Towards Sustainable Rural Revitalization: A Multidimensional Evaluation of Rural Vitality in China's Traditional Villages

: Traditional villages constitute a significant component of China's rural heritage. In the context of national efforts to achieve sustainable rural revitalisation, there is a lack of comprehensive assessments of rural vitality that can evaluate the balance between the competing demands of heritage conservation and rural development. This study aims to address the gap by defining an evaluation index system, Rural Vitality Assessment (RVA), which comprehensively assesses both protective and developmental aspects while taking into account natural and cultural ecological factors. The study utilizes data from a total of 206 traditional villages located in Hebei Province and employs a model to classify and analyze both subjective evaluations collected by interview and questionnaire alongside objective data. The framework employed a combined weighting method to determine appropriate indicator weights, thus facilitating quantitative evaluation of the data obtained. The study shows that over 90% of traditional villages in Hebei Province exhibit an imbalance between protection and development, which could lead to gradual deactivation. Additionally, the spatial distribution of RVA outcomes shows polarization, with higher levels observed in the north and lower levels in the south. The study concludes that the RVA framework is an effective tool for analysing the vitality level, spatial distribution, and disadvantage indicators of villages at different zoning levels. The results can provide a reference for the formulation of targeted heritage protection and development planning strategies and further aid in the rational allocation of resources, helping to narrow the development gap between urban and rural areas.


Introduction
The conservation of rural heritage faces numerous challenges due to the transition from an agrarian to an urbanindustrial economy and the rapid development of the urban-rural dichotomy.Facing the global challenge of rural decline, the UNESCO World Heritage Centre (2021) stipulates the need for a comprehensive and coherent conservation strategy.This includes clarifying the content of conservation, promoting participatory planning and stakeholder coordination, and ensuring transparency of operational mechanisms to establish an effective management system [1].In China, conservation and management of rural heritage is primarily accomplished through the selection of traditional villages at the national and provincial levels.In 2008, the Chinese government issued the Regulations on the Protection of Famous Historical and Cultural Cities, Towns and Villages, along with other relevant policies and regulations.This has led to the establishment of a relatively comprehensive system for the presevation of traditional villages [2].
In China, villages are characterized and classified by their long-standing history, distinctive architectural and cultural elements, and tight-knit community bonds [3].These settlements boast meticulously preserved traditional structures, ranging from ancient edifices to revered temples and shrines, alongside vibrant cultural practices like folklore, festivities, and indigenous craftsmanship [4].These villages have evolved through centuries of architectural development and serve as repositories of local heritage.They encapsulate the shared memories and identities of their inhabitants [5,6].Traditional villages play a crucial role in showcasing the local culture, customs, rural morphology and architecture style of different regions [7].They also serve as a reflection of the dynamic cultural and social development, and possess high aesthetic and environmental values [8].However, rapid urbanisation and industrialisation have significantly impacted rural development, resulting in traditional villages facing various challenges, such as population exodus [9].The collapse of numerous ancient buildings [10], the interruption of non-heritage cultural inheritance [11], and the rigid integration of old and new buildings [12] have led to the decline of rural settlements [13].Despite the plethora of research on traditional Chinese villages, the majority remains fixated solely on heritage preservation, overlooking the broader spectrum of rural development initiatives.
Rural revitalisation in China is considered a significant measure to address the loss of historical and cultural values and the lack of vitality in the development of China's traditional villages [14].The aim of the action is to rediscover and highlight the vitality of rural 'traditional genes', tap into regional culture, preserve the cultural heritage of the countryside, and promote cultural revitalisation [15].The new published policy in this context creates additional employment opportunities and facilitate the revitalisation of the local economy [9].Rural revitalization action also constructs and nurtures good talent-local relationships by dealing with agricultural industry, rural planning, and farmers [7,16].As consequence, rural tourism and the rural industrial chain have experienced significant growth since 2010, contributing to the rapid and diversified growth of the rural economy [17].For an extended period, rural settlement construction has suffered from a dearth of systematic planning guidance, leading to haphazard layouts, diminutive scales, and dispersed distributions [18].Therefore, rational allocation of rural development factors and optimization of rural living environment have become the key to the sustainable rural development, which will help promote comprehensive rural revitalization [19,20].In the process of holistic heritage management of traditional villages, it is imperative to establish a complete and systematic assessment framework.This framework necessitates the quantitative depiction of the practical challenges encountered by the rural regional system during urban-rural transformation, alongside the assessment of heritage value and development potential in traditional villages.
Scholars have extensively investigated the conservation of traditional villages as part of efforts to optimize and revitalize rural settlements.Existing studies primarily focus on two dimensions: the dynamic spatial characteristics and the factors influencing or driving them [21][22][23].Some scholars focus more on the morphological transformation of rural settlements, including the analysis of historic building characteristics and street layout using qualitative methods [21,24].Many of the quantitative studies use ArcGIS as the primary means of interpreting and evaluating the geospatial detection of spatial relationships and geospatial clusters through the construction of an analytical hierarchy of drivers [22,25,26].Quantitative studies of traditional villages have tended to focus on a specific aspect, such as spatial restructuring [27], climate adaptability [28], and sustainability of rural ecosystems [29] , but much less on social connectedness [30].Therefore, some scholars argue that a more scientific and effective assessment framework that can comprehensively and objectively evaluate the status quo of rural settlements is needed to complement the identification of the driving factors of rural settlement spatial development [30][31][32].
An accurate and comprehensive evaluation of traditional villages is fundamental to formulating policies for sustainable rural revitalization.Such an assessment enables a tailored approach to different regions and the efficient utilization of their internal resources [33].Academics have developed diverse systems for evaluating criteria from different viewpoints, such as "Production-Living-Ecology" evaluation system [30], "man-land areal system" [24], Population-land-industry evaluation index system [27].Geographical Information System (GIS) plays a significant role in examining the spatial arrangements of rural settlements.Methods such as nearest-neighbor distance analysis, assessment of spatial uniformity (utilizing tools like the Geographic centralization index, and Gini coefficient), as well as Kernel density techniques, are employed to investigate the spatial distribution features and developmental statuses of targeted traditional villages in Shaanxi [25].The topographic relief degree index was utilized to assess the terrain characteristics of both historical villages and their adjacent regions in Southwest China [34].This assessment was conducted via Neighbourhood Analysis" employing ArcGIS software and Digital Elevation Model (DEM) elevation data.In addition, statistical analysis methods such as Moran scatterplot correlation between altitude and distribution [34], are applied to classify rural settlements.Value evaluation function groups are applied to classify land use functions in rural areas [35].However, the evaluation results are still not comprehensive enough, as most current studies use only one of them or combine two of them for the evaluation.
As the village industry has developed and the economy has grown, the importance of fundamental factors such as the natural environment has decreased, while socio-economic factors like market demand have become more prominent [23].Local economic, social, cultural and management realities must be fully taken into account and the tailor-made proposal must be adhered to when formulating and implementing conservation plans [36].The study aims to answer the following question: In the context of national-level rural revitalisation efforts, what methodologies can be used to comprehensively evaluate the vitality of traditional villages, taking into account their current spatial, cultural characteristics, and economic development?
Through research on more than 200 cases in Hebei Province, the article contributes to: (1) An index system that can take into account the capacity of both the conservation of cultural heritage and rural development.
(2) A methodology that combines morphological study, GIS method and statistical analysis on the basis of large samples.
(3) An assessment framework that can be used to quantitatively assess both the vitality and the balance of vitality between protection and development.
This research endeavors to develop a comprehensive evaluation framework aimed at comprehending the vitality and attributes of traditional villages across China's administrative divisions, serving as a foundation for sustainable revitalization.In line with the imperative of sustainable rural revitalization, we investigated the composition of indices and assessment methodologies applicable to diverse village contexts.This research helps to formulate targeted heritage protection and development planning strategies as needed, and further contributes to the rational allocation of resources and narrow the gap between urban and rural development.

Study area
Hebei Province, situated in North China, encompasses 11 prefecture-level cities and covers an area of 188,800 square kilometers.Bordered by the Bohai Sea to the east, the Taihang Mountains to the west, and traversed by the Hai River and the Luan River, the Hebei Province exhibits diverse geographic features with a varied landscape.
As of January 2023, Hebei Province boasts 206 cases listed among Chinese traditional villages, representing 3% of the country's total [26].Predominantly situated in the eastern foothills of the Taihang Mountains and the southern slopes of the Yanshan Mountains, these cases exhibit a distribution pattern skewed towards the north, tapering off towards the west, as illustrated in Fig. 1.Since 2016, the governments at all levels in Hebei Province have prioritised the protection and preservation of those villages.The protection planning system, regulations, and policy measures have been continuously improved.An in-depth exploration of the cultural connotation has been carried out with a subsidy of 426 million yuan from the central government.In this process, 779 salvage and protection projects have been implemented.The traditional villages in Hebei Province exhibit varying degrees of vitality due to the economic influence of the Beijing-Tianjin-Hebei region and differences in their protection and development capabilities.As a result, county governments and administrations have faced challenges in identifying the basic unit for sustainable rural revitalisation and heritage conservation policies based on individualised village development.Hence, recognizing the necessity of assessing village vitality levels and acknowledging its potential implications, this study opts to focus on traditional villages in Hebei Province as the primary subjects of analysis.

Data sources
The data used in this article mainly come from the following sources: 1. Maps, including city and county administrative divisions and ecological environment geographical information data, come from the National Geographic Information Resources Directory Service System [37]  3. Data such as traditional village rating results and related protection policies refer to "China Statistical Yearbook 2023" [41]."Atlas of Historical and Cultural Towns, Famous and Traditional Villages in Hebei Province" [42]as well as socioeconomic data and policy documents of prefecture-level cities in Hebei Province.
4. Data acquisition in the production system and living system is mainly based on questionnaire surveys, supplemented by interviews with village cadres.

Method
Scholars pointed out that multi-dimensional quantitative framework should be used to comprehensively reflect the dynamic changes and future development potential of traditional villages over a period of time, including agricultural production activities, social life, and ecological environment changes [43][44][45][46].However, many rural vitality index systems only take into account economic, demographic, and social-cultural factors, as well as other factors related to development [33], while do not directly consider factors related to the preservation.Meanwhile, other index systems, such as 'social and cultural vitality indicators' [47] and 'cultural heritage vitality indicators' [48], are inadequate in representing the variations in cultural heritage preservation and rural construction and development capabilities.This is the primary cause of regional disparities in rural vitality levels.Further research is required to identify the indicator dimensions suitable for Rural Vitality Assessment (RVA).This will provide an objective and systematic basis for the protection and development of traditional villages.

Interpretation of the RVA
In light of the China's central government's emphasis on rural revitalisation, traditional villages have gained significant opportunities for conservation and development.In 2008, Jixiang Shan, the former head of China's State Administration of Cultural Heritage, highlighted the importance of tangible cultural heritage as a witness to history and culture.Such heritage still serves its original function and continues to play a role in modern social life [49].The conservation of traditional villages not only meets the livelihood needs of the residents but also brings significant economic benefits [50].In addition, the preservation of rural cultural heritage should not only serve the functions of inheritance and edification but also provide practical value in line with the development of the times [46].Thus, this study defines RVA as a comprehensive assessment of the ability to conserve rural heritage and develop rural areas.

The multi-dimensional evaluation index system
An assessment framework has been constructed, consisting of six aspects categorized under development and protection: Rural Industry, Living Environment, Natural Ecology, Cultural Ecology, Development Conditions, and Development Potential (see Table 1).This framework draws upon relevant literature on village revitalization assessment and incorporates insights from the 'Traditional Village Evaluation and Identification Indicator System (Trial)' [51] and chose 57 indicators (X1~X57) for quantitative evaluation (available in Additional file 1: Table S1).
Table 1 The six dimensions of the RVA framework.

Rural industry Land-use
Rural industry focuses on transforming traditional mono-farming and integrating new industries and tools to improve the efficiency of rural economic production in order to increase villagers' income and participation.

Living environment
It encompasses historical buildings and remains, such as traditional architectural styles, historic sites, and cultural heritage values, as well as traditional customs, such as unique ethnic characteristics, culture, or craftsmanship, and newly constructed living spaces.

Historic buildings
Traditional customs

Natural ecology
The ecosystem is defined by the interaction between spatial and temporal patterns in ecological processes of the environment of traditional villages.It refers to the landscape-scale ecosystem and ecological sensitivity, which considers the possible negative impact of the interaction between landscape pattern and ecological processes, taking into account spatial patterns and heterogeneity.

Ecological environment
Cultural ecology It refers to a comprehensive perspective of the cultural ecosystem based on the recognition of heritage value.This perspective interconnects the elements of material, behavioural, and spiritual culture that characterise the heritage itself with the environment, encompassing both the tangible and intangible heritage.

Development conditions
Development conditions primarily refer to the current situation that affects the development of the village, including its geographical location, foundational economic elements, and human resources.The main conditions that affect village development are a favourable geographic setting for economic growth, robust and stable overall income, a healthy population, and well-maintained and accessible public infrastructure.

Index weights determined by a combined weighting method
This study establishes index weights using a combined weighting method that includes both objective and subjective weight (see Error! Reference source not found.).The Analytic Hierarchy Process (AHP) is used to determine subjective weight, while the entropy weight method is used for objective weight.The weighting method is tailored to the distinct attributes of each index.The AHP is utilized to deconstruct the concept of RVA into its constituent components, indicators, and sub-indicators [58].These indices are compared pairwise across three levels to ascertain their relative significance.Based on specific considerations such as the quantity and nature of evaluation objects, the RVA of traditional villages in the Hebei province is graded accordingly (see Error! Reference source not found.).Subsequently, the evaluation process is iterated for elements within each criterion, followed by indices within each element [58].
This study conducted questionnaire surveys and interviews with local residents, officials familiar with selected cases, and experts with many years of work experience in related fields.A total of 180 responses were collected, including 165 questionnaires and 15 interviews with academic and government personnel.After several rounds of scoring, a judgement matrix was created and inputted into the yaanp2.5 software for Consistency Inspection (CI) and weight calculation.The inspection results indicated that the matrix passed the consistency test (all items were lower than 0.1).Subsequently, a subjective weight index system was established based on these results.Furthermore, the EW method involves constructing an original data matrix based on the evaluation framework indicators.The TOPSIS model is then used to calculate the eigenvalues and entropy values, resulting in the objective weight indicators (refer to Section 2.3 for a detailed description).Error!Reference source not found.displays the final weights of both subjective and objective indicators.

Index scoring and index weighting method
According to the index attributes and data types in the evaluation framework established by our team [58], the authors deeply study the backwardness of typical traditional villages with better protection and development, and combine the national standards, experts' and villagers' opinions, setting five evaluation standards (1, 2, 3, 4, 5) for scoring (see Table 2).0 < X ≤ 1 has a lower correspondence degree, with an assignment of 1 point, 4 < X ≤ 5, with the highest correspondence degree, with an assignment of 5 points.

Index data binning
All 57 indexes were analyzed by range standardization method.These need to find the maximum (Xmax) and minimum (Xmin) of the index, calculate the range (R=Xmax-Xmin), and then subtract the minimum (Xmin) from each observed value (X) of the variable and divide by the range (R).
X′ = (X − Xmin)/(Xmax − Xmin) Following the application of the range standardization method, each observed value of the variable undergoes a numerical transformation to ensure it falls within the range of 0 < X < 1, irrespective of its original positive or negative status.This process enables both positive and inverse indices to be uniformly converted into positive indices, streamlining subsequent weight calculation and comprehensive score determination.
Then, 18 indexes, such as vegetation coverage rate, were treated in equal width segments and specific scores were obtained (see Table 3).The remaining 39 indicators are scored according to the actual survey data.The EW method, also referred to as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model, operates as a distance-based evaluation technique.At its core, it gauges the distance between the evaluated object and both the optimal and worst values available [59].Then, it calculates the proximity between the evaluated object and the ideal value, facilitating the ranking of advantages and disadvantages.The study's specific requirements, characterized by a small sample size and high objectivity, deem it suitable.The EW-TOPSIS model represents an enhancement of the TOPSIS model, incorporating the entropy weight method to ascertain the weight of individual evaluation indices and evaluate the significance of each objective evaluation index [60].The TOPSIS model is then used to rank the decision objectives.The EW-TOPSIS model is used in this paper to calculate the index weights at all levels.The following section outlines the calculation steps: (1) Construct the evaluation index system matrix (M).Assuming that there are m evaluated objects and each evaluated object has n indexes, the evaluation index system matrix is: Where i is the evaluated object; j is the evaluation index [61].
(2) Standardization of index matrix: R = (r ij ) m×n (i = 1,2, ⋯ , m; j = 1,2, ⋯ , n) (2) Where R is the standardized evaluation index system matrix; r ij is the standard value of the i-th evaluated object on the j-th evaluation index; m is the total number of evaluation objects; n is the total number of evaluation indexes [61].
(3) Calculate the entropy: ) Where E j is the entropy; p ij =r ij / ∑i=1mr ij; k is a constant term, k=1/lnm [60]; p ij is the proportion of index value under the j evaluation index of the i-th evaluated object of matrix R [61].
(4) Determine the objective index weight: Where w j is the weight of index j; E j is the entropy of index j [61].
(5) Calculate the normalized entropy weight matrix (O): Where o ij is the value of the i-th evaluated object after the j-th evaluated index standardization [61].
(7) Calculate the Euclidean distance between the target object and the optimal and the worst solutions [61]: ) Where C j is the closeness between the evaluated object and the optimal solution, and the larger the value, the better the evaluated object [60].

Analytic Hierarchy Process (AHP)
The AHP is used to calculate the weights of subjective indexs assigned to different evaluation factors [62].The Consistency Ratio (CR) is utilized to assess the consistency of pair-wise comparisons of classes and subclasses.CR can be calculated using the following equation [63]: where RI is random index indicating the consistency index of randomly generated pairwise matrix shown in Table 2 and CI is the consistency index which was computed using following formula [64].

CI =
λmax−n n−1 (11) Where λmax is the largest matrix eigenvalue, n is the number of thematic layers.CR less than 0.10 indicates acceptable consistency of pair-wise comparison and weight calculation.If the CR is more than 0.10, the pair-wise comparison has to be modified until it is reduced below 0.10 [63].

ArcGIS superposition analysis
Employing the raster calculator tool of ArcGIS 10.8 and applying the weighted superposition method, this study conducts a comprehensive analysis of each evaluation index.The calculation method is as follows [65]: Here, Wi signifies the weight of the ith index, and Yi denotes the standardized value of the ith index [65].A higher RVA value corresponds to a heightened level of vitality, while the reverse holds true.The value should consistently remain within the range of 0 to 100.

Coefficient of variation method
The coefficient of variation method is a statistical measure that assesses the extent of variation among observed values in a dataset.When the unit of measurement aligns with the mean, the standard deviation can be directly utilized.However, if the unit differs from the mean, comparing the variation degree using the standard deviation becomes inappropriate.In such cases, the ratio of the standard deviation to the mean should be employed for comparison [26].The formula for calculating the coefficient of variation is as follows: Where C is the coefficient of variation, x is the standard deviation and φ is the mean [26].

Kernel Density Analysis
The spatial distribution of traditional villages across Hebei Province exhibits non-uniformity, which fluctuates according to the area under consideration [26].This method operates on the assumption that events can potentially transpire anywhere within a given space, each with varying probabilities across different locations.Moreover, the intensity of the designated reference point correlates with the likelihood of an event taking place, where a greater intensity signifies a heightened probability of occurrence.In this study, we utilize kernel density analysis to visually illustrate the clustering and dispersion patterns.The kernel density is computed using the following formula: x − represents the distance from the estimated point x to the event xi [66].

Interpretative Phenomenological Analysis (IPA)
The IPA is a methodological approach that falls under importance expressiveness analysis, typically represented in a four-quadrant diagram format, providing a visual representation of each objective within these quadrants.It delineates a two-dimensional depiction, with the vertical axis capturing 'potential value evaluation values,' encompassing development conditions and development potential.The diagram presents each objective in one of the four quadrants, with the horizontal axis representing 'current resource evaluation values' and factoring in three dimensions: production system, living system, and natural ecology (See Fig. 3).To determine the intersection point, the average value, excluding the highest and lowest values, is computed, resulting in the coordinates (23.81, 17.35).The coordinate system is divided into four quadrants: the advantage area, opportunity area, vulnerability area, and improvement area.

Ratings of RVA levels across Hebei province
After analysing the levels of vitality development in 206 selected cases in Hebei Province using the established evaluation model, it is clear that all evaluated entities received scores of 60 points or less.Baizhongbu Village received the lowest score of 29.50 (available in Additional file 2: Table S2).The sorted scores show a median of 40.58 points (see Fig. 4).The vitality development level in Hebei Province is notably low, whether examining individual scores or the median level.This highlights the challenge of halting the continuous decline of traditional villages.

Zoning assessment
Based on the spatial distribution of traditional villages with varying levels of vitality in Hebei Province (refer to Fig. 5), it becomes apparent that there is a concentration of objects with a middle-low level of vitality development primarily in south part of Hebei, such as Shijiazhuang (no.=53), and Zhangjiakou (no.=52),Handan (no.=44),Xingtai (no.=40).Baizhongbu Village is located in Zhangjiakou and it is the only case that exhibits a low level of the whole.For further evaluating, Hebei Province is divided into four areas based on climatic and geographical conditions: northern, central, eastern, and southern Hebei (refer to Fig. 6).

Statistical RVA results
According to the statistics for different vitality levels (refer to  It is evident that no villages in any region received ratings of V1 or V2 (refer to Table 5).The Central Hebei has the highest percentage of V3 ratings at 12.12%, while the Eastern Hebei region has a 100% rating for V4, followed by the Central Hebei at 96.22%.The Northern Hebei region achieves a 100% rating for V5, with the other regions receiving a rating of zero.Southern Hebei has the highest count of traditional villages (no.=84), while Eastern Hebei has the lowest count (no.=3) when considering the total number of villages in each district.

Median statistics analysis
The median statistics of RVA zoning assessment results in Hebei Province across the four regions (as shown in Fig. 7) indicate that the Eastern Hebei has the highest median development level in the province, standing at 44.03.Central Hebei and Southern Hebei fall into the medium-level category, whereas Northern Hebei exhibits the lowest median in the province, reaching only 39.42.These findings highlight differences in the protection and development status of villages across various regions of Hebei Province.The level of village activation in Northern Hebei is particularly low and requires special attention.Additionally, the eastern, central, and southern regions of Hebei need improvements in the dynamic development of traditional villages.

Economic development analysis
An analysis of the economic development levels of cities in Hebei Province (see Fig. 8) reveals that the Eastern Hebei has the highest per capita GDP and urbanization level in the province.Furthermore, the region has the second-highest proportion of secondary industry and the least proportion of primary industry.These findings suggest a favourable economic development status in the Eastern Hebei, indicating a relatively robust economic condition.In contrast, Southern Hebei has the lowest per capita GDP and urbanization rate in the province, indicating a relatively less favorable economic situation in the region.It is evident that the eastern region experiences high levels of economic development.However, the limited number of preserved traditional villages contributes to an overall poor revitalisation and development situation.Conversely, the other regions struggles with lower levels of economic development, resulting in poor RVA outcomes.Therefore, the dynamic development of traditional villages is intricately linked to the economic development level, highlighting the need for a balanced economic status that avoids extremes of both high and low levels.

Multi-dimensional scoring
According to the scores of traditional villages in the four subdivisions of Hebei Province across six dimensions (see Fig. 9), the Eastern Hebei performs better than the average in both ecosystem and development conditions, while the northern region significantly lags behind the average.Concurrently, the living system and cultural ecological dimensions across each district closely align with the average values, showing no significant differences.The cultural ecology dimension has the highest rating from an average score perspective.This indicates that there is commendable preservation of material heritage, robust inheritance of intangible cultural heritage, and favorable foundational conditions for the development of rural cultural industries.The development conditions dimension received a high score, indicating that traditional villages in Hebei Province have advantageous conditions in terms of location, infrastructure, population, and economic foundation.This positions them favorably to align with rural revitalization policies and contribute to the sustainable rural development.However, the remaining indicators, namely the living environment, rural industry, natural ecology, and development potential, receive lower scores.This indicates outdated production methods in those cases, underutilization of historical buildings, and suboptimal ecological conditions.

Kernel density analysis
Utilizing ArcGIS 10.8, we conducted a spatial visualization of vitality levels across six dimensions, as depicted in Figure 10 (see Fig. 10).The distribution characteristics within these six dimensions revealed a consistent pattern, shaping a bimodal activation spatial structure with elevated levels in the central and southern regions and diminished levels in the northern part of the province.Predominantly situated in the cities of Shijiazhuang, Handan, Xingtai, Baoding, and Zhangjiakou, the villages exhibit a clustered distribution in two primary areas.Notably, a concentration is observed in the western Xingtai-Handan region and the central-southern Shijiazhuang area, indicating higher vitality.Conversely, the southern part of Zhangjiakou showcases a concentration of villages with relatively lower vitality.

Balance analysis
The analysis of the degree of dispersion of RVA in the four regions employed the coefficient of variation to illustrate the balance of rural conservation and development (see Fig. 11) and further visualized in Fig. 12.A higher coefficient of variation denotes increased dispersion and a poorer balance, while a lower value indicates better balance.Fig. 11 reveals that the Southern Hebei exhibits the smallest coefficient of variation, indicating the highest level of balance.Central Hebei and Northern Hebei fall in the mid-range with average balance, while the Eastern Hebei displays the largest coefficient of variation, distinct differentiation characteristics, and the least favorable balance.

Regional activity analysis
The cultural landscape changes and population mobility are primarily influenced by macro social life and economic construction activities.To reflect the spatial distribution characteristics and correlation degree of regional activities in Hebei Province, three factors -population, GDP, and road network density -were selected and plotted (see Fig. 13).
The Eastern Hebei has a high spatial density of road networks, an average population density, and elevated GDP levels.The area has a widespread distribution, significant social and economic activity, and a limited number of scattered villages.In the central and southern regions of Hebei, which are characterized by dense road networks, population density, and GDP levels, a concentration of these attributes is observed in the central core area.The region's development is uneven, with high social and economic activity and a significant presence of villages.In contrast, the western regions face challenges related to population and transportation, while development is concentrated in the north.Northern Hebei has a low spatial density in road networks, accompanied by low population, overall GDP levels, and social and economic activity.Traditional villages are concentrated in the southern part of Zhangjiakou.The level of regional activity, whether high or low, presents challenges during rural renewal.High regional activity can lead to the destruction of underprotection rural areas, while low activity may impose developmental restrictions, resulting in a generally low activation process.
In conclusion, extreme regional socioeconomic activities act as impediments to the spatial protection and cultural inheritance.To revitalize these villages, it is essential to comprehensively consider the balance between the area's social and economic activity and the level of revitalization of the village, in order to ensure sustainable protection and development.
Fig. 13 The coupling diagram of the regional activity analysis and traditional villages in Hebei Province (Data source: https://www.gscloud.cn/(accessed on 5 November 2023).

Construction of evaluation framework and discussion on indicators for RVA of traditional villages in Hebei province
Rural communities must address conservation issues while recognizing the potential of their diverse and vibrant heritage.Existing research primarily focuses on two aspects: development elements, such as the economy, population, and social conditions [67], and the conservation of cultural heritage [54].There is a need for comprehensive studies that consider both rural development and heritage conservation.It is urgent to develop a methodology to understand the balance between these two conflicting aspects in rural heritage.
Examining rural communities worldwide, it is evident that nature and human society have coexisted for millennia.However, there is still controversy over whether the natural ecological environment and cultural ecological elements have a significant impact on the vitality of traditional villages.According to Mengyao Xu (2021), some scholars argue that the natural ecological environment has little impact on the development of rural area and should not be a research focus [68].This is because traditional villages in China are typically situated in mountainous and hilly areas with relatively good natural ecosystems.While some scholars have included the natural ecological environment as a criterion for vitality assessment and have analysed factors such as water quality, farmland density, altitude, and slope [57,69] others have also considered the morphological transformation of rural settlements [70].Incorporating natural ecological elements into the RVA index is significant and could offer a potential solution.
Some economic indicators such as birth rate, mortality rate, and employment rate were excluded from the index selection due to the unavailability of rural-level data in China.Once more comprehensive data is released by the country, the evaluation indicators will be further improved to enhance the comprehensiveness, objectivity, and logical structure of the evaluation.

IPA analysis to provide guidance for rural revitalization
This article utilises IPA diagrams to visually represent a comprehensive analysis of the protection status and development potential of traditional villages.The horizontal axis represents the current situation of rural heritage protection in the three dimensions of production system, living system, and ecological system.The vertical axis represents the prediction of village development potential in the two dimensions of development conditions and development potential.The intersection point (23.81, 17.35) is determined by taking the average value after removing the highest and lowest values.The coordinate system is then divided into four quadrants: advantage, opportunity, vulnerability, and improvement (see Fig. 14).Table 6 shows the basic characteristics of each quadrant.The practical implications of the IPA results are listed below: (1) Villages located in geographically advantageous areas often experience a higher level of revitalization, which is characterized by dominant industrial development, particularly in the form of tourism.These cases strategically leverage their traditional attributes and actively promote tourism as a means of safeguarding their cultural heritage while achieving harmonized economic, social, and ecological benefits.It is important to note that this assessment is based on objective analysis of available data, rather than subjective evaluation.Combining industrial transformation with cultural characteristics appears to be a promising strategy for promoting the dynamic development of traditional villages.
(2) Villages situated in fragile areas should focus on safeguarding and fortifying their original features.Any compromise to their architectural styles and spatial patterns could significantly impede their developmental trajectory.Furthermore, integrating cultural elements can facilitate industrial upgrading and development, attracting potential investments.
(3) Priority should be given to protecting and strengthening the original features of villages in fragile areas, as damage to their styles and patterns can be extremely detrimental to their development.Additionally, integrating cultural elements can aid in industrial upgrading and development, which can attract investment.
(4) Villages within the improvement area have abundant resources but generally exhibit low development potential, which is intricately linked to population decline.These cases have diminished social and economic value.To prevent the decline of such villages, it is imperative to attract younger demographics back to their ancestral homes and foster entrepreneurship.

The promotion and limitations of the RVA framework
The results of the RVA can be used to support the effectiveness of sustainable revitalisation policies for traditional villages.Different policies can be proposed based on the unique characteristics of each village to promote sustainable rural revitalisation.Local governments can then implement customised policies based on the vitality analysis levels and work priorities.This study proposes protection and development strategies for 192 low-vitality cases to prevent the extinction of traditional villages.The clusters with low vitality, such as Baizhongbu Village in North Hebei and Liujiazhuang Village in South Hebei, require special attention.Additionally, sustainable development and policy formulation should be the focus for the remaining 14 cases with medium-level vitality.The issues identified in the text include inadequate protection, a low proportion of historical architecture, limited preservation of the living environment, and constrained construction land.It is important to pay special attention to clusters such as Ranzhuang Village in Central Hebei, traditional village groups in Jingxing County, and Boyan Village in South Hebei.
Furthermore, the results of the RVA can serve as a foundation and methodology for evaluating the effectiveness of rural revitalization.The study collected data in January 2023 to establish a baseline for evaluating the ongoing impacts of rural revitalization.To facilitate comparison of changes in vitality levels, spatial distribution, conservation-development balance, and adverse indicators, recurrent data collection and evaluation using the same methodology will be conducted in subsequent years.This systematic approach allows for an objective evaluation of the effectiveness of sustainable revitalisation in rural areas of China.It provides a scientific basis for identifying any remaining issues and supports an assessment approach focused on promoting vitality.
Throughout this study, we identified certain limitations warranting further investigation: (1) The manifestation of rural vitality is dynamic, influenced not only by the spatial dimension of rural construction but also by the temporal dimension of rural development.The roster of traditional villages undergoes continuous updates, and the management and policy formulation for traditional village protection are subject to ongoing enhancements.Leveraging data from January 2023 as a reference point, this paper seeks to furnish the methodology (evaluation framework) and quantitative analysis data support for the protection of traditional villages over recent decades.
(2) Rural vitality is an inherently abstract concept, complicating the verification of vitality assessment results for hundreds of villages through questionnaires.As researchers are unlikely to conduct on-site visits and interview all residents, a fully objective and comprehensive judgment of the overall vitality level of these villages becomes challenging.Consequently, the outcomes of this study are representative but not exhaustive in encapsulating all village groups.
(3) Given the substantial disparity in China's economic and social development levels, the index weights established in this study rely on expert surveys familiar with cases in Hebei Province and are not directly transferable to other regions.When applying this methodology to other provinces, it is advisable to seek guidance from experts acquainted with the specific region to determine suitable index weights.
(4) The study focused on 206 selected cases in Hebei Province as the research area.However, the nation boasts a significant number of traditional villages with varying geographical locations, climatic conditions, social-cultural backgrounds, and development histories.Future research endeavors are encouraged to undertake comparative studies and analyses involving a broader spectrum of cases.

Conclusion
This study presents a framework and methodology for comprehensively assessing natural ecological factors, cultural heritage protection, and economic development in traditional villages, in line with the robust promotion of rural revitalisation.The rural revitalisation is divided into two core dimensions: conervation and development, which leads to the establishment of an evaluation index system.The index weights are determined using the combined weighting method, which takes into account the distinctive attributes of each index.The development level of revitalization in traditional villages within the region is then categorized, resulting in a comprehensive assessment of more than 200 cases in Hebei Province.
Our analysis reveals notable disparities in vitality development levels across different regions.While the eastern region exhibits higher levels of economic development and vitality, the northern region faces challenges with lower activation levels.This underscores the importance of tailored strategies to address the unique circumstances of each area.Furthermore, the spatial visualization of vitality levels using Kernel Density Analysis highlights a bimodal activation spatial structure, with concentrations of villages exhibiting higher vitality in central and southern regions.Conversely, the balance analysis employing the coefficient of variation indicates varying degrees of balance across regions, with the southern region demonstrating the highest level of balance and the eastern region displaying the least favorable balance.Moreover, the analysis of regional activity patterns sheds light on the influence of macro social and economic factors on cultural landscape changes and population mobility.The eastern region emerges as a hub of social and economic activity, with dense road networks and elevated GDP levels, while the northern region faces challenges related to population and transportation.In light of these findings, it is crucial to consider the balance between regional socioeconomic activities and the rural revitalization to ensure sustainable protection and development.Extreme regional activity levels can pose obstacles to the material heritage conservation and cultural inheritance.Therefore, comprehensive strategies that prioritize the preservation of cultural heritage while promoting balanced socioeconomic development are imperative for the revitalization of traditional villages in Hebei Province.
To conclude, the RVA index evaluation system plays a crucial role in identifying traditional villages that are facing significant challenges in terms of vitality and development.By pinpointing those cases with critically low vitality, it enables proactive measures to prevent their decline and cultural degradation.Conversely, the system also identifies cases with higher vitality and development levels, serving as exemplary models for others to emulate.This methodology is not limited to Hebei Province but can be adapted and applied to other domestic regions and areas with similar requirements.It provides a robust framework for classifying targeted villages and assessing the effectiveness of rural revitalization initiatives.By leveraging this evaluation system, policymakers and stakeholders can make informed decisions to prioritize resources and interventions where they are most needed, ultimately contributing to the sustainable preservation and development of traditional villages nationwide.

Fig. 1
Fig. 1 Location of traditional villages in Hebei province in 2022.(Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C. Map Source: http://bzdt.ch.mnr.gov.cn/(accessed on 5 November 2023).
primarily analysed by considering the local and extra-local factors that affect the village's growth.Local factors include its level of classification and travel-friendly period, while extra-local factors include government initiatives to attract talent, new employment opportunities, external investment, and more.The development potential of a village can be evaluated based on several indicators, including strong social and urban influence, natural and environmental resources, beneficial external funding, an inclusive management system, and strategically implemented policies.

Fig. 2
Fig.2The analysis flow of the combined weighting method.

Fig. 3
Fig. 3 IPA analysis presenting four different strategic areas.

Fig. 4
Fig. 4 Ranking of RVA level of traditional villages in Hebei Province.(Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C.).Note: Some the scores are not displayed in this chart.

Fig. 5
Fig. 5 Spatial distribution of traditional villages with different revitalization levels in Hebei Province (Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C. Map Source: http://bzdt.ch.mnr.gov.cn/(accessed on 5 November 2023).

Fig. 6
Fig. 6 Four regions in Hebei Province based on climatic and geographical conditions.(Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C. Map Source: http://bzdt.ch.mnr.gov.cn/(accessed on 5 November 2023).

Fig. 7
Fig. 7 Median statistics of RVA zoning assessment results in Hebei Province (Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C.).

Fig. 8
Fig. 8 Regional economic development level of Hebei Province.(Data source: Statistical Yearbook of Hebei Province 2022).

Fig. 9
Fig. 9 Scores of the six dimensions of RVA in Hebei Province.(Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C. Map Source: http://bzdt.ch.mnr.gov.cn/(accessed on 5 November 2023).

Fig. 10
Fig. 10 Kernel density analysis of the multi-dimensional RVA of traditional villages in Hebei Province.(Data source: The Ministry of Housing and Urban-Rural Development of the P.R.C. Map Source: http://bzdt.ch.mnr.gov.cn/(accessed on 5 November 2023).
Cultural Ecology (e) Development Conditions (f) Development Potential

Fig. 11
Fig. 11 The coefficient of variation of the revitalization development level of traditional villages in the four regions (Data source: https://www.gscloud.cn/(accessed on 5 November 2023).

Table 2
Classification of Traditional Villages' Vitality Development Level.

Table 3
Subjective indexes after standardization of equal width segments.

Table 4
), it is evident that 191 villages exhibit a low vitality development level (V4), accounting for 92.72% of the total.Additionally, 14 cases have an average vitality development level (V3), accounting for 6.80% of the total.Only one village demonstrates an extremely low vitality development level (V5), making up 0.48% of the total.Traditional villages with extremely high (V1) and relatively high (V2) levels of vitality development constitute 0%.

Table 4
Statistical results after RVA evaluating traditional villages in Hebei Province (amount).

Table 5
Statistical results after RVA evaluating traditional villages in Hebei Province (proportion).

Table 6
Analysis of IPA quadrant characteristics in traditional villages in Hebei Province.