Introduction

Cultural heritage encompasses all the material and spiritual wealth created by a nation, a state or a particular group, reflecting the historical trajectories of regional cooperation and exchange to some extent1,2. Research on cultural heritage supports its protection, inheritance and modernization. The city of Ningbo in Zhejiang province, where the Ningbo Section of the Grand Canal of China is located, has fostered diverse cultural heritage based on its unique natural environment and cultural context, including ACH, MFCH, canal cultural heritage (CCH), and MTCH. In this study, ACH reflects the origins of rice cultivation and the development of agrarian civilization. MFCH represents cultural traditions centered on maritime fishing, encompassing production, livelihood, and associated belief systems along the coast. CCH denotes the heritage associated with canal systems, including water management projects, transportation facilities, and related cultural practices, embodying the interaction between human activities and water conservancy. MTCH highlights cultural heritage shaped by maritime trade, characterized by external commerce, religious transmission, and cross-cultural exchanges along the Maritime Silk Road. These four types of cultural heritage are closely interconnected in regional development: (1) In the Neolithic period, dynamic coastal changes intensified the integration of primitive maritime fishing culture with agrarian culture, leading to the formation of stable marine communities after the coastal environment stabilized. (2) Since the Tang and Song Dynasties, Ningbo has leveraged its strategic location at the intersection of river and sea routes to facilitate domestic and international trade and cultural exchange. The Ningbo Section of the Grand Canal of China was connected to Mingzhou Port (present named Ningbo Port), making Ningbo a critical hub for the export of Yue Kiln celadon. Simultaneously, it enabled the eastward dissemination of Buddhist culture, an important component of maritime trade culture, with Tiantong Temple and Ashoka Temple as key nodes, forming a distinct network of religious and cultural exchange. Therefore, constructing heritage corridors as a spatial organizational component within the broader multicultural heritage connection system can promote the integrated conservation and sustainable development of cultural heritage in the region.

The concept of heritage corridor, first introduced by the United States for the regional protection of canal heritage, is primarily characterized by environmental improvement and tourism development3. Specifically, it may refer either to an existing linear cultural heritage, such as a natural river valley, or to a significant linear route connecting discrete cultural heritage sites4,5,6. In the early 21st century, after the concept was introduced to China, some scholars pointed out that the domestic cultural heritage protection system lacked regulations targeting regional heritage, resulting in inadequate protection of canals. Consequently, they advocated constructing heritage corridor for the protection and management of linear cultural heritage7. Regarding the form of cultural resources, the Grand Canal of China differs from canals that are remnants of industrial civilization, such as the Illinois & Michigan Canal and the Erie Canal, as it is closely associated with ancient hydraulic engineering and the commercial transportation networks along its route. In terms of governance, international practices emphasize broad public participation by non-profit organizations, tourists, community members, volunteers, and national institutions8,9,10; whereas heritage corridor construction along the Grand Canal of China places greater emphasis on government leadership, promoting the revival of heritage areas through top-down administrative measures11. Although China and other countries differ in organizational models and cultural expression in corridor construction, both face the common challenge of achieving systematic connections between cultural resources and improving the efficiency of spatial coordination and protection. Traditional governance approaches centered on policy and organizational guidance have integration advantages but also exhibit limitations, such as insufficient spatial connectivity. With the development of spatial planning and landscape ecology, heritage corridor construction has gradually shifted from a purely institutional governance model to an approach that integrates spatial connectivity as a core component of the heritage connection system.

Research on heritage corridor construction abroad is relatively scarce. Existing studies primarily focus on heritage protection and integration12, heritage tourism and sustainable marketing along corridors13,14, and the environmental sustainability of corridor planning15, with a strong emphasis on qualitative analysis. In contrast, domestic research primarily leverages existing linear spaces, such as rivers, roads, city walls, and cultural routes. Spatial analysis methods are employed to integrate cultural resources along these routes and construct heritage corridors. For example, Li constructed the heritage corridor network for intangible cultural heritages in the Yellow River basin from a systematic and holistic perspective, proposing a method and framework for the systematic protection of intangible cultural heritage16. Yue developed several north-south main corridors and branch corridors along the Shu Road, determining corridor grades based on spatial syntax17. Lin studied the spatial structure of intangible cultural heritages along the Great Wall and conducted heritage corridor construction18. However, research on the construction of canal heritage corridor remains limited, primarily addressing canal heritage tourism and sustainable development19,20, canal heritage protection21, and the spatio-temporal distribution and influencing factors of canal heritage22,23,24,25. This study aims to construct the spatial pattern of heritage corridors along the Grand Canal of China, which serve as spatial organizational components within the heritage connection system, forming the spatial framework for coordinated conservation.

In terms of corridor path construction, ecological corridor identification practices provide technical support for simulating the spatial flow of cultural elements. The current ecological corridor construction mainly uses the MCR model, which calculates the cost distance between ecological sources to obtain the least cost path, thereby determining the optimal route for species migration26. However, the MCR approach has limitations, including operational complexity and its inability to assess the relative importance of corridors27. Circuit theory offers a more efficient alternative by simulating current flow through circuits to identify high-quality corridors, without the need to generate least cost paths for each heritage site. Therefore, GIS spatial analysis and circuit theory are applied to identify multicultural heritage corridors along the Grand Canal of China.

Push-pull theory was initially applied to population migration research to reveal the key drivers behind migration decisions. Although traditional push-pull theory fails to fully reflect the complex interactions between push and pull factors and does not directly consider spatial distance as a barrier, it provides an important analytical framework for understanding mobility dynamics. Since the 1960s, scholars have attempted to quantify population migration using model-based prediction methods to simulate flows at different spatial scales. Among them, the gravity model, proposed by Ravenstein in 188528, analogizes migration flows to the force of gravity: the scale of flows between two places is proportional to population size and inversely proportional to spatial distance29. While it accounts for distance decay, it does not adequately reflect the relative attraction or repulsion of different regions. To further explore the mechanisms driving cross-regional cultural flows, this study integrates the spatial pattern of the heritage corridor network with traditional push–pull theory and migration prediction model to develop an improved push–pull framework. This framework identifies the push-pull factors of cultural origins and incorporates distance impedance, thereby providing an explanatory perspective on cultural flows in heterogeneous landscapes. It enables the analysis of the mechanisms and processes of cultural transmission and multicultural interaction, while also offering theoretical and methodological support for the integrated analysis and planning of multicultural heritage connection in the Ningbo Section of the Grand Canal of China.

The main content of this research can be summarized as follows: (1) Identifying the spatial distribution of ACH, MFCH and MTCH, and extracting the origins of agrarian culture, maritime fishing culture and maritime trade culture using kernel density grading. This study then generates multicultural origins through spatial superposition. (2) Developing an evaluation index system for agrarian culture, maritime fishing culture and maritime trade culture, calculating their respective comprehensive resistance surfaces and multicultural comprehensive resistance surface. Based on these, potential multicultural heritage corridors and critical areas are identified using circuit theory. By comparing with the routes of the Ningbo Section of the Grand Canal of China, the spatial pattern of multicultural heritage corridors is optimized to form a coherent heritage connection system. (3) Drawing on the spatial pattern of corridors, the improved push-pull framework analyzes the transitions and integration among primary cultural threads in the region, thereby exploring the dynamic evolution of the cultural heritage and the multicultural interactions.

Methods

Study area

This research designates the Ningbo Section of the Grand Canal of China as the study area. The Grand Canal of China spans 27 cities across 8 provinces, playing a significant role in regional economic development and cultural exchange by linking areas along the canal and connecting them to the Maritime Silk Road. The Ningbo Section of the Grand Canal of China, located in Ningbo city, Zhejiang province, is not only the southernmost outlet to the sea of the Grand Canal but also a crucial port of the Maritime Silk Road. Situated in eastern Zhejiang, Ningbo borders the Zhoushan Islands to the east and Hangzhou Bay to the north, enjoying a favorable geographical location. The terrain slopes from high southwest to low northeast, dominated by plains and low hills. Relying on Ningbo Port and the Grand Canal, Ningbo has been a vital port for transshipment and maritime trade along the southeast coast. Furthermore, Ningbo has long been an important center for cultural exchange in East Asia, serving as the focal point for the eastward transmission of Chinese Chan Buddhism during the Song and Yuan Dynasties via the Maritime Silk Road. With human activities dating back over 8000 years to the Jingtoushan Site, the region has fostered rich agrarian culture and maritime fishing culture. Its unique geographical environment and cultural context have led to the formation of a diverse array of cultural resources, offering significant potential for heritage preservation and integrated development.

Data sources

The data and their sources are as follows: (1) Cultural heritage data: ACH, MFCH and MTCH were obtained from the national, provincial, municipal and county-level cultural relic protection units, as well as from the respective lists of cultural relic protection sites and intangible cultural heritage inventories (Table S1). Based on the definitions of the three categories of cultural heritage, a total of 110 cultural heritage resources were identified. (2) Elevation data: Acquired from the Geospatial Data Cloud Platform (http://www.gscloud.cn/) with a spatial resolution of 30 m. (3) River system and road network data: Obtained from Open Street Map (www.openstreetmap.org) for 2024. (4) County boundary data: Obtained from the National Geographic Information Public Service Platform (http://www.tianditu.gov.cn), updated to May 2024. (5) Land use data: Retrieved from Esri’s ArcGIS Living Atlas of the World (https://livingatlas.arcgis.com) with a spatial resolution of 10 m. (6) Shoreline data: Collected from the National Oceanic and Atmospheric Administration (NOAA) (http://www.ngdc.noaa.gov) for the year 2024.

This study identifies four primary cultural threads based on historical documents: agrarian culture, maritime fishing culture, canal culture and maritime trade culture. Given the linear distribution of CCH along the canal, the cultural heritage data were systematically collected for three cultural routes: agrarian culture, maritime fishing culture, and maritime trade culture. Geographic coordinates for ACH, MFCH and MTCH were obtained from Baidu Maps and converted to actual coordinates. The routes of the Ningbo Section of the Grand Canal were extracted from the river system, and the slope data was obtained from slope analysis of the elevation data. Vector data for elevation, slope, river system, road, land use, coastline, and the routes of the Ningbo Section of the Grand Canal were used as resistance factors to construct evaluation index systems for the three cultures.

Research methods

This study employs GIS spatial analysis and circuit theory to construct the spatial pattern of multicultural heritage corridors, and proposes an improved push-pull framework based on traditional push-pull theory and migration model. The research aims to reveal the dynamic evolution of cultural heritage and multicultural interactions by analyzing the transitions and integration among primary cultural threads in the region. The innovations and research framework are illustrated in the figure below (Figs. 1, 2).

Fig. 1: Study area.
figure 1

a The main map illustrates the Ningbo Section of the Grand Canal of China. Elevation is shown with a gradient from light green (low, 0 m) to dark green (high, 958 m), and the county boundary is outlined in gray lines. Red triangles denote agrarian cultural heritage (ACH), orange pentagons denote maritime fishing cultural heritage (MFCH), and blue circles denote maritime trade cultural heritage (MTCH). The Grand Canal of China is indicated with blue lines, with the Ningbo Section specifically highlighted in light blue. b The inset map shows the location of Zhejiang province within China. Open rectangles indicate the boundaries of other provinces, the Grand Canal of China is marked in blue, and Beijing is identified with a red star. The small inset in the lower right displays the outline of islands in the South China Sea. c The inset map highlights Zhejiang province, with the study area shown in red and surrounding cities within Zhejiang displayed in light green (drawn by authors).

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Fig. 2
figure 2

Research innovations and technological route (drawn by authors).

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The identification of multicultural origins

Cultural origin, as the source of cultural transmission30, forms the foundation for constructing heritage corridors. In this study, kernel density analysis was conducted on ACH, MFCH and MTCH to identify their respective cultural origins. The analysis was conducted with the output area density unit set to square kilometers, and the pixel size was set to 250 m for ACH, MFCH, and MTCH. To fully capture their spatial distribution, the search radii were set to 8000 m, 14,000 m, and 7500 m, respectively. The choice of kernel density bandwidth is critical, as an excessively large bandwidth may obscure local spatial variations, whereas an excessively small one may generate noisy outputs. The analysis results were divided into five levels using the natural breakpoint method, areas with a density of third-level or higher were defined as the cultural origins for each type, and their spatial forms were preserved through spatial superposition to identify the multicultural origins.

This method avoids using cultural heritage sites as the origin of a particular culture, addressing the issue of their small scale31. Kernel density analysis generates a continuous three-dimensional surface from two-dimensional discrete points using a kernel density estimation function, calculating the density of event points within a surrounding neighborhood. This method reflects the aggregation or dispersion characteristics of the point clusters30. There is a positive correlation between cultural heritage site density and event probability, with denser areas indicating a higher likelihood. The formula is:

$$f(x) = \frac{1}{n h} \sum_{i=1}^{n} k\!\left( \frac{x - x_i}{h} \right)$$
(1)

In the formula, \(k\!\left(\frac{x - x_i}{h}\right)\) denotes the kernel function, \(h\) is the search radius and \(h\) > 0; \(\left(x - x_i\right)\) denotes the distance from the estimated point \(x\) to the cultural heritage point \(x_i\), and \(n\) denotes the cultural heritage sample size.

The construction of comprehensive resistance surfaces and multicultural heritage corridor spatial pattern

The cultural comprehensive resistance surface describes the difficulty of movement for cultural experiencers, reflecting the impact of landscape heterogeneity on cultural transmission. In this study, resistance factors for agrarian culture, maritime fishing culture, and maritime trade culture were identified based on spatial environmental suitability—which includes natural and socio-economic dimensions—and historical-cultural value, with higher scores indicating greater resistance to cultural element flows. Factor weights for each resistance factor were determined using expert scoring, which involved constructing judgment matrices, calculating maximum eigenvalues, and performing consistency checks (CI, CR < 0.1; Table S2). The resulting weights are listed in Table S3, and the resistance level of each factor was subsequently classified (Table S4). Due to incomplete archaeological data, the temporal span of ACH could not be determined, while MFCH and MTCH periods were inferred from historical documents. Accordingly, historical-cultural value was incorporated for MFCH and MTCH, considering heritage age (pre-Tang = 1, Tang–Song = 2, Yuan–Ming = 3, Qing–Republic = 4, modern era = 5) and protection level (national = 1, provincial = 2, municipal = 3, county = 4, unlisted = 5), with higher scores indicating greater resistance. IDW interpolation generated resistance surfaces for heritage age and protection level, classified into five levels using the natural breakpoint method. The comprehensive resistance surfaces of all three cultures were then calculated according to their weights and classified into low, medium, and high resistance. In the absence of direct quantitative data, the number and spatial density of heritage resources served as proxies for historical activity and continuity, with ACH, MFCH, and MTCH proportions estimated at 21%, 51%, and 28% to construct a multicultural comprehensive resistance surface.

Using circuit theory, multicultural origins and multicultural comprehensive resistance surface were used to identify potential heritage corridors and critical areas, which were then compared with the Ningbo Section of the Grand Canal to construct the spatial pattern of multicultural heritage corridors. Circuit theory was applied to identify potential heritage corridors, where higher cumulative current values indicate greater connectivity and higher likelihood of cultural element movement32. The process of constructing the spatial pattern of corridors involves: (1) Calculating centrality of multicultural origins using Centrality Mapper and classifying them into three levels—first-level indicating the best centrality—using the natural breakpoint method; (2) Identifying potential multicultural heritage corridors using Build Network and Map Linkages Tool, with multicultural origins and comprehensive resistance surface as inputs; corridors were classified by flow centrality and the cost-weighted distance to least cost path length ratio (CWD/LCP_length), each divided into three levels, with higher CWD/LCP_length ratios indicating stronger resistance33. (3) Identifying critical areas within corridors using Pinchpoint Mapper, classified into three levels, with the highest level designated as the critical areas. (4) Optimizing potential corridors by comparing them with the Ningbo Section of the Grand Canal to generate the final spatial pattern of multicultural heritage corridors.

The construction of the improved push-pull framework

This study develops an improved push–pull framework integrating heritage corridor analysis, traditional push–pull theory, and migration modeling to examine the spatial flow of cultural elements. The framework construction involves: (1) calculating push and pull factors of each cultural origin; (2) incorporating distance impedance into the improved push–pull framework. It assumes that natural and socio-economic factors jointly act as push–pull forces driving population migration and cultural flow. Given the limited sample size, the framework serves as a theoretical model for exploring spatial flow patterns in combination with heritage corridor construction, rather than for high-precision prediction.

The calculation of push and pull factors of a cultural origin

Variations in indicators across cultural origins influence population mobility, reflected in the flow of cultural elements between origins. Seven indicators were selected to represent the influencing factors of cultural element flow: terrain undulation index (x1), water network density (x2), land use type (x3), road network accessibility (x4), distance from canal routes (x5), cultural heritage density (x6), and cultural origin current flow centrality (x7). Each indicator was normalized using min-max normalization, and the mean value within each cultural origin was used as its score. Indicator weights were determined by the information entropy method. If the value of an indicator for a given cultural origin is directly proportional to its attractiveness, the coefficient is positive when calculating the pull factor. The sign of the push coefficient is determined in the same way. The weights of each indicator are shown in Table 1.

Table1 Factors influencing the flow of cultural elements and their weights
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Since each cultural origin can act as both the origin and destination of cultural element flows, push and pull factors for each origin were computed based on Table 1, applying Eqs. (2) and (3) respectively.

$$\nu(O)_i = \exp\!\left( \sum_{n=1}^{n=V} a_n \cdot x(n)_i \right)$$
(2)
$${\nu}(D)_{j} = \exp\left( \mathop{\sum}\limits_{n=1}^{n=V} {\beta}_{n} \cdot x(n)_j \right)$$
(3)

\(\nu(O)_i\) represents the push factor of cultural origin i driving cultural elements to flow outward from cultural origin i; \(\nu(D)_j\) represents the pull factor of cultural origin j, attracting cultural elements to flow toward cultural origin j. \({a}_{n}\) represents the weight of the push indicator \(x{\left(n\right)}_{i}\) of cultural origin i, and \({\beta }_{n}\) represents the weight of the pull indicator \(x{\left(n\right)}_{j}\) of cultural origin j. After normalizing and weighting the sum of each indicator, the push and pull factors of each cultural origin are calculated in exponential form.

The construction of the improved push-pull framework

In population migration simulations, migration likelihood decreases as transportation costs increase with distance. The distance impedance effect is commonly modeled as a negative exponential function34. In this study, the ratio of LcDist to EucDist is used to replace the traditional distance impedance coefficient, representing travel cost per unit distance, with higher ratios indicating greater landscape resistance. The improved distance impedance function based on circuit theory is shown in Eq. 4.

$${d}_{{ij}}={\exp}\left({D}_{{ij}}\cdot \frac{{LcDist}}{{EucDist}}\right)$$
(4)

\({d}_{{ij}}\) is the distance impedance from cultural origin i and j; \({LcDist}\) is the actual length of the least cost path between cultural origins (m), \({EucDist}\) is the Euclidean distance (m), and \({D}_{{ij}}\) is the geometric length of the least cost path (m). If the corridor crosses a more complex, high-resistance landscape unit, i.e., \({LcDist}\) > \({EucDist}\) and the growth rate accelerates with increasing distance, this indicates that the unit distance travel cost is rising.

$${C}_{{ij}}=s\cdot v{\left(O\right)}_{i}^{{a}_{1}}\cdot v{\left(D\right)}_{j}^{{a}_{2}}\cdot {d}_{{ij}}^{{a}_{3}}$$
(5)

In constructing the improved push-pull framework (Eq. 5), this study focuses on three core factors: push and pull factors between cultural origins, and landscape heterogeneity path resistance introduced in distance impedance. Although the population sizes of source and destination areas typically affect migration likelihood, due to the lack of systematic and comparable historical population data between cultural origins, population was excluded from the framework to avoid potential bias. In the Equation (5), \({{C}}_{{ij}}\) is the intensity of cultural element flow between cultural origins; \(v{(O)}_{i}\) is the push factor of cultural origin i (source area); \(v{(D)}_{j}\) is the pull factor of cultural origin j (destination); \(s\) is the elasticity coefficient; and \({a}_{1}\), \({a}_{2}\), and \({a}_{3}\) are the parameters to be estimated.

Results

Characteristics of multicultural origins

Kernel density analysis of cultural heritage sites reveals distinct spatial aggregation patterns, providing a basis for identifying cultural origins. ACH formed a high-density core in the central-northern region of the study area, accompanied by one sub-high-density core to the north and two to the south (Fig. 3a). MFCH formed a high-density core along the southeastern coastline, accompanied by four sub-high-density clusters located on the northern and southern near sides of the semi-enclosed bay and in the offshore area to the northeast. Overall, the density of MFCH decreased progressively with increasing distance from the coastline (Fig. 3b). The MTCH demonstrated strong clustering in the northern part of the semi-enclosed bay, forming high-density cores in Cixi and Sanjiangkou (the junction of Haishu, Jiangbei, and Yinzhou districts), along with three sub-high-density clusters to the east, west and southwest of Sanjiangkou (Fig. 3c).

Fig. 3: Cultural heritage kernel density analysis and multicultural origins.
figure 3

a The density of agrarian cultural heritage (ACH). b The density of maritime fishing cultural heritage (MFCH). c The density of maritime trade cultural heritage (MTCH). In all three density maps, shading from light yellow to dark blue represents increasing kernel density values, with lighter yellow indicating lower concentrations and darker blue marking the highest clustering. d Agrarian cultural origins are highlighted in light green. e Maritime fishing cultural origins are shaded in light blue. f Maritime trade cultural origins are marked in cyan blue. g Multicultural origins are differentiated by type and current flow centrality. Single-type origins are represented with areas shaded by a single diagonal line, while compound-type origins are represented with areas shaded by crossed double diagonal lines. Centrality is further classified into first-level origins (dark brown), second-level origins (orange), and third-level origins (light orange). The county boundary is outlined in gray lines (drawn by authors).

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A total of nine multicultural origins were identified, including three compound origins of agrarian-maritime trade culture, two compound origins of maritime fishing-trade culture, three single origins of maritime fishing culture, one of agrarian culture (Fig. 3g). The areas of first, second, and third-level multicultural origins accounted for 38.31%, 35.77%, and 25.92% of the total area, respectively. First-level origins are primarily located in the central region of the study area, characterized by flat terrain and a dense network of rivers and roads. Second-level origins are mainly distributed around the first-level origins. Third-level origins exhibit the greatest spatial dispersion, scattered from Cixi in the north to Xiangshan in the south.

Comprehensive resistance surfaces

Based on the evaluation indicator systems and the resistance grading (Fig. 4), both individual comprehensive resistance surfaces for the three cultures and a multicultural comprehensive resistance surface were constructed. The distribution of low, medium and high resistance area across the three cultures varies significantly, reflecting the suitability of different types of cultural activity. For agrarian culture, the low resistance area accounts for 21.87% of the region, primarily consisting of cultivated land. The medium resistance area, covering 56.46%, mainly includes bare land, pasture, and construction land. The high resistance area accounts for 21.67%, and is largely composed of forested areas (Fig. 5a). For maritime fishing culture, the low resistance area constitutes 25.56% of the region, mainly distributed in the northeastern and southeastern coastal areas, as well as in adjacent regions with dense road networks and water systems. The medium resistance area, comprising 38.99%, is predominantly located in zones with dense river and road networks near the low resistance area. The high resistance area, covering 35.45%, is mostly found in mountainous and hilly regions with poor transportation accessibility (Fig. 5b). For maritime trade culture, the low resistance area covers 20.72% of the total region and is mostly distributed along the Grand Canal, extending outward along connected river and road networks. The medium resistance area accounts for 42.65%, concentrated in the northern region where transport networks are sparse or distant from the canal. The high resistance area, comprising 36.63%, is located mainly in the western mountainous zone and southern areas where terrain barriers hinder canal connectivity (Fig. 5c).

Fig. 4: Resistance factors and resistance grading.
figure 4

a Elevation. b Slope. c Land use type. d Distance from the river. e Distance from the road. f Distance from the coastline. g Distance from the routes of the Ningbo Section of the Grand Canal of China. h Age of MFCH. i Age of MTCH. j Protection level of MFCH. k Protection level of MTCH. All panels are classified into five resistance levels. Shading from light yellow to dark blue represents increasing resistance values, where light yellow indicates the lowest resistance and dark blue indicates the highest resistance. The county boundary is outlined in gray lines (drawn by authors).

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Fig. 5: Comprehensive resistance surfaces and spatial pattern of multicultural heritage corridors.
figure 5

a Comprehensive resistance surface of agrarian culture. b Comprehensive resistance surface of maritime fishing culture. c Comprehensive resistance surface of maritime trade culture. d Multicultural comprehensive resistance surface. e Multicultural heritage corridors. f Critical areas of corridors. In all panels, the county boundary is outlined in gray lines. In a–d, shading indicates resistance levels: light yellow represents low resistance, medium green represents medium resistance, and dark blue represents high resistance. In e, multicultural heritage corridors are overlaid on the multicultural comprehensive resistance surface. Two classification schemes are shown: Based on current flow centrality values, corridors are divided into first-level (solid red lines with circles), second-level (dash–dot orange lines), and third-level (dotted light blue lines); Based on the CWD/LCP_length ratio, corridors are divided into three intervals: light blue (2.04–2.34), medium blue (2.35–2.67), and dark purple (2.68–3.04), where larger values indicate greater resistance. Cultural origins are represented as follows: single-type origins are shaded with a single diagonal line, while compound-type origins are shaded with crossed double diagonal lines. Centrality of multicultural origins is further classified into first-level (dark brown), second-level (orange), and third-level (light orange). The Ningbo Section of the Grand Canal of China is indicated with a purple line. In f, critical areas of corridors are highlighted as solid red areas (drawn by authors).

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Spatial pattern of multicultural heritage corridors

A comparison between the potential multicultural heritage corridors and the routes of the Ningbo Section of the Grand Canal resulted in the identification of 15 multicultural heritage corridors, excluding the canal routes themselves (Fig. 5e). These corridors were integrated with critical areas to construct the spatial pattern of multicultural heritage corridors. The first, second, and third-level corridors accounted for 13.33%, 40%, and 46.67% of the total number of corridors, respectively. The current flow centrality values of the first-level, second-level, and third-level heritage corridors range from 8.51 to 10.64, 5.33 to 8.5, and 2.43 to 5.32, respectively. First-level corridors (best centrality) play a crucial role in maintaining the overall connectivity of the network, forming the corridor network around cultural origin 4 by linking canal routes with both second and third-level corridors. A comparison of corridor centrality with CWD/LCP_length shows that first-level and second-level corridors correspond to moderate resistance, with ranges of 2.04-2.34, and 2.35-2.67, respectively. Second-level corridors traverse high resistance areas, suggesting a need for improved regional connectivity. The third-level heritage corridors, located in Fenghua, Ninghai, and Xiangshan, have CWD/LCP_length ranging from 2.68 to 3.04, and are connected to the corridor network centered on cultural origin 4, thereby achieving north-south connectivity in the region.

Critical areas of corridors (Fig. 5f) are narrow zones within corridors characterized by low resistance, indicating high potential for cultural flow and limited alternative pathways. Overlay analysis of corridor centrality and CWD/LCP_length reveals that these critical areas are predominantly located within third-level corridors, where CWD/LCP_length ranges from 2.68 to 3.04. Land use analysis further indicates that critical areas are dominated by construction land, forest land, and cultivated land, with construction land occupying the largest proportion. These findings suggest a high intensity of human activities in critical areas of corridors, highlighting the need to minimize anthropogenic disruptions to preserve corridor connectivity.

Discussion

First, this research focuses on the structural innovations and explanatory advantages of the improved push-pull framework. The improved push-pull framework constructed in this study is grounded in the gravity model. It inherits the traditional push-pull framework’s approach to quantifying regional push and pull factors, while introducing heterogeneous landscape path resistance to enhance model applicability. In the model fitting, the push and pull factors, together with path resistance, are incorporated as key variables. Heritage corridor current flow centrality is used as a proxy for the intensity of cultural element flow (\({C}_{{ij}}\)).

The gravity model originates from Zipf’s “P₁·P₂/D” hypothesis (Eq. 6), which posits that migration intensity is proportional to the population sizes of two regions and inversely proportional to the distance between them35. However, this model is primarily empirical and cannot fully capture complex population migration or cultural element flow dynamics. Wilson subsequently derived a theoretical expression for the gravity model based on the principle of entropy maximization (Eq. 7)36, introducing statistical physics foundations and the distance sensitivity parameter λ, which provides a robust framework for modeling spatial interactions, including population migration and commodity circulation.

$${T}_{{ij}}=k\cdot \frac{{P}_{i}\cdot {P}_{j}}{{D}_{{ij}}}$$
(6)
$${T}_{ij} = {A}_{i}\cdot {B}_{j}\cdot {O}_{i}\cdot {D}_{j}\cdot \exp(-\beta \cdot {c}_{ij})$$
(7)

On this basis, this study mainly achieves two improvements. Firstly, in constructing the distance impedance function, previous models typically used Euclidean distance, shortest flight path, or road distance to characterize spatial impedance effect37,38. Some research extended the distance term to account for population-weighted centroid distance39 or psychological barriers, and cultural barriers40; however, these approaches rarely capture the complexity of actual travel paths in heterogeneous landscapes. This study utilizes circuit theory to identify the spatial patterns of heritage corridors. The geometric length of the least cost path (LCP_length) and the ratio of the least cost path length to Euclidean distance between patches (LcDist/EucDist) are introduced to construct a distance impedance function, effectively reflecting path tortuosity and landscape resistance, and better representing the real flow of cultural elements across heterogeneous environments. Secondly, regarding the push-pull indicator system, traditional studies often rely on socio-economic variables such as employment, economy, population, education, and health to measure regional attractiveness or repulsiveness. In contrast, this study emphasizes the mobility of cultural elements and constructs an indicator system comprising seven factors, including terrain undulation, water network density, road network accessibility, and other variables, to better capture the challenges cultural elements face in traversing natural and human landscapes historically. Overall, this framework represents a structural shift from “static distance” to “dynamic transmission costs” and highlights cultural diffusion as an asymmetric process driven by push factors in source areas and modulated by path resistance. These innovations enhance the model’s explanatory power regarding the directionality and diversity of cultural transmission paths and provide an adaptive analytical framework for investigating cross-regional cultural diffusion in historical and cultural contexts.

Second, the transitions and integration among primary cultural threads under the improved framework are discussed. A least squares algorithm was performed on the improved push-pull framework, and the results are shown in Table 2. The elasticity coefficient for the push factor of cultural origin was 0.770, significantly higher than that of the destination pull factor (0.360). The adjustment coefficient for path resistance was -0.007. The overall model fit, indicated by R², was 0.07. Although the model effect was relatively poor due to the limited sample size, the parameter signs are consistent with theoretical expectations, suggesting that the flow of cultural elements is primarily driven by the push factors of the origin, while also being modulated by the pull factors of the destination and path resistance. This result demonstrates the model’s advantage in expressing cultural mechanisms.

Table 2 Regression results of the improved push-pull framework
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The formation of the spatial pattern of multicultural heritage corridors is shaped by the combined influence of push-pull and resistance factors. Along with the spatial pattern of the corridors, the improved push-pull framework is applied to analyze the transitions and integration among primary cultural threads: (1) maritime fishing culture to agrarian culture, and the continuation of coastal maritime fishing culture; (2) agrarian culture to canal culture; and (3) canal culture to maritime trade culture.

During the early to middle phase of the Middle Holocene, a key transition unfolded from maritime fishing to agrarian lifeways. Following the later stabilization and retreat of the coastline, stable maritime fishing communities developed in coastal regions. Marine fishery activities are concentrated along the coastal zones (cultural origins 4, 6, 7, 8, and 9), with particularly high-density cluster in the southern part of Xiangshan (cultural origin 9). However, evidence of systematic marine resource utilization can be traced back to the Jingtoushan Site (8300–7800 years ago, cultural origin 2). As the coastline in Xiangshan stabilized, natural harbors such as Shipu Port and proximity to rich East China Sea fishing grounds enabled the development of a complex maritime fishing culture, which exhibits distinct spatial aggregation. Agrarian culture activities are primarily distributed in cultural origins 1, 2, 3, and 5. The high-density concentration of ACH in the Yao River Valley Plain (cultural origin 2) resulted from sea-level retreat and mid-Holocene climate change.

The interaction between maritime fishing culture and agrarian culture is manifested in two main aspects. First, it was reflected in the transformation and integration of primitive maritime fishing culture, as exemplified by the Jingtoushan Site, with emerging agrarian practices. This first aspect of cultural interplay was spatially supported by second-level corridors centered on the Yao River Basin, where the connections between cultural origins 1–2, 2–3, and 3–5 exhibited relatively low CWD/LCP_length values, indicating weak path resistance. Second, the development and consolidation of mature maritime fishing culture occured in coastal areas such as Xiangshan after the stabilization of the coastal environment. In terms of cultural dissemination, the corridor connecting cultural origins 4 and 7 exhibits relatively low resistance, creating a convenient pathway for the flow of maritime cultural elements between these areas.

During the mid-Holocene, the ancient Ningbo Bay gradually evolved from a tidal zone to a shallow-sea environment, within which maritime fishing and agrarian lifeways coexisted. This cultural evolution was driven primarily by external environmental pressures: sea-level rise after 8000 cal yr BP, landward shoreline migration, and storm surges displaced coastal populations toward the western uplands and reduced access to marine resources; at the same time, accelerated seawater retreat between 8000 and 7600 cal yr BP facilitated the formation of the Yao River Valley Plain and created new flatlands (e.g., the Ningshao Plain) suitable for settlement. Internal factors, though secondary, were also important: around 7600 cal yr BP, environmental desalination in the Yao River Valley improved the feasibility of rice cultivation, and growing settlement density encouraged more intensive agricultural management (seasonal water regulation and improved tools), which accelerated rice domestication and promoted widespread cultivation between 6800 and 6600 cal yr BP. After a prolonged interval, continued sea-level retreat exposed the Hangzhou, Xiangshan, and Sanmen bays as land; although saline, silty soils constrained rice farming, natural harbors and proximity to East China Sea fishing grounds supported coastal livelihoods, consolidating mature maritime fishing culture along the shoreline.

Another significant transition was the shift from agrarian culture to canal culture, reflecting how environmental, political and economic factors shaped the integration of agrarian and canal systems in different historical periods. Overall, external environmental factors (push factors) occurred prior to internal supporting factors (pull factors) and played a dominant role, while pull factors and path resistance served as supplementary influences on this cultural transmission. In terms of corridors characteristics, the canal extends from the Yao River Basin to the Ningbo Plain, converging with the Sanjiangkou area and artificial irrigation channels to form a highly integrated canal network. This network connects agrarian cultural origins 1, 2, 3, and 5, establishing a corridor-canal system that effectively facilitates the integration of agrarian culture and canal culture.

After approximately 6000 cal yr BP, tidal forces shifted the Cao’e River eastward, and by 5000 cal yr BP, the formation of the ancient Yao River increased flooding and sedimentation in the Yao River Valley Plain, temporarily hindering rice cultivation41. These environmental changes, however, created the hydrological foundation for the formation of the Ningbo Section of the Grand Canal. Subsequently, the Yao and Yong Rivers, as tidal rivers, experienced major water level fluctuations and saltwater intrusion, prompting early settlers to construct water conservancy projects since Sui and Tang Dynasties. During the Song Dynasty, artificial tidal-avoidance waterways were established along existing channels, forming a dual system of natural and artificial channels42. Meanwhile, the renovation of six irrigation channels in the Yinzhou West and Yinzhou East Plains created the “Three Rivers and Six Irrigation Channels” network, which improved irrigation efficiency, expanded agrarian activities toward the Ningbo Plain, and enhanced the overall stability of agrarian culture43.

Pull factors were mainly political and economic. By the late Spring and Autumn Period, the State of Yue constructed the Shanyin waterways to develop the Ningshao Plain and consolidate governance, initiating politically driven waterway engineering. The Han Dynasty saw large-scale northern migration amid social unrest—this boosted labor demand and spurred the region’s first major water conservancy projects. By the Tang and Song Dynasties, the integration of natural and artificial waterways enabled the gradual connection of the Ningbo Section of the Grand Canal, significantly upgrading inland water transport44. During the Southern Song Dynasty, the capital established in Lin’an (Hangzhou) and growing trade demand drove river maintenance and shipping expansion. Ningbo, as a critical seaport serving the capital, enhanced inland–maritime connectivity through water conservancy facilities, and the growth of maritime trade further improved canal management and transport efficiency.

The transition from canal culture to maritime trade culture highlights how Ningbo evolved from an inland navigation hub to international port. Maritime trade activities were primarily concentrated in cultural origins 1, 2, 4, 5, and 6. Among them, cultural origins 1 (the Shanglin Lake area of Cixi) and 4 (the Sanjiangkou area) had the highest density of MTCH. The Shanglin Lake area provided abundant clay for porcelain production and forest fuel, while Sanjiangkou—at the junction of the Zhejiang Eastern Water System and East China Sea shipping routes—linked inland production sites to Mingzhou Port (Ningbo Port) and overseas markets via the Ningbo Section of the Grand Canal45. Canal waterways and heritage corridors connecting these origins formed an integrated network, enabling interaction between canal culture and maritime trade culture.

In this process, push factors played a dominant role, including political changes, natural environment, and shipbuilding technology. During the Tang Dynasty, Mingzhou (present-day Ningbo) relocated its capital to Sanjiangkou, forming a new port layout and establishing Ningbo as a key hub along the Maritime Silk Road46. The adoption of an open policy toward Japan and other regions, combined with efficient waterway connections via the Grand Canal, facilitated smooth transport and spurred the growth of regional foreign trade. During the Northern Song Dynasty, deterioration of shipping conditions in Hangzhou Bay and the Qiantang River made Ningbo the preferred port of call for ocean-going vessels. Accordingly, the Zhejiang Maritime Trade Office was moved from Hangzhou to Ningbo to manage shipping and trade. In addition, the Song-era shipbuilding yard at Sanjiangkou was among the most advanced nationwide, providing strong support for maritime trade.

Pull factors played a complementary role, reflecting policy support, rich cultural heritage, and a broad economic hinterland. In the Southern Song, Mingzhou was designated as the sole port for trade with Japan and Korea, with a Korean embassy established to facilitate stable trade and cultural exchanges. Subsequently, the Maritime Trade Offices in Hangzhou, Wenzhou, and four other places were abolished, making Mingzhou one of the three major foreign trade ports. By the Ming, Ningbo was the only port for Japanese Kan’ei trade tribute ships. After the Qing lifted the maritime ban, Ningbo became one of four national trade ports, and later one of five foreign trade ports in the Daoguang period. Beyond political support, cultural factors, particularly the flourishing of Buddhism, significantly influenced canal-related interactions. Introduced in the Eastern Jin, Buddhist culture was absorbed, integrated, and developed in Ningbo, peaking in the Tang and Song. This drew numerous Japanese and Korean monks for study and preaching; for example, in the Southern Song, Japanese monks Rongxi and Daoyuan sailed to Sanjiangkou, then took the canal to Tiantong Temple (cultural origin 6) for Buddhist studies. After returning to Japan, they established the Rinzai and Sōtō Schools of Chinese Zen respectively, sustaining cultural exchange between the region and Japan. Economic factors and the region’s rich natural resources further reinforced these exchanges. The Ningbo Section of the Grand Canal connected Shaoxing and Hangzhou to the Beijing–Hangzhou Grand Canal, creating a vast economic hinterland. The areas along the canal had abundant resources—such as Hangzhou silk, tea, and Yue Kiln celadon—which were transported via the canal to Sanjiangkou and then overseas. Simultaneously, foreign envoys brought exotic goods to local markets via the canal, sustaining two-way economic and cultural interactions in the region.

Third, the research’s methodological advantages are explored. One of the important methodological approaches of this study is the identification of cultural origins from points to areas. The cultural heritage is categorized into three main groups: ACH, MFCH and MTCH. Based on kernel density analysis, areal origins for agrarian culture, maritime fishing culture, and maritime trade culture are identified, proposing a point-to-area cultural origin identification system. This provides a theoretical basis for constructing the spatial pattern of corridors as a spatial organization component within heritage connection system. Traditionally, cultural heritage is categorized as tangible or intangible during the data collection stage16,47. However, such classification overlooks the historical threads behind cultural formation and hinders deeper understanding of its connotations and developmental logic. Most heritage corridor studies treat individual heritage sites as point-based origins and apply least cost path analysis to construct corridors17,48. This approach has two major limitations: (1) The spatial scale of heritage sites is often too small to capture the agglomerative and radiative characteristics of cultural diffusion. (2) Isolated heritage sites fail to reveal the internal logic of regional cultural development. In a complex region like Ningbo, where multiple cultures intersect, reliance on point-based origins can sever the spatial continuity of cultural systems, resulting in a fragmented corridor network. Therefore, the primary cultural threads in the region were extracted, and kernel density analysis was used to convert discrete heritage points into continuous surfaces representing cultural aggregation intensity. Third-level and higher density areas were then identified as cultural origins.

The research also develops a system for constructing corridors by integrating the elements of canal culture. To reflect the interaction between canal culture and other cultural systems, this study incorporates canal routes into the evaluation index system of maritime trade culture and compares the routes with potential corridors to construct the spatial pattern of multicultural heritage corridors. In previous studies, distance to the river was commonly used as a natural resistance factor, with resistance values assigned accordingly18. As a significant hydraulic infrastructure, canals have also played a significant role in shaping the evolution of cultural heritage in canal regions. The opening of the Ningbo Section of the Grand Canal enhanced regional water connectivity and facilitated trade and cultural exchange, leading to the accumulation of cultural heritage. This study quantifies the influence of canal routes on maritime trade culture by incorporating them as a resistance factor in the construction of the comprehensive resistance surface of maritime trade culture. Given the canal’s role in transportation and cultural transmission, its integration with potential corridors results in the spatial pattern of multicultural heritage corridors. Previous studies on heritage corridors often emphasized the direct corridors identification without integrating them into established regional transportation networks (including river systems)17,49, thereby limiting their effectiveness in promoting tourism and related industries.

Finally, strategies for cultural heritage preservation and tourism development based on corridor grading are proposed. Based on the spatial characteristics of multicultural heritage corridors—including cultural origins (Characteristics of them see Table S5), corridor centrality and CWD/LCP_length (Table S6)—this study proposes thematic and hierarchical tourism development strategies aimed at achieving both cultural heritage conservation and tourism growth. By connecting diverse cultural origins, heritage corridors acquire distinct cultural attributes, forming a foundation for themed tourism development. Heritage corridors mitigate the fragmentation of cultural origins by linking scattered origins. However, in practical implementation, differences in the internal distribution of heritage sites within each cultural origin should be taken into account. Accordingly, corridor-based tourism routes need to be adjusted to align with the spatial layout of cultural origins, ensuring smooth transitions between external corridors and internal heritage areas. Such spatial optimization not only preserves the integrity of cultural heritage but also supports effective corridor utilization and enhances the visitor experience.

The first-level corridors include two routes: corridor 1 (connecting cultural origins 2 and 4) and corridor 2 (connecting cultural origins 4 and 6). Their CWD/LCP_length values range from 2.04 to 2.34 and 2.35 to 2.67, respectively. Corridor 1 exhibits relatively low spatial resistance and can be prioritized for development. Functional zoning allows for thematic experiences: cultural origin 2, with its rich ACH, is designated as an agrarian cultural experience zone. The southern part of cultural origin 4 and northern part of origin 6, historically a hub for trade and Buddhist cultural exchange, can be planned as a maritime trade and Buddhist culture experience zone, with historical reenactments illustrating port trade activities and the movement of monks. Coastal areas of northern origin 4 and southern origin 6, rich in maritime fishing resources, are designated as maritime fishing culture zones. Corridor 1 thus enables a sequential visitor experience from agrarian culture to maritime trade and maritime fishing culture. Corridor 2 connects origins 4 and 6, highlighting temple nodes and historical contexts while providing a maritime fishing culture experience zone along the route.

Second-level corridors are concentrated on the west side of cultural origin 4, including corridors 3–6. Corridors 3–5 connect cultural origins 1, 2, 3, and 5 from north to south. Corridor 6 starts at cultural origin 4 and connects origin 5. Given the high integration of the canal and heritage corridors in this area, a canal protection zone can be established along the route to preserve the landscape. Combining this with the existing road network allows for a composite sightseeing route that integrates agrarian culture, maritime fishing culture, and maritime trade culture. Functional zones for each origin are clearly defined: western cultural origin 1 serves as an agrarian cultural zone (including Zishan and Tongjiaao Sites), while the eastern part provides maritime trade and celadon cultural experiences (Kaidao Mountain Kiln and Silongkou Kiln Sites). Cultural origin 3 is an agrarian cultural zone (Lujiaqiao Site), and origin 5 combines agrarian and maritime trade culture. Corridor 3 can be developed into a short celadon cultural experience route; Corridor 4 can establish a rice farming demonstration zone to strengthen agrarian culture, and corridors 5 and 6 integrate adjacent canal waterways, forming a composite sightseeing circuit combining agrarian, maritime trade, and maritime fishing cultural experiences.

Third-level corridors are divided into east-west (corridors 9 and 11) and north-south (corridors 13 to 15) directions. Corridors 9 and 11 connect cultural origins 1, 4, and 7, with CWD/LCP_length values of 2.04–2.34, indicating low resistance and facilitating visitor movement. Corridor 9 links the east side of origin 1 with the northern part of origin 4 (Xiepu Confucian Temple and “Bingchanggen” Site), enhancing visitor understanding of maritime trade and fishing cultures. Corridor 11 connects the material remains of maritime fishing culture in northern origin 4 with intangible cultural heritage in origin 7 (Xianchang Lantern Play), enriching visitor experiences. Corridors 13–15, running north-south, have higher CWD/LCP_length values (2.68–3.04), indicating significant resistance. Critical areas of the corridor are concentrated in the middle segments of corridors 13 to 15 (Fig. 5f), suggesting limited alternative paths for cultural element flow in this area. Full connectivity of corridors 13–15 is therefore essential for improving overall corrido r connectivity and supporting cultural experience activities.

This study takes the Ningbo Section of the Grand Canal of China as the study area. Based on the spatial pattern of multicultural heritage corridors, an improved push–pull framework is proposed by integrating traditional push-pull theory with migration modelling, thereby establishing a systematic approach for the connection of multicultural heritage.

The main conclusions are as follows: (1) Different types of cultural heritage exhibit varying spatial aggregation trends, which facilitate the identification of multicultural origins and form the basis for developing the spatial pattern of multicultural heritage corridors. (2) The Ningbo Section of the Grand Canal is strongly integrated with potential multicultural heritage corridors. The formation of a composite corridor network centered on Sanjiangkou facilitates the efficient flow of cultural elements. (3) Applying the improved push–pull framework to the spatial pattern of the corridors enables the analysis of the transitions and integration among primary cultural threads, offering insights into the dynamic evolution of cultural heritage and multicultural interactions.

The main innovation of this study lies in the construction of an improved push–pull framework and its integration with the spatial pattern of heritage corridors. From a theoretical perspective, this framework moves beyond the traditional assumptions in population migration studies that rely solely on population size and road distance. By incorporating distance impedance based on circuit theory together with indicators of cultural element mobility, the model captures the heterogeneous landscape resistance inherent in cross-regional cultural dissemination. This enhances the explanatory power of the framework, providing a more realistic account of cultural diffusion processes in historical contexts and offering a novel perspective for understanding mechanisms of intercultural interaction. From a practical perspective, the improved push–pull framework, when combined with GIS spatial analysis and corridor analysis, effectively reveals the connection mechanisms among cultural origins. It offers scientific support for heritage protection, tourism route optimization, and regional cultural governance by enabling the identification of least cost cultural flow paths, providing a basis for hierarchical protection of heritage corridors, and supporting functional zoning for cultural experiences and integrated development. Moreover, the framework demonstrates strong transferability and can be applied to other heritage-concentrated regions, providing methodological guidance for corridor construction and cultural exchange studies worldwide.

Despite these contributions, several limitations remain: (1) Some resistance factors are difficult to quantify and have not yet been integrated into the evaluation index system. (2) The current cultural heritage inventory is incomplete and requires further updates in future research. (3) The present study focuses primarily on land-based corridors, while maritime spaces have not yet been included. (4) Long-term natural and socio-economic datasets are limited, making it difficult to capture the long-term processes underlying the evolution of heritage corridors. Future studies should address these limitations by incorporating unquantified variables, updating and expanding heritage inventories, and integrating maritime corridors into the analytical framework. In addition, examining the dynamic evolution of corridors over longer time scales based on enriched datasets of natural and socio-economic conditions from multiple historical periods will be essential. Furthermore, better integration of the corridor network with related transportation systems is expected to significantly enhance regional heritage conservation and tourism development.