"auto","created_at":"2025-05-06 09:30:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1066310,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of different types of travel intensity of Lin’an town and village residents at three spatial levels[8]\u003c/p\u003e\n\u003cp\u003e[8]To quantify the travelfrequency in the questionnaire data, we set weights according to different frequency intervals- almost daily at1.00, 3-5 times per week at 0.60, 1-2 times per week at 0.20, 1-2 times per month at 0.06, 1 time in two or three months at 0.02, 1-3 times per year at 0.01, and no travel at 0.00. Then the sample size was weighted and summed to obtain the travel intensity.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/c4309f38bef2626438cdf0a9.png"},{"id":82044488,"identity":"e45f54a9-e026-418a-823e-48680be197c5","added_by":"auto","created_at":"2025-05-06 09:30:13","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":803832,"visible":true,"origin":"","legend":"\u003cp\u003eQuestionnaire statistics of Hangzhou city residents traveling to towns and villages (a.) Travel purposes (b.) Comparison of the travel frequencies of respondents with or without family members in towns or villages\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/0c7fed671f70fa0c7f4846a5.png"},{"id":85231289,"identity":"134207aa-457b-43cd-b6f9-959a5f11721a","added_by":"auto","created_at":"2025-06-23 16:04:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12578420,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5733130/v1/52481021-a570-4cc2-b68b-d1f652040499.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Town-village Spatial Restructuring in Developed Regions of China from the Perspective of Resident Travel: A Case of Lin'an District, Hangzhou","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eTowns and villages in China\u0026apos;s developed regions have undergone profound spatial structural changes over the past decades (Zhang et al., 2022). It shows a faster pace and unique features under the national system, which has attracted the world\u0026rsquo;s attention (Chai et al., 2007, Long and Liu, 2016). From the 1980s to the 1990s, township enterprises[1] have successively sprung up in China\u0026apos;s eastern coastal areas, which has greatly promoted the industrialization of towns and villages from the bottom up. A typical example is the so-called \u0026ldquo;Zhejiang Model\u0026rdquo; (\u0026ldquo;浙江模式\u0026rdquo;) - originating from Zhejiang Province, China, it is a regional growth pattern driven by the private economy and grassroots entrepreneurship through market-oriented reforms (Zhao, 2009). With the growth of foreign trade and the implementation of the coastal opening policy, these township enterprises are increasingly integrated into the regional division of labor. Since the new century, the strengthening of the link to the global production system and intensive spillovers from metropolises to the surrounding areas has led to industrial specialization and spatial separation in rural areas, promoting the flows such as labor, capital, logistics, and information in a larger range (Woods, 2007, Yang et al., 2016). In addition, benefiting from the natural resources of the countryside and the huge urban demand for leisure and culture, rural tourism has developed rapidly, with pioneering regions starting as early as the 1990s. It further drives the shift in rural space use from production to consumption (Wu et al., 2024).\u003c/p\u003e\n\u003cp\u003eWith these macro trends, the functions of towns and villages have been transformed from a single agricultural form to a agriculture-industry-service integration model, which has further drove the rural space to become diversified, interactive, and dynamic, distinct from the traditional, homogeneous, and isolated form (Tian et al., 2014, Yang et al., 2016, Wu et al., 2024). The urban-rural relationship has also gradually changed from unilateral connection to bilateral interaction with complementary functions (Zhang et al., 2022, Qian et al., 2025). Under such a transforming context, the town-village spatial structure and the mechanisms behind it need to be re-recognized. \u003c/p\u003e\n\u003cp\u003eFrom a micro perspective, these changes result in a fundamental transformation of residents\u0026rsquo; working and living modes in town and village areas. It is because the economic, social, traffic, and other functional flows between regions foster people\u0026rsquo;s travel or movements, while in turn, they promote the reconstruction of the rural spatial structure (Woods, 2012, Chai et al., 2016). Moreover, due to the improvement of transportation and the increase in car ownership, rural residents now have greater accessibility and initiative to travel across villages, towns, and even cities, mainly stimulated by higher wages, public services, and consumer demand.\u003c/p\u003e\n\u003cp\u003eRegarding the policy context in China, 2017 witnessed a shift in emphasis towards the countryside when the Rural Revitalization Strategy[2] was put forward by the central leadership, with a series of strategies covering spatial configuration, industrial development, land management, human settlements, governance systems, etc., to support it (Liu et al., 2020). Local rural planning has become more multifunctional, targeted, and implemented, from the focus on single land use and facility allocation to people-centered ideology (Liu et al., 2020). Examples include the plan of the \u0026ldquo;beautiful rural cluster\u0026rdquo; in Guangzhou (Tang et al., 2024), the \u0026ldquo;rural functional unit\u0026rdquo; in Wuhan (Xiong, 2021), the \u0026ldquo;rural group\u0026rdquo; in Wuxi (Yuan and Wang, 2021), and the \u0026ldquo;urban-rural integrated development units\u0026rdquo; in Chengdu (Chen et al., 2020). They are similar in the idea that villages and towns can be merged into clusters and classified according to the 3 dimensions of \u0026ldquo;industry-residence-services\u0026rdquo; to achieve spatial control, resource sharing, industrial collaboration, and construction management. It helps reshape the rural spatial configuration and further promotes the free flow and rational allocation of urban and rural resources (Chen et al., 2020, Li et al., 2023).\u003c/p\u003e\n\u003cp\u003eTherefore, residents\u0026rsquo; activities, especially cross-regional travel, are considered to be an important reflection of spatial structure and are widely used to reveal spatial patterns (Niu and Li, 2022, Gao et al., 2023). However, previous studies on rural space often focus solely on the physical space itself or rigid town-village hierarchical systems, ignoring their openness, connections, and dynamics under the functional shift. One of the main reasons is that the spatial relation or connection is difficult to measure, especially in rural areas where data is limited. On the other hand, the in-depth mechanisms of space evolution in research using big data are still vague due to the lack of qualitative analysis.\u003c/p\u003e\n\u003cp\u003eThus, this study proposes a novel approach that combines mobile phone signaling data to map spatial linkages and field research to uncover the mechanisms of the phenomenon, and tests it in an empirical case context. The remainder of this paper is organized as follows: Section 2 is the literature review, elaborating on the spatial cognition evolution, the study of town-village space from the behavioral perspective, and the transformation of rural planning in China. Section 3 introduces the study area, data sources, and methodology. In section 4, town-village spatial structure is quantitatively measured using commuting and non-commuting travel links identified by mobile phone signaling data, including the characteristics of the network structures, clusters, and rural-urban links. In section 5, we explore the drivers of town-village spatial restructuring and the mechanisms through questionnaire data analysis and qualitative field research. Based on the research results, section 6 discusses how the town-village spatial restructuring connects to Western theories and the implications for the town-village spatial planning.\u003c/p\u003e\n\u003cp\u003e[1] Township enterprises refer to collective, cooperative or individual enterprises established in the rural area.\u003c/p\u003e\n\u003cp\u003e[2] The national \u0026ldquo;Rural Revitalization Strategy\u0026rdquo; aims at achieving five broad goals before 2050: economic vitality, ecological liveability, civilized rural communities, effective governance, and prosperous livelihoods. It broadens the definition of rural areas to encompass both towns and villages, advocating that towns play a leading role in village development, while villages contribute to the growth of towns. \u003c/p\u003e"},{"header":"2 Literature review","content":"\u003ch2\u003e2.1 Spatial restructuring: cognitive shift towards hybrid relations\u003c/h2\u003e\n\u003cp\u003eWith the deepening of the regional division of labor from the mid-20th century (Krugman, 1991), the understanding of space has evolved from an initial static, undifferentiated entity to a dynamic, interconnected, and hybrid construct rooted in the continuous (re-)shaping of relationships. Ullman (1957) suggests that no region can exist and develop in isolation, but through the material exchange and mutual collaboration between regions can obtain a win-win situation. The central place theory proposes the spatial relationships that central places with different orders provide goods and services for their corresponding rural hinterland, though the relationships between central places and regions beyond the hinterland were not established (Christaller and Baskin, 1966). Friedmann\u0026apos;s (1966) work on core-periphery dynamics further highlights the evolving spatial interactions within regional systems. Harvey (1973) introduces a social production idea that space is shaped by the relationships it contains, which vary across scales and are constantly in a process of reshaping. Under the \u0026ldquo;time-space compression\u0026rdquo; brought about by globalization and advanced communication technologies, Castells\u0026apos;s (1996) \u0026ldquo;space of flows\u0026rdquo; concept marked a more significant shift, emphasizing the dominance of relational networks (the \u0026ldquo;space of flows\u0026rdquo;) over geographical proximity (the \u0026ldquo;space of places\u0026rdquo;). This paradigm change has been supported by subsequent empirical studies on city networks (Alderson and Beckfield, 2004, Derudder and Witlox, 2009, Taylor et al., 2013), which highlight the importance of various flows - traffic, economic, information, and population - in shaping spatial networks.\u003c/p\u003e\n\u003cp\u003eThe above changes also influence the realm of rural studies, as the countryside has gradually become open and has been reconstructed with the diverse material exchanges with the outside world (Woods, 2007, Fink et al., 2013, Yang et al., 2016). The relational perspective views rural space as a multi-authored, multi-faceted, and co-constituted space, shaped through local-global interconnections and their place-specific manifestations (Heley and Jones, 2012). It advocates for a relational rural epistemology that recognizes the co-constitutive production of rural space through material and discursive phenomena, processes, and practices, highlighting the theoretical pluralism in comprehending new rural space in its multidimensional complexity\u0026nbsp;(Heley and Jones, 2012, Qian et al., 2025). Similarly, the \u0026ldquo;global countryside\u0026rdquo; illustrates that\u0026nbsp;the full picture of rural\u0026nbsp;space\u0026nbsp;can only be\u0026nbsp;seen\u0026nbsp;through a hybrid and networked approach at the interregional level, rather than through a single site or urban-centric approach\u0026nbsp;(Woods, 2007, Woods, 2009).\u0026nbsp;With\u0026nbsp;the rural transition began in the Global North before progressing to the Global South\u0026nbsp;(Wu et al., 2024), the rural space in China is also increasingly understood as a dynamic and multifaceted phenomenon that transcends static, predefined socio-economic and cultural attributes, and is constantly being redefined and reimagined through its socio-spatial interactions with the urban\u0026nbsp;(Qian et al., 2025).\u003c/p\u003e\n\u003cp\u003eHowever, Hoggar and Paniagua (2001) criticize the indiscriminate use of the term \u0026ldquo;rural restructuring,\u0026rdquo; which has become a catch-all phrase in academic discourse. To more accurately determine whether and to what extent rural restructuring has genuinely occurred, they propose viewing restructuring as an \u0026ldquo;approach\u0026rdquo; rather than a pre-set \u0026ldquo;fact\u0026rdquo;, and this approach necessitates a holistic and thorough examination of various dimensions, encompassing economic diversification, social stratification, cultural evolution, and spatial reorganization (Hoggar and Paniagua, 2001, Long and Liu, 2016).\u003c/p\u003e\n\u003cp\u003eCollectively, rural spatial restructuring is a complex process manifested through the interplay of multiple dimensions such as infrastructure networks, production and lifestyle changes, the mobility and heterogeneity of socio-spatial relations, and the dynamic nature of space itself (Long and Liu, 2016), which challenge traditional understandings of rurality (Qian et al., 2025). Yet the restructuring concept often lacks precision and theoretical depth, or the support of empirical evidence. Therefore, an up-to-date spatial interpretation framework for rural space should be established with the hybrid connections between spaces and the logic of functional organization behind them.\u003c/p\u003e\n\u003ch2\u003e2.2 Rural spatial analysis from the behavior perspective\u003c/h2\u003e\n\u003cp\u003eBuilding on the cognitive shift discussed in Section 2.1, the understanding of rural space has long been enriched by examining the dynamic activity space composed of residents\u0026rsquo; daily behavioral activities (Chai et al., 2016). These activities, with their diverse functions, continuously (re-)shape the rural space (Wang et al., 2021). This perspective traces back to the emergence of behavioral geography and spatiotemporal geography in the 1960s and 1970s\u0026nbsp;under the Western humanist trend, which emphasized the spatial and temporal manifestations of human behavior, highlighting individual agency and the relationship between activities\u0026nbsp;(especially\u0026nbsp;travel or movement)\u0026nbsp;and space\u0026nbsp;(H\u0026auml;gerstraand, 1970, Massey, 1999). Studies in this area cover daily space-time patterns of residential, commuting, consumption, recreation, social visits, and public service access, in which great regularity is found\u0026nbsp;(Ahas et al., 2010, Gao et al., 2023). Some research explores spatial organization through diverse travel behaviors\u0026nbsp;(Asakura and Iryo, 2007, Verhetsel et al., 2018)\u0026nbsp;or identifies different zones based on activity patterns\u0026nbsp;(Fu and Wang, 2021). These studies highlight the functional connectivity patterns revealed by different types of travel links,\u0026nbsp;reveal the rapid transformation of urban lifestyles, as well as\u0026nbsp;people\u0026rsquo;s\u0026nbsp;decision-making mechanisms in undergoing socio-economic transition.\u003c/p\u003e\n\u003cp\u003eIn rural contexts, research often examines the living and production spaces formed by residents\u0026rsquo; daily activities in various natural and cultural settings (Guo et al., 2020). Studies in China often aim to inform planning, focusing on identifying patterns, evolution, and drivers of change under considerations of human-land relationships (Wang et al., 2021). The impact of globalization, urbanization, and informatization on rural living space has also garnered increasing attention\u0026nbsp;(Zhang et al., 2022, Wang et al., 2023). However, traditional data collection methods, such as activity diaries, questionnaires, interviews, and censuses, often fail to capture the complexity of activity space in the face of rural population diversification and spatial heterogeneity\u0026nbsp;(Gao et al., 2023).\u003c/p\u003e\n\u003cp\u003eThe advent of mobile phone signaling big data has significantly enhanced spatial-temporal granularity, overcoming limitations of low spatial accuracy, small sample size, and poor timeliness, offering advantages in investigating rural spatial structure (Liu et al., 2020, Gao et al., 2023), especially given the widespread mobile phone ownership among rural residents. While mobile phone signaling data has been widely used in urban research since 2010, its application in rural areas remains limited. Notable studies include Eagle et al. (2009), who compared behavioral dynamics in rural and urban societies using mobile phone data, finding that rural and urban communities differ dramatically in terms of personal network topologies and behavioral characteristics such as travel. Using the same data, Liu et al. (2020) analyzed rural residents\u0026rsquo; daily activity patterns by frequency, diversity, and the spatial range of activities. Through movement links measured by mobile phone signaling data, Zhao and Xu (2019) identified complex network characteristics and cluster-form spatial connections in a town of Zhongshan City, China. Niu and Li (2022) also used this data to measure inter-town commuting and non-commuting travel linkages in the Shanghai suburb and identified clusters within, from which they proposed to optimize the town circles\u0026rsquo; spatial configuration in a networked manner. The above explorations demonstrate the feasibility and potential of mobile phone signaling data in rural spatial analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"3 Study area and methods","content":"\u003ch2\u003e3.1 Study area\u003c/h2\u003e\n\u003cp\u003eLin\u0026rsquo;an District is located in the outer suburbs of Hangzhou\u0026nbsp;metropolis, Zhejiang Province, eastern China\u0026nbsp;(Figure 1). It includes 18 town- (street-) level administrative units, covering an area of 3126.8 km\u003csup\u003e2\u003c/sup\u003e. It had 635 thousand permanent residents in 2020, including 258 thousand rural residents. Since 2017, Lin\u0026rsquo;an\u0026rsquo;s administrative level has been upgraded from county level to city level, meaning it officially joined the Hangzhou city district. Due to the location of the developed areas and the solid historical industrial foundation, Lin\u0026rsquo;an\u0026rsquo;s rural economy is relatively prosperous. The per capita disposable income of rural residents is higher than the average value of the eastern region and far higher than that of the central, western, and northeast regions in China. Under the guidance of the \u0026ldquo;Two Mountains Theory\u0026rdquo; (\u0026ldquo;两山理念\u0026rdquo;)[3], Lin\u0026rsquo;an\u0026rsquo;s development mode is in the process of a shift from extensive expansion to more emphasis on green development and quality improvement. Thus, Lin\u0026rsquo;an\u0026rsquo;s new economy, especially the e-economy and eco-tourism, has developed vigorously in the past 10 years. Moreover, promoted by the rich local governments, the construction of settlements, public service facilities, and infrastructure in rural Lin\u0026rsquo;an is also at a high level, forming a new model of \u0026ldquo;beautiful towns and villages\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eIn summary, rural Lin\u0026rsquo;an has been transforming from self-organized development relying on natural resources to spatial reconstruction under the influence of external forces such as urbanization, industrialization, informatization, and radiation of the metropolis. Whilst, it also retains rurality in geography, society, and industry. Therefore, with a diverse urban-rural-dual nature, the Lin\u0026rsquo;an rural area makes a typical case for our study.\u003c/p\u003e\n\u003cp\u003eTowns and villages in China are regarded as closely interconnected and indivisible systems that are often studied as a whole. The town-village area studied in this paper covers 13 towns or 298 administrative villages in Lin\u0026rsquo;an District. Among them, Yuqian Town and Changhua Town are the two central towns (\u0026ldquo;中心镇\u0026rdquo;) with comprehensive functions, assuming the central and western sub-centers of Lin\u0026rsquo;an, respectively. The Lin\u0026rsquo;an city area (the 5 street-level administrative units) located in the east is the main center, which is depart from the town-village area. Under a town-level administrative division, there are two levels of administrative villages \u0026nbsp;(\u0026ldquo;行政村\u0026rdquo;) - town center village(s) \u0026nbsp;(\u0026ldquo;镇区\u0026rdquo;) and other general villages.\u003c/p\u003e\n\u003ch2\u003e3.2 Methods and data\u003c/h2\u003e\n\u003ch3\u003e3.2.1 Data source and link identification\u003c/h3\u003e\n\u003cp\u003eIn this study, we use mobile phone signaling data to identify two kinds of resident travel links - commuting links and non-commuting links. The former refers to travel from home to the workplace. The latter involves travel from home to a variety of public services, mainly including out-of-class education, medical care, shopping, and recreation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mobile phone signaling data was obtained from China Mobile[4] for 30 consecutive days in April 2017, including 20 working days and 10 rest days. The data fields include user ID, time, and base station code. The total number of communication base stations within the study area is 2126, with an average spatial coverage of 1.47 km2 each, covering 90.1% of the villages. 25 villages with no base stations distributed were excluded from the follow-up calculation.\u003c/p\u003e\n\u003cp\u003eIn the 30 days, when a user stayed for the longest time and at least greater than 2 hours from 19:00 to 8:00 the next day, and this routine had the largest number of repeated days and at least 60% of the total days, then the location of this base station was taken as the user\u0026apos;s home. The location identified in the same way from 9:00 to 18:00 during the daytime was regarded as the user\u0026rsquo;s workplace. When a user traveled from home and then stayed within the range of a destination base station for more than 30 minutes, and this base station was neither the home nor workplace base station, then this base station was defined as a non-commuting destination. We considered a link between the user\u0026apos;s home and workplace as a commuting link, and a link between home and the non-commuting destination as a non-commuting link. A total of 79,500 commuting links and 1,159,500 non-commuting links were identified within the study area.\u003c/p\u003e\n\u003ch3\u003e3.2.2 Travel networks building and analysis\u003c/h3\u003e\n\u003cp\u003eTo depict the spatial distribution of resident travel, we built commuting and non-commuting networks by drawing on the complex\u0026nbsp;network analysis approach\u0026nbsp;(Niu and Li, 2022, Gao et al., 2023). Specifically, the geometric\u0026nbsp;center points of villages served as network nodes, the linking lines among them as edges, and the sum of two-way travel links as the weight of the edges. The one-way movement trajectories from Village A to Village B, and from Village B to Village A, were summed into a single two-way link between Village A and Village B.\u0026nbsp;Only inter-village links were retained, and intra-village travel links were excluded. Moreover, the links between villages and urban areas (Lin\u0026rsquo;an City and Hangzhou Central City) were summed up in the same way.\u003c/p\u003e\n\u003cp\u003eTo quantify the hierarchical characteristics of inter-village travel links, we defined an indicator - \u0026ldquo;proportion of top town center links (PTCL)\u0026rdquo; - for each village, i.e., the proportion of links between a village and the maximum-link town center to the total amount of external links to the village. For a village, the larger the PTCL, the more dominant the village\u0026apos;s linkage with the top town center, and vice versa, for a more evenly split linkage with neighboring villages.\u0026nbsp;For all the villages studied, the more villages with high PTCL, the more centralized and hierarchical the whole linkage structure is, and vice versa, the more decentralized and flatter it is. All linkage values here refer to two-way linkages. The formula is as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003e3.2.3 Network cluster identification\u003c/h3\u003e\n\u003cp\u003eWe employed the Louvain method, a community-detecting algorithm proposed by Blondel et al. (2008), to detect clusters in the networks. The algorithm goes through several iterations, trying to add individual nodes to the communities (clusters) that can maximize modularity until no node change in the network can improve the modularity[5], and the algorithm automatically stops. As the iteration proceeds, smaller clusters are gradually merged. We substituted the commuting network and the non-commuting network into the algorithm. Both the two networks eventually went through three iterations and demonstrated 12 and 10 clusters, respectively. The final modularity reached 0.77 and 0.67, respectively. The modularity is high, meaning that the intra-cluster links are very tight and the inter-cluster links are relatively weak.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e3.2.4 Field research and questionnaire distribution\u003c/h3\u003e\n\u003cp\u003eAfter big data mapping, we further dig into the drivers of town-village spatial restructuring and the mechanisms behind them. Firstly, we selected\u0026nbsp;4 representative towns\u0026nbsp;in the Lin\u0026rsquo;an district:\u0026nbsp;Yuqian, Changhua, Tianmushan, and Taihuyuan. Next,\u0026nbsp;6-8 villages in each town, including town-center villages and general villages at varying distances from them\u0026nbsp;(32 villages in total), were selected for in-depth\u0026nbsp;field research. We visited the town governments, village committees, typical rural households, and some enterprises to investigate\u0026nbsp;details of local industries, town and village construction, and residents\u0026apos; daily lives.\u003c/p\u003e\n\u003cp\u003eMeanwhile, a questionnaire was distributed to a random sample in these villages from 12\u0026nbsp;July\u0026nbsp;to 20\u0026nbsp;July 2021. Questionnaires\u0026nbsp;were distributed to rural residents face-to-face by members of the investigation team, with\u0026nbsp;about 20 questionnaires in each town-center\u0026nbsp;village, and 6-10 questionnaires in each general village. The questionnaire mainly included questions on the respondents\u0026rsquo; basic personal and family information, employment, and frequency of travel for various purposes. A total of 307 questionnaires were collected, with 299\u0026nbsp;valid ones. The valid questionnaire rate was 97%.\u003c/p\u003e\n\u003cp\u003eIn addition, another questionnaire was distributed to city residents of Hangzhou via Wenjuanxing - a Chinese professional questionnaire online platform - between 27 July and 31 July 2021. This questionnaire mainly contained aspects such as respondents\u0026apos; basic information, and frequency and purpose of traveling to the countryside. A total of 210 questionnaires were collected. After excluding the samples of respondents living outside Hangzhou urban areas, 164 questionnaires were considered valid. The questionnaire validity rate was 78%.\u003c/p\u003e\n\u003cp\u003e[3] As a guide to action for national ecological civilization, the \u0026ldquo;Two Mountains Theory\u0026rdquo; holds that lucid waters and lush mountains are invaluable assets, revealing the dialectical unity between economic development and ecological protection.\u003c/p\u003e\n\u003cp\u003e[4] As the No. 1 of China\u0026apos;s three major mobile phone service providers, China Mobile has a 52.54% market share in 2020, which can fulfill the sample size requirement for our data sampling. Considering user privacy issues, the users\u0026rsquo; information is hidden in the original dataset.\u003c/p\u003e\n\u003cp\u003e[5] The Louvain method is a modularity optimization-based algorithm that iteratively assigns nodes to different communities to maximize the modularity value of the network. Modularity is a measure of the strength of division of a network into communities, reflecting the density of connections within communities compared to connections between communities. A higher modularity value indicates stronger internal connections within communities and weaker connections between different communities, suggesting a more distinct and well-separated community structure in the network.\u003c/p\u003e"},{"header":"4 Characteristics of the town-village spatial structure","content":"\u003ch2\u003e4.1 The hierarchical form\u0026nbsp;dominates, while the network pattern appears\u003c/h2\u003e\n\u003cp\u003eFrom the commuting and non-commuting networks of the Lin\u0026rsquo;an town-village area (Figure 2), their\u0026nbsp;patterns both primarily show a hierarchical \u0026ldquo;central place\u0026rdquo; form, where the centers of each town form radial connections with the surrounding villages. Among them, the linkage patterns of the two central towns -\u0026nbsp;Yuqian and Changhua\u0026nbsp;-\u0026nbsp;are more central. And they are linked to a larger range of areas beyond their township boundaries. Whereas, a networking trend has simultaneously emerged. Some villages have formed closer horizontal links with each other, especially in the areas adjacent to Lin\u0026rsquo;an City, where relatively dense and flat networks\u0026nbsp;formed. In other words, residents travel to and from villages of the same level to a great extent, not just between general villages and town centers. this finding suggests a mismatch to the traditional \u0026ldquo;central place\u0026rdquo; model of town-village spatial structure.\u003c/p\u003e\n\u003cp\u003eThe results in Figure 3 show that in commuting and non-commuting networks, villages with PTCL greater than 0.3 accounted for 40.0% and 8.3%, respectively; while villages with PTCL less than 0.1 accounted for 31.6% and 60.4%, respectively. It indicates that although there are still some villages that form major links with a single town center, some have built evenly matched links with other town centers or villages. Therefore, the dominance of the town center, with which they have major links, is not clearly shown. Specifically, commuting links are more confined within the township, similar to the \u0026ldquo;central place\u0026rdquo; system within each township. In contrast, non-commuting links are more extensive, more dispersed, and less hierarchical. It is worth noting that for a village, the top-linked town center is not necessarily in the town to which it belongs, i.e., a village may exceed its township to form its major link with other town centers (mainly the two central towns). This is the case for 16% and 74% of the commuting and non-commuting networks, respectively. This result is somewhat contrary to the conventional notion of the hierarchical town-village system in China, also deviating from the assumptions of the central place theory, which we will elaborate on in the discussion section.\u003c/p\u003e\n\u003ch2\u003e4.2 Links extend on a large scale while forming clusters at the local level\u003c/h2\u003e\n\u003ch3\u003e4.2.1 Analysis of travel distances\u003c/h3\u003e\n\u003cp\u003eIn the Lin\u0026rsquo;an town-village area, the average non-commuting travel distance[6] is longer than that of commuting (see Table 1): when all links are calculated, the average commuting distance is 1322m, while the average non-commuting distance is 1397m - slightly higher than the former. When only inter-village links are considered, the average non-commuting distance (2045m) is significantly higher than the average commuting distance (1625m). This result indicates a higher proportion of long distances in non-commuting travel, though this may be influenced by the different identification algorithms of the two types of trajectories.\u003c/p\u003e\n\u003cp\u003eNext, we do the horizontal urban-rural comparison. Firstly, the second section in Table 1\u0026nbsp;shows that the average distance for both types of travel in Lin\u0026rsquo;an City is lower than that in the Lin\u0026rsquo;an\u0026nbsp;town-village area. One possible reason for this is that the Lin\u0026rsquo;an City itself is small in size so long-distance travel is mainly linked to the Hangzhou central city.\u0026nbsp;Secondly,\u0026nbsp;the average commuting distance in the Hangzhou central city is considerably higher than that in the Lin\u0026rsquo;an\u0026nbsp;town-village areas, regardless of whether the calculation includes intra-village links. Only for the inter-village non-commuting average distance, the former is lower than the latter. This is\u0026nbsp;possible because the distribution density of various public service facilities in the rural area is lower than that in the city, making it unavoidable to travel longer distances to access the services.\u003c/p\u003e\n\u003cp\u003eAs the work-residence relationship is considered an important aspect in judging the spatial structure configuration, we take the commuting distance as a key indicator. From Table 2, the daily commuting distances of rural residents are mostly short, i.e., links of less than 3 km account for the majority. It is worth noting that longer-distance commuters are also beginning to appear and have become non-negligible in number. When all links are calculated, the proportion of commuting links longer than 3 km is as high as 33.2%, those larger than 5 km are 17.9%, and those larger than 10 km still make up 4.8%. A total of 11.2% are inter-town links. Whilst among inter-village links, the proportions of all the above long-distance links are even higher.\u003c/p\u003e\n\u003cp\u003eTab. 1 Average commuting and non-commuting travel distances in different regions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eTown-village area of Lin\u0026rsquo;an\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003eLin\u0026rsquo;an City\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eHangzhou Central City\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eAll links, including intra-village links\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eInter-village links only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eAll links, including intra-village (community) links\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eInter-village (community) links only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eAll links, including intra-village (community) links\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eInter-village (community) links only\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eCommuting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1322 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1625 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1313 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1581 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e2483 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e2787 m\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eNon-commuting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1397 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2045 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e414 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e462 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1417 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1516 m\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTab.2 Percentage of commuting links of different distances in the Lin\u0026rsquo;an town-village area\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026gt;3km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026gt;5km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026gt;7km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026gt;10km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eCross-town\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eAll links\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e33.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e17.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e10.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e4.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e11.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eInter-village links only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e41.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e22.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e13.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e6.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e14.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e4.2.2 Analysis of network clusters\u003c/h3\u003e\n\u003cp\u003eClusters\u0026nbsp;in our study\u0026nbsp;can be interpreted as network substructures formed by the self-organized people flow, representing rural\u0026nbsp;functional zones\u0026nbsp;promoted by the demand of residents. The commuting clusters are indicators of the work-residence balance situation, while the\u0026nbsp;non-commuting clusters illustrate the pattern of linkages between homes and rural public services and consumption places. Corresponding to the structure of the linkage networks in Figure 1,\u0026nbsp;each cluster often contains a core\u0026nbsp;(usually the town centers) and a hinterland that are closely interconnected.\u003c/p\u003e\n\u003cp\u003eFigure 4 shows that the clusters identified from the commuting and non-commuting networks differ in spatial pattern. There are 12 smaller and more equitable-in-size clusters\u0026nbsp;identified from the commuting network. Each cluster has a balanced work-residence relationship within it, with shorter commuting distances.\u0026nbsp;By comparison, the non-commuting network forms 10 clusters with greater variation in size. Among them, the boundaries of the two clusters with Yuchen and Changhua towns as the cores, respectively, noticeably extend beyond the town boundaries and include the surrounding villages of other towns. While the rest of the clusters are smaller.\u003c/p\u003e\n\u003cp\u003eInterestingly, the clusters of both commuting and non-commuting networks do not completely match town administrative boundaries. A few clusters, especially the two central clusters, break through their town boundaries and extend outward, while some split into two clusters within a township. This finding indicates that the administrative factor plays an inconclusive role in separating the cluster organization\u0026nbsp;of resident travel in rural areas. Instead, it may be influenced by a variety of other factors. Additionally, the modularity of the commuting network (0.77)\u0026nbsp;is higher than that of the non-commuting network (0.67), indicating that the former has a more distinct feature of clustering.\u003c/p\u003e\n\u003ch2\u003e4.3 Linkages to the city strengthen, following the\u0026nbsp;distance decay law\u003c/h2\u003e\n\u003cp\u003eFrom the analysis above, the daily travel ranges of rural residents have extended far beyond a walkable range, so it is necessary to analyze the links between rural and urban areas. Figure 5 illustrates the results of the regression analysis on the two indicators: 1) the distance between each village and the city, and 2)\u0026nbsp;PLC. It is found that the farther the distance between a village and Lin\u0026rsquo;an City, the lower the percentage of its commuting and non-commuting\u0026nbsp;links with Lin\u0026rsquo;an City is, indicating that the geographical proximity of residents\u0026rsquo; travel has not been surpassed to a large extent. In other words, rural\u0026nbsp;residents living close to the city rely more on the city for access to\u0026nbsp;jobs and higher-level public services, thus\u0026nbsp;having greater cross-border mobility. Whereas villages farther away from the city mainly form a stable work-residence and services-residence balance with neighboring towns and villages.\u003c/p\u003e\n\u003cp\u003eFurthermore, this distance decay is not linear but approximates a logarithmic function curve. It means that when the distance increases to a certain degree, the regression curve gradually flattens out, so the travel proportion to Lin\u0026rsquo;an City does not decrease much with the distance increase. The goodness of fit of commuting links is better than that of non-commuting links, with the\u0026nbsp;R\u003csup\u003e\u0026nbsp;\u003c/sup\u003esquare of 0.60 and 0.56, respectively. It\u0026nbsp;indicates that the commuting\u0026nbsp;decay trend is more obvious, while the latter is more insensitive to geographic distance, probably due to the greater occasionality in service and leisure travel.\u003c/p\u003e\n\u003cp\u003eHowever, for the regression analysis of the villages to the Hangzhou Central City, no such decay pattern is shown. It is presumably because when the travel distance exceeds a certain threshold, the travel is very low in\u0026nbsp;frequency, depending more on the random personal demand without a daily pattern.\u003c/p\u003e\n\u003cp\u003eWe further calculated the proportion of the scale of the rural-urban link. Of residents living in the Lin\u0026rsquo;an town-village area and having a stable workplace outside of the same village, 8.6% of them have their workplace in Lin\u0026rsquo;an city. For the non-commuting links, 16.7% of rural residents have travel destinations in Lin\u0026rsquo;an City and 2.8% in Hangzhou Central City. Moreover, the scale of the urban-to-rural links is also considerable: the number of commuters living in Lin\u0026rsquo;an City and employed in the town-village area is about twice that in the opposite direction. The number of non-commuting travelers from Lin\u0026rsquo;an City to the town-village area is about 40% higher than that in the opposite direction; the number of non-commuting travelers from Hangzhou Central City to the Lin\u0026rsquo;an town-village area is nearly four times that in the opposite direction. It is shown that with the overall improvement of urban and rural economy, the urban-rural dualism is gradually broken, and regular daily travels across urban and rural areas have been formed.\u003c/p\u003e\n\u003cp\u003e[6] The (non-)commuting distance here refers to the Euclidean distance between the two base station points. Considering that the base station layout makes it difficult to identify short-distance travel within 1 km, the actual average distance may be shorter as links within the same base station radiation range are discarded.\u003c/p\u003e"},{"header":"5 Drivers of town-village spatial restructuring","content":"\u003cp\u003eMultiple exogenous and endogenous factors are driving the changes in the town-village\u0026nbsp;area revealed above, including natural resources, economic, social, policy, and transportation. This section summarizes major drivers from the spatial relational perspective into three aspects: transportation and information technology\u0026nbsp;improvement, industrial reconstruction, and the changes in physical space resulting from policies.\u003c/p\u003e\n\u003ch2\u003e5.1 Time-space compression caused by technology development\u003c/h2\u003e\n\u003cp\u003eLimited by the backward productivity level and traffic conditions, previous\u0026nbsp;villages were often centered on settlements, with the farming distance determining the village\u0026nbsp;range.\u0026nbsp;Therefore, the traditional rural landscape in China featured homogeneous, independent, and was greatly affected by natural factors such as mountains and rivers.\u0026nbsp;Nowadays, however, the significant improvement of transportation infrastructure and communication technology has greatly weakened the geographic frame of village and town development (Yang et al., 2016), which is described as \u0026ldquo;time-space\u0026nbsp;compression\u0026rdquo;,\u0026nbsp;triggering the\u0026nbsp;reconstruction of\u0026nbsp;town-village landscapes and the formation of town-village networks.\u003c/p\u003e\n\u003cp\u003eFirstly,\u0026nbsp;the improvement of rural transportation\u0026nbsp;has provided residents with long-distance accessibility, which has\u0026nbsp;significantly expanded the scale of live-work-service cells. By 2016, the motorized rate of rural roads in Lin\u0026rsquo;an reached 100%, and the public transport accessibility of natural villages\u0026nbsp;(the lowest division level under the administrative village) in the region reached 99%. Since 2020, an east-west expressway has been constructed\u0026nbsp;crossing Lin\u0026rsquo;an District and a subway line connecting to Hangzhou\u0026nbsp;Central City. The private car ownership rate of rural residents has also\u0026nbsp;been greatly improved. According to our questionnaire data, over 70% of the rural families in Lin\u0026rsquo;an own their cars and can easily travel between towns and villages, even to Lin\u0026rsquo;an City and Hangzhou Central City. However, it is worth noting the shortage and long intervals of rural public transport, and some natural villages still do not have public transport stations. This results in inequity of accessibility for the elderly, juvenile, low-income earners, and other vulnerable groups without cars or driving capability.\u003c/p\u003e\n\u003cp\u003eSecondly, informatization has indirectly influenced spatial restructuring by changing the way of production, consumption, and social interaction of rural residents. The first point to mention is rural production in the network era. Towns and villages have greater chances to explore their talented resources and comparative advantages, therefore easily participating in the regional division of labor\u0026nbsp;and creating more rural employment\u0026nbsp;(Wu et al., 2021, Wang et al., 2023). Typical cases are \u0026ldquo;\u003cem\u003eTaobao\u003c/em\u003e village\u0026rdquo; and \u0026ldquo;internet-famous village\u0026rdquo;[7] emerging in recent years. Some towns and villages play the leadership role and reorganize their surrounding areas. For example, Bainiu Town in Lin\u0026rsquo;an has become a base of e-entrepreneurship incubation, e-commerce training, and sightseeing. To support Bainiu, the nearby Daoshi Town serves as the main production base, Longgang Town and Qingliangfeng Town are the main processing and logistics bases, and Changhua Town is the exhibition and tourism center. Thanks to online shopping platforms and logistics networks, these town group\u0026rsquo;s products are sold nationwide.\u003c/p\u003e\n\u003cp\u003eAnother point is about rural life. Online shopping has partly replaced the commercial functions of town\u0026nbsp;centers and urban areas. Our questionnaire\u0026nbsp;shows that the rural\u0026nbsp;residents in Lin\u0026rsquo;an, especially young and middle-aged groups, have already become accustomed to online shopping. In addition, the prevalence of online chatting has not only expanded the social network but also transferred kinship and geographical ties in rural areas. In addition, Figure 6 illustrates that travel for \u0026ldquo;visiting relatives and friends\u0026rdquo; is still frequent among the Lin\u0026rsquo;an\u0026nbsp;rural\u0026nbsp;residents. Hangzhou urban residents with family members who live or work in towns and villages have a higher travel frequency between urban and rural areas (see\u0026nbsp;Figure 7). It is suggested that though the urban-rural\u0026nbsp;gap is sewn by modern technologies, the traditional rural social relations have not disintegrated, but to some extent, been strengthened.\u003c/p\u003e\n\u003ch2\u003e5.2 Upgrading and diversification\u0026nbsp;of industry structure\u003c/h2\u003e\n\u003cp\u003eSince the 1980s\u0026nbsp;and 1990s, substantial bottom-up industrialization in rural\u0026nbsp;Lin\u0026rsquo;an has promoted the transformation\u0026nbsp;of industry structure\u0026nbsp;and formed local industrial clusters. It is not a\u0026nbsp;rare case in the developed regions of China\u0026nbsp;(Zhang et al., 2022).\u0026nbsp;The\u0026nbsp;original single agricultural production has evolved into a comprehensive industrial structure integrating agricultural production, agricultural product processing, cultural tourism, e-commerce, scientific research, etc. For example, originated from bamboo planting, the bamboo shoot industry in Taihuyuan Town\u0026nbsp;has developed\u0026nbsp;into\u0026nbsp;an industrial cluster including bamboo seeding research and breeding, bamboo shoot gardening technology research and promotion, bamboo science popularization, ecological teaching, and rural technicist training. The pecan industry in the west of Lin\u0026rsquo;an has also extended from original planting and processing to e-commerce platform sales, leisure agriculture, and cultural tourism.\u003c/p\u003e\n\u003cp\u003eThe reconstruction of the industry has changed local labor markets\u0026nbsp;and the connectivity between work and residence, which in turn have also reshaped\u0026nbsp;the rural spatial structure.\u0026nbsp;The advancement of the new economy, especially the e-commerce, has been proven to intensify the expansion and integration of rural land use and the spatial network connections between towns and villages (Wang et al., 2023). In our study, on the one hand, different from urban areas, the locality and informality of town and village industries determine that the distance between Lin\u0026rsquo;an rural residents\u0026rsquo; occupation and residence is mainly short. From our questionnaire data, about 95% of rural\u0026nbsp;employees live nearby. Among them, about 26.8% work part-time in enterprises\u0026nbsp;near their home, and meanwhile operate small shops, farmhouse restaurants, homestays, online shops, or cultivate their own farmland. But on the other hand, some\u0026nbsp;long-distance commuters, even across urban and rural areas, have already appeared. Specifically, people living in rural areas find their jobs in\u0026nbsp;city enterprises, institutions,\u0026nbsp;or governments, commuting in the\u0026nbsp;\u0026ldquo;pendulum\u0026rdquo;\u0026nbsp;mode, which used to be characterized as the urban commuting pattern.\u003c/p\u003e\n\u003ch2\u003e5.3 Concentration of\u0026nbsp;built-up space driven by policies\u003c/h2\u003e\n\u003cp\u003eFirst of all, this spatial concentration is manifested in industrial land use. Like most rural areas in the Chinese developed\u0026nbsp;region\u0026nbsp;along the southeast coast, with the advantages of a loose policy environment, cheap land rent, and low labor prices, Lin\u0026rsquo;an has been industrialized for decades.\u0026nbsp;The early rise of the private economy in towns and villages has\u0026nbsp;led to the point-like\u0026nbsp;sprawl of industrial land. However, in recent years, guided by top-down\u0026nbsp;policies encouraging industry agglomeration, township industries have begun to relocate to industrial parks mainly neighboring town\u0026nbsp;centers, especially in central towns.\u003c/p\u003e\n\u003cp\u003eA similar concentration trend is seen in the spatial layout of public service facilities.\u0026nbsp;The allocation of public service facilities in rural\u0026nbsp;Lin\u0026rsquo;an traditionally\u0026nbsp;follows the hierarchical model, so as to match the settlement layout. However, a myriad of policies in recent years have contributed to the rapid and large-scale implementation of the merging of townships and\u0026nbsp;the relocation and combination of rural settlements. From 2001 to 2011, the number of townships in Lin\u0026rsquo;an was reduced from 39 to 13, and the number of administrative villages was reduced from more than 600 to around 200. A typical example of a response to it is\u0026nbsp;that most of the village-level kindergartens and primary schools have been or will be revoked. The two central towns, Yuqian and Changhua, own public service\u0026nbsp;facilities of larger scales and better quality in rural\u0026nbsp;Lin\u0026rsquo;an,\u0026nbsp;equipped with senior middle schools, junior middle schools, district-level hospitals, hub bus stations, large shopping malls, and entertainment facilities.\u0026nbsp;They attract more\u0026nbsp;people from surrounding towns and villages with medical, shopping, entertainment, and travel needs. In contrast, other general\u0026nbsp;towns mostly\u0026nbsp;own only town governments and farmers\u0026apos; markets. Thus, their importance\u0026nbsp;in the service or even the overall centrality\u0026nbsp;has been greatly weakened.\u003c/p\u003e\n\u003cp\u003eThe above changes in physical space have led to a concentration of daily flows towards the two central towns. The results are presented in the mobile phone signaling data mapping in Section 4.1. The central place form is dominant viewed from the regional level, within which the hierarchical transformations and structural distortions occur. As the industrial parks, residential communities, and commercial centers of the two central towns are more clearly zoned, the intra-core network densification is also significant.\u003c/p\u003e\n\u003cp\u003e[7] A Taobao Village is an administrative village where a significant number of local residents operate e-commerce businesses on the Taobao platform, with at least 10% of households engaged in online sales or an annual e-commerce transaction volume of over RMB 10 million. An \u0026ldquo;internet-famous village\u0026rdquo; or \u0026ldquo;\u003cem\u003eWanghong\u003c/em\u003e village\u0026rdquo; is a village that has leveraged its unique natural landscapes, cultural heritage, or innovative development models to attract a large number of visitors through social media platforms, thereby becoming a popular tourist destination.\u003c/p\u003e"},{"header":"6 Discussion","content":"\u003cp\u003eThe spatial restructuring of the town-village area is not a singular transformation of land functions but also involves changes in spatial functional relationships, which are closely related to the\u0026nbsp;work and life of rural residents. From agricultural civilization to industrial civilization and then to the informatization\u0026nbsp;era, the towns and villages in the developed regions have experienced earlier and more drastic spatial changes in China, challenging and extending traditional central place theory. There are two points to discuss in this section.\u003c/p\u003e\n\u003cp\u003eThe first point addresses the trend of networked restructuring in modern rural spaces.\u0026nbsp;In Christaller\u0026rsquo;s central place model, central places of different orders provide commercial, administrative, and transportation functions of different levels, while the hinterlands or \u0026ldquo;complementary regions\u0026rdquo; are in the position of receiving services (Christaller and Baskin, 1966).\u0026nbsp;Aligning\u0026nbsp;with this\u0026nbsp;hypothetical framework, the long-standing town and village planning in China has built a hierarchical system of\u0026nbsp;\u0026ldquo;central town - general town - central village - general village\u0026rdquo;. Most of the previous\u0026nbsp;studies on\u0026nbsp;China\u0026rsquo;s\u0026nbsp;town-village system\u0026nbsp;and village layout planning\u0026nbsp;also follow this logic, but\u0026nbsp;limited by its strict assumptions, static nature, and lack of consideration for natural-human interactions, it struggles to fully explain the observed spatial patterns in modern rural areas (Wang and He, 2014, Cao et al., 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThus, a mixture of hierarchical and networked spatial structures in rural Lin\u0026rsquo;an calls for a\u0026nbsp;more dynamic and linkage-oriented approach to understanding spatial organization, which\u0026nbsp;should\u0026nbsp;not be\u0026nbsp;limited to\u0026nbsp;hierarchical patterns,\u0026nbsp;not only\u0026nbsp;in scale\u0026nbsp;but in\u0026nbsp;function.\u0026nbsp;This is\u0026nbsp;especially\u0026nbsp;true for\u0026nbsp;the developed regions, where the flow of factors is more frequent\u0026nbsp;and hybrid (Zhang et al., 2022).\u0026nbsp;The\u0026nbsp;spatial restructuring of\u0026nbsp;Lin\u0026rsquo;an originated from a reform of rural residents\u0026rsquo; production and living approaches. Therefore, there is no unitary spatial model, such as the central place or the spatial network, that can precisely and comprehensively depict its town-village spatial organizations. Moreover, the strong interconnected clusters suggest that spatial interactions are not solely dictated by hierarchical relationships but are also influenced by functional interdependencies and social networks. This is consistent with the shift towards a more macro and networked view of spatial organization, as noted by\u0026nbsp;Castells (1996) and Woods (2007). The expansion of residents\u0026rsquo; daily reach found in our study is also in line with the observations by\u0026nbsp;Harvey (1973)\u0026nbsp;that technological progress leads to \u0026ldquo;time-space compression,\u0026rdquo; reducing the constraints of geographical distance. It highlights the need to incorporate technological factors into spatial analysis and policymaking. Spatial planning should focus on the cluster characteristics in networks - integrate towns and villages by the three major functions of living, production, and services into functional clusters.\u003c/p\u003e\n\u003cp\u003eThe second point concerns the human-centered perspective and the value of human flow in re-depicting the rural spatial structure. The functional connection is reflected in human mobility. The logic of this lies in that various internal and external factors drive people\u0026rsquo;s movements. In turn, people and various flow elements such as capital, labor, information, and social relations they \u0026ldquo;carry,\u0026rdquo; reshaping spatial structures. Our study shows that residents\u0026rsquo; travel links, both commuting and non-commuting, extend beyond traditional hierarchical boundaries, forming self-balanced clusters with strong internal connections. This highlights the importance of human behavior and mobility in shaping spatial structures.\u003c/p\u003e\n\u003cp\u003eThe relationship between people and land in rural areas has long been the core issue studied. However, top-down town and village planning in China is often oriented to arranging land functions and town-village hierarchies, with insufficient consideration for the actual land \u0026ldquo;users\u0026rdquo; and the fundamental changes in spatial relationships. Entering into the people-centered New Urbanization process, meeting people\u0026rsquo;s needs is the premise of spatial configuration. How people \u0026ldquo;use\u0026rdquo; space rather than the space (land) itself is what calls for the most attention. In the case of Lin\u0026rsquo;an, most rural residents transferred their working and living ways while continuing to live in their rural houses. Accordingly, the towns and villages areas did reshape to accommodate their new demands, which were mainly observed in the central towns, county-level cities and even beyond. For some residents who still kept traditional rural farming life, the policies and rural planning guaranteed basic facilities and infrastructure to ensure their daily work and living. By prioritizing people\u0026rsquo;s daily needs, planners can better accommodate the lived experiences and requirements of the population, leading to more effective and sustainable spatial planning outcomes.\u003c/p\u003e\n\u003cp\u003eIn summary, Lin\u0026rsquo;an is a glimpse of the towns and villages that are economically developed, highly accessible, and working-living modernized in China. The rural area landscape becomes complex and cannot be summarized as restructured or not restructured. This study has made some advancement, perhaps on at least one side, in understanding the interplay between human activities and changes in the rural spatial organization. The technical approach promoted can better accommodate this hybridity and dynamism and help promote sustainable spatial development.\u003c/p\u003e"},{"header":"7 Conclusion","content":"\u003cp\u003eThis study investigates the spatial restructuring of town-village areas in developed regions of China, using the Lin\u0026rsquo;an District of Hangzhou as a case. By analyzing residents' travel links derived from mobile phone signaling data and combining them with questionnaire surveys and field research, we draw the following conclusions.\u003c/p\u003e \u003cp\u003e1) The spatial structure of the town-village area exhibits a combination of hierarchical and network patterns. While the \u0026ldquo;central place\u0026rdquo; model still dominates, with central town centers forming radial connections to surrounding villages, some localized networked structures have emerged, characterized by horizontal links between villages. This indicates a partial deconstruction of the traditional hierarchical model, as villages are increasingly connected to multiple centers and other villages rather than being solely dependent on a single town center.\u003c/p\u003e \u003cp\u003e2) Both commuting (home-work) and non-commuting (home-service) travel links have extended spatially, forming self-balanced clusters with strong internal links. These clusters do not strictly follow administrative boundaries, suggesting that functional connections play a more significant role in shaping rural spatial structure than administrative divisions. The commuting network forms 12 smaller and more equitable-sized clusters, while the non-commuting network forms 10 clusters with greater variation in size, indicating different patterns of work-residence balance and service access.\u003c/p\u003e \u003cp\u003e3) The linkages between rural and urban areas have strengthened, following the law of distance decay. Rural residents living closer to urban areas rely more on cities for jobs and higher-level services, forming regular daily travel patterns across urban-rural boundaries. However, this relationship is not linear, with a logarithmic decay trend observed for commuting links, indicating that the influence of distance diminishes as it increases. The proportion of rural-urban commuting and non-commuting links is significant, highlighting the increasing urban-rural integration.\u003c/p\u003e \u003cp\u003e4) The drivers of town-village spatial restructuring are multifaceted. \u0026ldquo;Time-space compression\u0026rdquo; led by technological advancements has enabled residents to travel longer distances and establish remote communication, weakening the constraints of natural conditions and making networked connections possible. Industrial restructuring and diversification have transformed local labor markets, creating new employment opportunities and changing work-residence relationships. Policy interventions aimed at concentrating built-up space, such as relocating industries to parks and consolidating public service facilities, have directly influenced residents\u0026rsquo; travel patterns.\u003c/p\u003e \u003cp\u003eThis study makes several contributions to the understanding of town-village spatial restructuring in the context of socio-economic transformation. Firstly, it provides a novel methodological approach by utilizing mobile phone signaling data to quantify and map resident travel links, revealing the underlying spatial networks and clusters. This method offers a more detailed and dynamic view of spatial structure compared to traditional approaches. Secondly, the combination of quantitative data analysis with qualitative field research and questionnaire surveys allows for a comprehensive exploration of the drivers and mechanisms behind spatial changes. This integrated approach provides a deeper understanding of the complex interactions between human activities and spatial organization. Lastly, the findings offer valuable insights for town-village spatial planning and policy-making, highlighting the need to consider actual functional relationships and resident behavior in addition to physical land use arrangements.\u003c/p\u003e \u003cp\u003eHowever, this study has some limitations. One crucial concern is that the mobile phone signaling data cannot fully capture the complex travel patterns of rural residents in China. These patterns, influenced by multiple, part-time, and informal employment, and tied to household roles, lack fixed or regular space-time commuting characteristics - men typically engage in agricultural or industrial work, while women manage household tasks and service-oriented activities. The current data cannot fully capture the underlying purposes of these travel patterns. Additionally, the questionnaire data has a relatively small number of responses and limited geographic scope, which may affect the representativeness and generalizability of causal mining. Future research could focus on validating and refining the methods with data of larger coverage and more cases to assess their applicability and robustness. The development of models that incorporate the diverse factors influencing spatial restructuring would also be beneficial. The dynamic nature of space suggests that continuous monitoring and adaptive planning approaches will be essential for achieving balanced and sustainable urban-rural development in China and beyond under the transformation context.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data that has been used is confidential.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo funding to declare.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors would like to express special thanks to Xinyi Niu of Tongji University for data support. Many thanks would also like to give to the members who participated in the survey of Lin'an Towns and Villages for their hard work, and the four town governments of Yuqian, Changhua, Tianmushan, and Taihuyuan who provided great assistance for our survey.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eConceptualization, LT and YC; methodology, LT; software, LT; visualization, LT; formal analysis, LT; investigation, LT and YC; resources, YC; data curation, YC; writing—original draft preparation, LT and YC; writing—review and editing, LT and YC; supervision, YC; project administration, YC.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eAll procedures performed in this study adhered to the ethical standards outlined in the Declaration of Helsinki and its subsequent amendments. Ethical approval was granted on July 1, 2021, by the Institution Review Board of Department of Urban Planning, College of Architecture and Urban Planning, Tongji University. All research activities complied with applicable guidelines and regulations for studies involving human participants. The approved project was titled “Survey on Travelling Activities of Town and Village Residents in Lin’an District and Urban Residents in Hangzhou City.” The review documents included the Ethics Review Approval Form and Investigator’s Manual.\u003c/p\u003e\n\u003cp\u003eInformed consent\u003c/p\u003e\n\u003cp\u003eDuring the first questionnaire survey conducted from 12\u0026nbsp;July\u0026nbsp;to 20\u0026nbsp;July, 2021, trained survey assistants distributed written informed consent forms to all respondents, which were signed by each participant on a voluntary basis. During the second online questionnaire survey conducted from\u0026nbsp;27 July to 31 July, 2021, the questionnaire was set up to inform participants of the research purpose, and that “submitting answers” was considered informed consent. The two surveys did not involve vulnerable groups or minors. All participants were assured that their anonymity and confidentiality would be strictly protected, and all data would be used solely for academic research purposes. All participants were fully informed about the research objectives, procedures, data usage, potential risks, and their rights. Participants could exit at any time during the questionnaire-filling process.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAhas R, Aasa A, Silm S, Tiru M (2010) Daily rhythms of suburban commuters\u0026rsquo; movements in the Tallinn metropolitan area: Case study with mobile positioning data. Transportation Research Part C: Emerging Technologies 18(1): 45-54\u003c/li\u003e\n \u003cli\u003eAlderson A, Beckfield J (2004) Power and Position in the World City System. American Journal of Sociology 109: 811-851\u003c/li\u003e\n \u003cli\u003eAsakura Y, Iryo T (2007) Analysis of tourist behaviour based on the tracking data collected using a mobile communication instrument. Transportation Research Part A: Policy and Practice 41(7): 684-690\u003c/li\u003e\n \u003cli\u003eBlondel V D, Guillaume J-L, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008(10)\u003c/li\u003e\n \u003cli\u003eCao Y, Li G, Cao Y, Wang J, Fang X, Zhou L, Liu Y (2020) Distinct types of restructuring scenarios for rural settlements in a heterogeneous rural landscape: Application of a clustering approach and ecological niche modeling. Habitat International 104\u003c/li\u003e\n \u003cli\u003eCastells M (1996) The rise of the network society. Blackwell Publishers, \u0026nbsp;Malden\u003c/li\u003e\n \u003cli\u003eChai Y, Ta N, Ma J (2016) The socio-spatial dimension of behavior analysis: Frontiers and progress in Chinese behavioral geography. Journal of Geographical Sciences 26(8): 1243-1260\u003c/li\u003e\n \u003cli\u003eChai Y, Zhou S, Cai Y, Zhang Y, Wu L, Weng G (2007) Recent Progress of Human Geography in China: Retrospect and Prospect. Japanese Journal of Human Geography 59: 2-22\u003c/li\u003e\n \u003cli\u003eChen J, Gao M, Fu Y, Ruan C (2020) Research on the New Development Path of Towns and Villages Based on the Concept of Urban-Rural Integration: Taking Chengdu Urban-Rural Integration Unit as an Example. City Planning Review 44(8): 120-128\u003c/li\u003e\n \u003cli\u003eChristaller W, Baskin C W (1966) Central places in southern Germany. Prentice-Hall, \u0026nbsp; Englewood Cliffs, N.J.,\u003c/li\u003e\n \u003cli\u003eDerudder B, Witlox F (2009) The impact of progressive liberalization on the spatiality of airline networks: a measurement framework based on the assessment of hierarchical differentiation. Journal of Transport Geography 17(4): 276-284\u003c/li\u003e\n \u003cli\u003eEagle N, de Montjoye Y-A, Bettencourt L M A (2009). Community Computing: Comparisons between Rural and Urban Societies Using Mobile Phone Data. 2009 International Conference on Computational Science and Engineering\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003e144-150\u003c/li\u003e\n \u003cli\u003eFink M, Lang R, Harms R (2013) Local responses to global technological change \u0026mdash; Contrasting restructuring practices in two rural communities in Austria. Technological Forecasting and Social Change 80(2): 243-252\u003c/li\u003e\n \u003cli\u003eFriedmann J (1966) Regional development policy. M.I.T. Press, \u0026nbsp;Cambridge\u003c/li\u003e\n \u003cli\u003eFu Y, Wang D (2021) Living space structural pattern of typical residential areas in Shanghai. Progress in Geography 40(4): 565-579\u003c/li\u003e\n \u003cli\u003eGao X, Liu L, Ou D, Yuwu H (2023) Using mobile phone data to probe the mobility‐related well‐being of rural residents: A case study of Chengdu, China. Regional Science Policy \u0026amp; Practice 15(9): 1893-1907\u003c/li\u003e\n \u003cli\u003eGuo X, Yu B, Zhuo R, Zeng J, Yan M (2020) Change of farming households\u0026apos; employment and influencing factors on the Jianghan Plain. Progress in Geography 39(12): 2094-2104\u003c/li\u003e\n \u003cli\u003eH\u0026auml;gerstraand T (1970) What About People in Regional Science? Papers in Regional Science 24(1): 7-24\u003c/li\u003e\n \u003cli\u003eHarvey D (1973) Social Justice and the City. Edward Arnold, \u0026nbsp;London\u003c/li\u003e\n \u003cli\u003eHeley J, Jones L (2012) Relational rurals: Some thoughts on relating things and theory in rural studies. Journal of Rural Studies 28(3): 208-217\u003c/li\u003e\n \u003cli\u003eHoggar K, Paniagua A (2001) What rural restructuring? Journal of Rural Studies 17(1): 41-62\u003c/li\u003e\n \u003cli\u003eKrugman P (1991) Increasing Returns and Economic Geography. Journal of Political Economy 99(3): 483-499\u003c/li\u003e\n \u003cli\u003eLi H, Lai W, Xiao W, Gao L (2023) Practical Directions, Theoretical Logic, and Methodology of Rural Contiguous Planning: An Analysis in the \u0026quot;Function-Network\u0026quot; Perspective. Urban Planning Forum(3): 47-55\u003c/li\u003e\n \u003cli\u003eLiu L, Gao X, Zhuang J, Wu W, Yang B, Cheng W, Xiao P, Yao X, Deng O (2020) Evaluating the lifestyle impact of China\u0026rsquo;s rural housing land consolidation with locational big data: A study of Chengdu. Land Use Policy 96: 1-9\u003c/li\u003e\n \u003cli\u003eLiu Y, Zang Y, Yang Y (2020) China\u0026rsquo;s rural revitalization and development: Theory, technology and management. Journal of Geographical Sciences 30(12): 1923-1942\u003c/li\u003e\n \u003cli\u003eLong H, Liu Y (2016) Rural restructuring in China. Journal of Rural Studies 47: 387-391\u003c/li\u003e\n \u003cli\u003eMassey D (1999) Space‐Time, \u0026apos;Science\u0026apos; and the Relationship between Physical Geography and Human Geography. Transactions of the Institute of British Geographers 24(3): 261-276\u003c/li\u003e\n \u003cli\u003eNiu X, Li Z (2022) Spatial Organization of Shanghai Suburb Town Circles Based on the Characteristics of Resident Activities. Shanghai Urban Planning Review(1): 80-86\u003c/li\u003e\n \u003cli\u003eQian J, He S, Smith D (2025) Rural-urban interfaces and changing forms of relational and planetary rurality. Journal of Rural Studies 116\u003c/li\u003e\n \u003cli\u003eTang S, Wang F, Ye H, Lu X (2024) Rural Clustering Development Strategies Based on Symbiosis Theory, Guangzhou. Planners(4): 55-63\u003c/li\u003e\n \u003cli\u003eTaylor P, Derudder B, Hoyler M, Ni P, Witlox F (2013) City-Dyad Analyses of China\u0026rsquo;s Integration into the World City Network. Urban Studies 51(5): 868-882\u003c/li\u003e\n \u003cli\u003eTian G, Qiao Z, Gao X (2014) Rural settlement land dynamic modes and policy implications in Beijing metropolitan region, China. Habitat International 44: 237-246\u003c/li\u003e\n \u003cli\u003eUllman E L (1957) American Commodity Flow. University of Washington Press, \u0026nbsp; Seattle\u003c/li\u003e\n \u003cli\u003eVerhetsel A, Beckers J, De Meyere M (2018) Assessing Daily Urban Systems: A Heterogeneous Commuting Network Approach. Networks and Spatial Economics 18(3): 633-656\u003c/li\u003e\n \u003cli\u003eWang C, Zhou T, Ren M (2023) Driving spatial network connections in rural settlements_The role of e-commerce. Applied Geography 159\u003c/li\u003e\n \u003cli\u003eWang D, Xie D, Wang C, Yin Z (2021) Regularity and predictability of individual spatiotemporal behavior: A case study of residents working day activities in Shanghai. Progress in Geography 40(03): 433-440\u003c/li\u003e\n \u003cli\u003eWang D, Xie D, Wang C, Yin Z (2021) Regularity and predictability of individual spatiotemporal behavior: A case study of residents working day activities in Shanghai. Progress in Geography 40(3): 433-440\u003c/li\u003e\n \u003cli\u003eWang J, He S (2014) From Tree Structure to Interactive Network: A Preliminary Study on Transit-Oriented Spatial Development Patterns of Village-Town Communities. China City Planning Review 23(4): 41-47\u003c/li\u003e\n \u003cli\u003eWoods M (2007) Engaging the global countryside: globalization, hybridity and the reconstitution of rural place. Progress in Human Geography 31(4): 485-507\u003c/li\u003e\n \u003cli\u003eWoods M (2009) Rural geography: blurring boundaries and making connections. Progress in Human Geography 33(6): 849-858\u003c/li\u003e\n \u003cli\u003eWoods M (2012) New directions in rural studies? Journal of Rural Studies 28(1): 1-4\u003c/li\u003e\n \u003cli\u003eWu J, Luo Z, Qian J (2021) Research on the Driving Mechanism of Human Urbanization in the Internet Age: Based on the Empirical Evidence of the Individual Life Course of the Taobao Village Elite. Shanghai Urban Planning Review(02): 1-7\u003c/li\u003e\n \u003cli\u003eWu M, Zhang Q F, Donaldson J (2024) Post-productivism and rural revitalization in China: Drivers and outcomes. Journal of Rural Studies 110\u003c/li\u003e\n \u003cli\u003eXiong W (2021) Rural Functional Unit Planning of Non-concentrated Construction Area, Wuhan. Planners(3): 78-84\u003c/li\u003e\n \u003cli\u003eYang R, Xu Q, Long H (2016) Spatial distribution characteristics and optimized reconstruction analysis of China\u0026rsquo;s rural settlements during the process of rapid urbanization. Journal of Rural Studies 47: 413-424\u003c/li\u003e\n \u003cli\u003eYuan X, Wang X (2021) Exploration of the Development Path of Rural Groups in the Early-Developing Regions: A Case Study of Rural Group around Nanqing Lake. Modern Urban Research(12): 6-11\u003c/li\u003e\n \u003cli\u003eZhang R, Li H, Yuan Y (2022) Analyzing space-time evolution of rural transition in a rapidly urbanizing region: A case study of Suzhou, China. Journal of Geographical Sciences 32(7): 1343-1356\u003c/li\u003e\n \u003cli\u003eZhao M, Xu Y (2019) Exploring the Spatial Network of Rural and Urban Settlements through the Lens of Mobile Phone Signaling Data: A Case Study of Sanxiang Town in Zhongshan. Shanghai Urban Planning Review(6): 38-45\u003c/li\u003e\n \u003cli\u003eZhao W (2009) Zhejiang Pattern: A Multifold Transitional Way of the Chinese Regional Economies. Zhejiang Social Sciences(2): 22-31\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"town-village spatial structure, spatial networks, resident travel links, mobile phone signaling data, Rural China","lastPublishedDoi":"10.21203/rs.3.rs-5733130/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5733130/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe organization of town-village space in developed regionsof China is undergoing profound restructuring, which has resulted in fundamental changes in the daily travel patterns of rural residents. However, current studies often focus on the static space itself, neglecting the dynamic interactions and functional shifts driven by the “users” of space. This study fills the gap by analyzing residents’ inter-village commuting and non-commuting travel links using mobile phone signaling data, combined with field research and questionnaire surveys. The findings reveal that the town-village spatial structure exhibits a combination of hierarchical and network patterns. First, the traditional “central place” model remains dominant, with central town centers forming radial connections to surrounding villages. However, localized networked structures have emerged, characterized by horizontal links between villages. Second, both commuting and non-commuting travel links have extended spatially, forming self-balanced clusters with strong internal connections that do not strictly follow administrative boundaries. The linkages between rural and urban areas have also strengthened, following a logarithmic distance decay trend. Finally, the study highlights that technological advancements, industrial upgrading and diversification, and policy interventions are the main drivers of spatial restructuring. The findings provide valuable insights for town-village spatial planning and policy-making, emphasizing the need to consider actual functional relationships and resident behavior. It is important for rural areas in China and beyond in the context of rural transition.\u003c/p\u003e","manuscriptTitle":"Town-village Spatial Restructuring in Developed Regions of China from the Perspective of Resident Travel: A Case of Lin'an District, Hangzhou","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 09:30:08","doi":"10.21203/rs.3.rs-5733130/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-13T15:01:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-13T15:01:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-27T09:02:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9093824565985034498779661407454631601","date":"2025-04-27T08:55:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-27T05:40:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170080065449968231137150219666401105439","date":"2025-04-27T05:31:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-27T03:40:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-14T07:32:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-04-04T13:57:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"84747e93-b24b-4bd8-9faf-fa03161e3029","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47737224,"name":"Humanities/Complex networks"},{"id":47737225,"name":"Social science/Geography"},{"id":47737226,"name":"Social science/Science technology and society"}],"tags":[],"updatedAt":"2025-06-23T15:58:58+00:00","versionOfRecord":{"articleIdentity":"rs-5733130","link":"https://doi.org/10.1057/s41599-025-05136-9","journal":{"identity":"humanities-and-social-sciences-communications","isVorOnly":false,"title":"Humanities and Social Sciences Communications"},"publishedOn":"2025-06-16 15:57:08","publishedOnDateReadable":"June 16th, 2025"},"versionCreatedAt":"2025-05-06 09:30:08","video":"","vorDoi":"10.1057/s41599-025-05136-9","vorDoiUrl":"https://doi.org/10.1057/s41599-025-05136-9","workflowStages":[]},"version":"v1","identity":"rs-5733130","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-5733130","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}