Sustainable Protection Strategies for Traditional Villages Based on a Socio-Ecological Systems Spatial Pattern Evaluation: A Case Study from Jinjiang River Basin in China

Abstract

Traditional villages have reached milestones in developing a living culture, politics, economy, and society, among other aspects, while acting as important carriers of agricultural culture formed by long-term interactions between humans and nature. Unfortunately, traditional villages could disappear with the advent of urbanization. Therefore, this study enhances the accuracy of traditional village classification protection work by examining traditional villages in the Jinjiang River Basin in Quanzhou, China. A spatial pattern is extracted for the socio-ecological systems (SES) prototype of traditional villages, and an SES classification protection system is constructed based on a prototype analysis. Given the evaluation results, a K-means cluster analysis is applied to establish the SES sustainability levels for six types of traditional villages. After adjusting the types according to the principles of sustainability, equilibrium, and individual cases, six SES system types are identified: SES decay and shrinkage (Type 1), SES fusion and development (Type 2), SES ecological decline (Type 3), SES social decline (Type 4), SES ecological conservation (Type 5), and SES extensive development (Type 6). This system provides a quantitative analysis method to classify and protect concentrated and contiguous traditional villages. It also helps facilitate a better understanding of local rural society, economy, and culture, especially a deeper understanding of the interactions between humans and the rural environment.

1. Introduction

Traditional villages are material and non-material cultural heritage sites with irreplaceable historical, cultural, architectural, and research value [1]. These villages are generally ancient, formed over 600 years ago. Rural areas have reached milestones in the development of a living culture, politics, economy, and society, among other aspects, while acting as important carriers of agricultural culture formed by the long-term interactions between humans and nature [2]. China’s Ministry of Housing and Urban-Rural Development and four other ministries define traditional villages as “villages that formed early, have rich traditional resources including agricultural products, forestry resources, cultural heritage, architectural heritage, and water resources, are relatively intact, and have high historical, cultural scientific, artistic, social, and economic value” [3]. The spatial expression of traditional villages reflects their evolutionary processes of formation, development, prosperity, decay, and regeneration [4,5]. They embody the wisdom deriving from the ancient Chinese living environment and provide useful inspiration for contemporary village planning and the revitalization of traditional villages [6,7]. However, traditional villages could face the challenge of disappearing with the occurrence of phenomena such as population decline and environmental destruction [8]. They generally face such problems as aging facilities and resources, a functional decline, and constructive destruction [9]. The sustainable development of traditional villages, referring to villages that have formed early, possess rich cultural and natural resources, and have specific historical, cultural, scientific, artistic, economic, and social values (definition from the province where this research is conducted, Fuzhou People’s Government website: http://www.fuzhou.gov.cn, accessed on 15 July 2024), has been widely discussed in academia [10,11]. From 2012 to 2019, the Ministry of Housing and Urban-Rural Development, the former Ministry of Culture (now the Ministry of Culture and Tourism), and the Ministry of Finance of the People’s Republic of China jointly listed 6819 traditional Chinese villages for rescue and protection [11]. These villages have become the largest and most distinctive agglomeration areas in the world’s agricultural civilization [12].

In 2022, Chinese departments, including the Ministry of Housing and Urban-Rural Development, Ministry of Culture and Tourism, and Cultural Relics Bureau of China, organized traditional village surveys and designated 1352 traditional villages with protective value (according to the government website: https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/202210/20221025_768248.html, accessed on 15 July 2024), indicating that the Chinese government has significantly increased its efforts to protect traditional villages in China. The protection of traditional villages is based on their being well-inserted into the local environment, which has been a particular concern [13]. Subsequently, the protection of traditional villages has entered an important stage in which social, cultural, and spatial protections are equally important [14].

In 1930, France promulgated the “Law on the Protection of Scenic Spots”, the first international document to include villages within the scope of cultural heritage protection [15]. In 1950, Japan’s “Law on the Protection of Cultural Properties” established a “traditional architectural group protection area” system [16]. In recent years, traditional village protections have gradually shifted from individual cultural heritage sites or historical buildings to the overall protection of rural settlements [17]. Consequently, concentrated and contiguous traditional villages have experienced long-term development, forming a socio-ecological system (SES) of rural settlements. Natural, economic, and social environments are jointly regarded as an ecological environment support system that interacts with the traditional village space and promotes the spatial evolution process [18,19]. Traditional villages’ spatial evolution is an orderly, dynamic process that involves a spatial adaptability transformation [20]. Previous research has shown that traditional villages should be preserved in their spatial form and development law [21]. Further, the SES of ancient villages is an important carrier of regional cultural protection and inheritance and is critical in promoting the protection and sustainable construction of traditional villages [22].

The socio-ecological system has a certain theoretical research foundation, but no relevant research applications have been found in the study of traditional villages. The study of the socio-ecological system has been divided into three stages, according to its origin, evolution, and rapid development [23]. In the first research stage, most studies use the qualitative description method to explore the origin of social work and the natural environment. Subsequently, this has been supplemented with the qualitative, descriptive method [24], such as cluster, principal component, and variance analyses [25].

From the perspective of ecological economics, the interaction between humans and the natural environment in general—that is, the socio-economic system and natural ecosystem—can form three states: the mutual promotion of sustainable development, the vicious circle of contradictions, and the mutual destruction of imbalance. The first state is the universally recognized “sustainable development” path that mankind should choose. Traditional villages’ SES generally evolves with changes in the political, economic, social, and natural environments and other comprehensive factors [26]. Finally, it manifests as a comprehensive material and cultural form in the spatial construction of traditional villages, including architectural, street, and overall spaces. Natural factors of traditional village spaces mainly include the regional terrain, while cultural factors include traditional cultural heritage and beliefs [27]. Economic factors include agricultural production and tourism [28]. Social factors include social structure, population density, population migration, policymaking, and social relations [29,30].

Sustainability science has significantly progressed in building the theoretical foundation of the SES [31] and designing conceptual frameworks to implement these theories [32]. A promising avenue of research involves searching for typically recurring pathways of SES changes and their outcomes [33]. Identifying the archetypes of such SESs and their variations has become an essential tool for an intermediate abstraction between case specificity and general interpretation. These prototypes reflect recurring patterns, processes, or actors in SESs and can be generalized or deduced. Hence, prototype analyses have become a central tool for significant types of sustainability studies used to identify human-nature interactions [34].

Current research on traditional villages has primarily focused on traditional village culture and its material carrier (e.g., building monomers, historical environmental elements, or the village space) [27]. Existing assessments focus only on the number of individual buildings that are required to be protected, the length or number of streets and alleys in traditional villages that must be transformed, and protecting the historical environment [35]. Therefore, the content of protection work is fragmented, and the protection and activation measures are poorly targeted, which makes it difficult to solve the problem of sustainable development among complex SESs in traditional villages [36]. On the one hand, studies of the traditional village spatial model are based on the traditional village culture, including the village’s location, landscape pattern, value system, and ritual order, among other traits. On the other hand, it is a multidisciplinary perspective that includes ecology, geography, landscape science, and new technologies [37]. However, studies from a cultural perspective focus on summary and induction and lack effective rational data support [38].

Moreover, integrations based on multiple disciplines are an important trend in traditional village studies [39,40], but quantitative evaluations of SES spatial patterns in traditional villages are still facing challenges. In terms of qualitative analysis, SES concepts and characteristics such as resilience, adaptability, and vulnerability have been studied [36,38]. However, these methods rely on researchers’ rich practical experience, subjective judgment, and analytical abilities. For quantitative, cluster, principal component, and variance analyses, GIS, RS, and other methods are typically used [37,38]. Research on the protection of traditional villages has become increasingly interdisciplinary, involving ecology, sociology, economic geography, and other scientific fields [40]. Unilateral or multi-angle comprehensive analysis makes it difficult to support a summary of SES spatial models of traditional villages and discern complex types. While there has been a significant increase in interest and research on socio-ecological systems (SESs) and their spatial dimensions, the greatest challenge is to develop appropriate statistical and computational techniques to analyze complex spatial data and model dynamic interactions, which is also a challenge in this study.

Based on previous research above, there is a certain degree of mutual influence between social, economic, and environmental factors in the socio-ecological system (SES) of traditional villages. Systematic classification and a more profound interpretation of SES concepts are needed [38]. The SES is a conceptual framework for the integration of human social systems and natural ecosystems [41], whose relationships ultimately formed a series of unique cultural and economic activities in traditional villages [37,38,39]. A well-functioning traditional village social ecosystem maintains a long-term dynamic balance between society and ecology, mutually reinforcing and cyclically developing.

In summary, this study uses traditional villages in Quanzhou’s Jinjiang Valley as an example to improve the accuracy of classifying and protecting traditional villages. It extracts the spatial pattern of SES prototypes of traditional villages to build an SES classification and protection system of traditional villages based on a nested prototype analysis. First, a K-means clustering analysis was used to classify the data features, and the classified samples’ clustering center characteristics were observed and studied. Finally, the characteristics of the SES spatial patterns were summarized and described for each type of spatial pattern. Optimization strategies and implementation paths for the different types were proposed based on this study. This contributes to a better understanding and analysis of the local rural society, economy, culture, and way of life [1,5,6], as well as a deeper understanding of the interaction between humans and environments [8,10,22]. This study involves theoretical and methodological approaches from such disciplines as rural geography, sociology, economics, and planning. The basic concepts of socio-ecological systems and related quantitative analysis methods are introduced in this study. Using typical concentrated and contiguous traditional villages in China’s Jinjiang River Basin as an empirical case study provides a reference for extracting spatial patterns that interpret the interaction between people and the environment in areas other than ancient villages.

2. Materials and Methods

2.1. Study Area

This study’s research area is the Jinjiang River Basin in Quanzhou City, Fujian Province, a southeast coastal area in China. In 2021, the Committee of the 44th World Heritage Conference approved the inclusion of Quanzhou as a “World Marine Trade Center of Song and Yuan China” on the World Cultural Heritage List. The Jinjiang River Basin is the third-largest basin in Fujian and an important corridor for inland connectivity and extension. Covering 51.1% of Quanzhou’s land area, the Jinjiang River Basin is densely populated with traditional villages that are closely connected to 22 heritage sites (Figure 1). The evolution and formation of traditional villages in the Jinjiang River Basin are closely related to their unique geographical environment and historical population migration and development. The current situation of traditional village protection still faces difficulties (Figure 2).

On the one hand, the geographical environment dominated by mountains, seas, and hilly terrain is often affected by heavy rainfall, resulting in traditional villages being located upstream of river intersections in mountain basins. On the other hand, due to the scarcity of local population and multiple historical population migrations, the tension on land has been further exacerbated, resulting in traditional villages’ economic industries mainly focusing on cash crops. Due to the need for foreign trade in cash crops, villages often choose to be located near waterways.

Traditional villages within the watershed have a socio-ecological system model driven by regional characteristics. There are many heritage resources within the study area, corresponding to features, space, society, and culture, which are important components of the socio-ecological system (Figure 3). Rural settlements in the Jinjiang River Basin have relied on its natural hilly landscape characteristics, with a long history of development. However, research on SES spatial patterns in contemporary conservation practices is lacking.

According to publicly available data from the Quanzhou Municipal Government, as of 2023, 92 traditional villages exist within the watershed, and Quanzhou city, as the trade hub of the ancient Maritime Silk Road, has reached 69.7% urbanization, creating more prominent contradictions in the protection and development of village culture. As local governments have invested more than 100 million yuan in village protection, a comprehensive spatial study of the Jinjiang River Basin’s traditional villages is representative of the overall protection and development of traditional villages.

2.2. Study Methods

This study examined the research methods and latest research progress on SESs in traditional villages [42], adopting a combination of quantitative and qualitative research methods. In terms of the sustainability level of SESs in traditional villages, intuitive quantitative data are used for the selected indicators to indicate its strength. At the same time, relevant local communities, stakeholders, and experts are invited to qualitatively score the relevant indicator data, using a score gradient to represent the strength of the sustainability level. When dividing the sustainability types of traditional villages, a combination of quantitative classification and qualitative adjustment is adopted to determine the sustainability types of traditional SES. K-means clustering analysis is adopted for preliminary division, and qualitative subdivision is conducted through on-site investigation and verification, along with qualitative testing through the spatial distribution results of kernel density.

(1)

Qualitative and quantitative research

The qualitative analysis focused on the SES’ connotations, concepts, and attributes, including resilience, adaptability, and fragility. It mainly used non-quantitative analysis methods, such as causal, comparative, and contradiction analyses. These relied heavily on the researchers’ practical experience, subjective judgment, and analytical ability.

The principal component analysis is a combined qualitative and quantitative analysis method [43]. The variance analysis is mainly used for an experimental analysis of the impact of single or multiple factors, which can be used to analyze and discuss key influencing factors. However, it is limited to the discussion and analysis of some aspects of the SES and is not applicable to quantitative extraction research of SES spatial patterns. Research on the protection of traditional villages has increasingly crossed over into multidisciplinary fusion research involving multiple scientific fields, such as ecology, sociology, and economic geography [43,44]. Comprehensive analyses from single or multiple perspectives make it difficult to support the summary and classification of SES spatial patterns of traditional villages and their complex types.

(2)

Cluster analysis

Cluster analysis is the process of categorizing and organizing data members that are similar to certain aspects of a dataset [45]. Previous studies have applied clustering algorithms to classify the appearance types of traditional villages [46,47]. Clustering is a technique used to discover the underlying structure and is often called “unsupervised learning” [48]. Further, K-means clustering is the most popular partitioning clustering algorithm; its simplicity and efficiency make it the most widely used among all clustering algorithms [49]. Given a set of data points and the desired number of clusters K specified by the user, the K-means algorithm repeatedly partitions the data into K clusters based on a distance function. The K-means clustering analysis method can perform type classifications based on data features without confirming the classification criteria, then observe and study the classified sample clusters’ cluster center features to summarize and describe the characteristics of each type’s SES spatial patterns. This method effectively avoids speculative bias in research results. It reduces subjective speculation that may lead to flawed research results, thus improving the scientific classification of SES spatial patterns to a certain extent.

(3)

GIS spatial analysis

This study used the tools in ArcGIS 10.0 to examine the spatial distribution density of traditional villages at the watershed spatial level. The traditional villages’ spatial village clusters could then be identified and divided to explain and understand the spatial pattern hierarchy of SESs in the Jinjiang River Basin.

• Nearest-neighbor distance and nearest-neighbor index

Point features have three types of spatial distributions: random, uniform, and clustered. The nearest-neighbor distance and index can be used to discriminate between them. The nearest-neighbor distance is a geographic indicator that represents the degree of adjacency between point features in a geographic space. Specifically, the distance $r_1$ between each point and its nearest neighbor is measured, and the average value of these distances $r_1$ is taken to represent the average nearest-neighbor distance, abbreviated as nearest-neighbor distance. When the point features in the studied area are randomly distributed using a Poisson distribution, the theoretical formula for the nearest-neighbor distance ($r_E$) can be expressed as:

$$r_E={\displaystyle \frac{1}{2\sqrt{m/A}}}={\displaystyle \frac{1}{2\sqrt{D}}}$$

(1)

where m denotes the number of points, A is the area of the region, and D is the point density. The nearest-neighbor index R is the ratio of the observed nearest-neighbor distance to the expected nearest-neighbor distance and is expressed as follows:

$$R={\displaystyle \frac{\overline{r1}}{r_E}}=2\sqrt{D{r}_1}$$

(2)

When R equals one, then $r_1$ = $r_E$, indicating that the point features are randomly distributed; when R is greater than one, then $r_1$ > $r_E$, and the point features are uniformly distributed; and when $r_1$ is less than $r_E$, then the point features are clustered.

• Kernel density estimation method

Kernel density estimation is a method of spatial distribution density estimation in ArcGIS software that is mainly used to describe the probability of events occurring at a certain location in a geographical space. The more (or less) dense the points, the higher (or lower) an event’s probability. Supposing a sample point set is sampled from the population of the spatial distribution density function {${\mathrm{x}}_1$,${\mathrm{x}}_2$, ${\mathrm{x}}_3$……${\mathrm{x}}_{\mathrm{n}}$}, the kernel density estimate is $F_{\left(x\right)}$ at point x, expressed as:

$$F_n(x)={\displaystyle \frac{1}{nh}}{\sum }_{i=1}^{n}k\left(\right(x-x_i)/h)$$

(3)

where $x-x_i$ is the distance between point x and event $x_i$, $k\left(\right(\mathrm{x}-{\mathrm{x}}_{\mathrm{i}})/\mathrm{h}$) is the kernel function, n is the number of points, and h (h > 0) is the bandwidth. The kernel function and bandwidth are the main factors affecting the kernel density estimate.

(4)

SPSS analysis method

Given the different dimensions of all types of data collected, it was necessary to eliminate the data’s dimensional influence to conduct a quantitative evaluation. For simplicity, this study used the linear dimensionless SPSS analysis method to normalize the data and quantify the value of each evaluation index to [0,1]. First, the maximum (max) and minimum (min) values in the quantified data are identified. Secondly, the raw data (x) in each indicator are standardized using the following formula:

X’ = 0.1 + (x − min)/(max − min) × 0.9

where x’ is the standardized data value.

The method of “minimum, maximum standardization” can preserve the distribution characteristics of the original data and is suitable for the processing and analysis of numerical data in this case. This study applied this standardization method three times: first, the standardization of the quantified three-level indicators; second, the secondary standardization after aggregation into secondary indicators; and third, the three rounds of standardization after collecting the third-level indicators.

Figure 4 illustrates the road map regarding the technological processes used in this study’s analysis.

Data and Materials Acquisition

This study selected all 44 traditional villages on the list of Chinese traditional villages in the Jinjiang River Basin as research samples. The data and information were obtained through three methods: a data search, field investigation, and software acquisition. Among these, the field investigation information and data were primarily used, and mutual verification of the three data types ensured their objectivity and validation [47]. The data collection was supported by the Department of Housing and Urban Rural Development of Fuzhou Province and the Fuzhou Planning and Design Research Institute Group in 2023. During the research process, personal information is not disclosed to the public.

(1)

Traditional data

Historical and current information on economic development, industrial composition, social population, and other aspects of the traditional villages’ region originated from the government’s annual bulletin on social and economic development, government statistical yearbooks, and other documents from the government website https://www.quanzhou.gov.cn. The historical information regarding economic development, industries, the social population, and other aspects of traditional villages was obtained from the survey and recommendation form responses of traditional villages in Fujian Province, traditional village archives and protection, development planning, and other documents; existing academic research results are also critical supplementary sources. This study ensured the data sources’ authenticity and integrity by obtaining data from official public documents released by the government and academic websites in 2023. Due to the long formation time and relatively slow changes in traditional villages, this study mainly discusses the SES classification of traditional villages in Jinjiang. It proposes protection measures based on relatively comprehensive data and research results obtained in 2023.

(2)

Survey data

This study avoided mismatches between traditional village archival data and actual data by conducting field research to verify and supplement the data. Many comprehensive field investigations supplemented and validated the historical information from traditional villages in 2023. The current information collected included statistics on economic income, population, intangible cultural heritage, traditional buildings, and infrastructure.

(3)

Open data

In spite of field investigation and government statistics collection processes from the government website https://www.quanzhou.gov.cn, some data from the traditional villages were still missing. For example, most of these villages’ relevant documents focused on information about traditional architecture, culture, and infrastructure. However, historical and current information reflecting their green space and water surface was ignored, and it was difficult to obtain comprehensive information from existing literature. Therefore, with the help of Google Earth, GIS, ENVI, CAD, and other software, statistics regarding traditional villages’ green spaces and water surfaces were effectively verified by collecting and analyzing satellite images [50]. However, remote sensing technology has certain limitations in filling data gaps, mainly including difficulties in data processing, interpretation, and verification of remote sensing images and limited real-time accuracy. Therefore, as supplementary information for on-site research, it assists in village classification.

2.3. Constructing the SES Sustainable Development Evaluation Index System

2.3.1. Construction Principle

The selection of indicators should follow several principles. First, systematization implies that indicators should comprehensively reflect the system’s overall characteristics and conform to all aspects of traditional villages’ sustainable development. The indicator system should reflect all significant components, such as the economy, society, culture, and ecology. Second, the selected indicators’ feasibility should consider the difficulty in acquiring data and the operability of quantifying the indicator. Third, comparability is involved when the selected indicators’ connotations are universally applicable among traditional villages, facilitating a comparative study. Fourth, the comprehensive principle impacts the index’s construction, as qualitative, quantitative, comprehensive, and scientific methods can be combined to reflect the traditional villages’ sustainable development level [51].

In the process of forming a classification system, in terms of society, the attribute characteristics of traditional village history and culture should be considered first, and both material and non-material cultural aspects should be considered and extended. At the same time, consideration should be given to the social attributes and characteristics of individuals, starting from the main social factors that are dominated by people. Finally, economic factors that support human social activities should be considered, starting from their industries, land, income, and other aspects. In terms of ecology, while considering the natural environment and resources of the location, the coordination relationship between the ecological environment and the artificial environment formed by the combination of humans should be considered, and its relationship with development should be further measured, as shown in Figure 5.

2.3.2. Construction Framework

Constructing this study’s index system involved a two-way sorting and determination process. Initially, the first-level index framework was determined from the socio-ecological theory and sustainable development perspectives. Second, existing policy documents and research results from existing experts and scholars were considered to form a three-level index database, which parallels many close evaluation system-construction studies. Finally, a two-level index system was determined by two-way induction between the primary and tertiary indices, combined with existing research results.

2.3.3. Index and Weigh of the Evaluation System

This study measured the degree and characteristics of traditional villages’ sustainable development under the framework of socio-ecological and sustainable development theories [52]. This was combined with the traditional villages’ historical and cultural characteristics and the social system and ecosystem, based on the sixth batch of the Traditional Village Survey Recommendation Form [40,52]. By referring to the Evaluation Index System of Traditional Villages in 2012 and the Evaluation Index System of the Seventh Batch of Famous Towns and Villages of Chinese History and Culture in 2017, as well as relevant literature [53,54,55], the first-level “social system and ecosystem” indicators were comprehensively determined [53,54,55,56,57,58]. The “social inheritance degree”, “social stability”, “social and economic productivity”, “natural resources’ richness”, “close degree with development”, “historical style”, and “degree of natural environment coordination” were also considered, resulting in 6 secondary indicators and 26 tertiary indicators [54,55]. These included 14 third-level indicators for reference, and 12 new indicators were investigated [53,56].

The evaluation indicators were forward- and reverse-scoring indicators, as shown in

Table 1. SES sustainable development evaluation index system.

Category	Index	Metric Breakdown	Rank in Importance	Weight
Social system	Social inheritance	Types of tangible cultural heritage (pcs)	1	0.386
		Types of intangible cultural heritage (pcs)	2	0.193
		Protected List level	3	0.129
		History (years)	4	0.096
		Publish the batch	5	0.077
		Number of anecdotes (pcs)	6	0.064
		Number of important historical figures (pcs)	7	0.055
	Social stability	Number of resident population (person)	1	0.480
		Number of nationalities (pcs)	2	0.240
		Number of family surnames (pcs)	3	0.160
		Number of registered population (person)	4	0.120
	Social and economic productivity	The per capita annual income of the villagers (yuan)	1	0.438
		The annual income of the village collective (10,000 yuan)	2	0.219
		Number of major industry types (cash crops) (pcs)	3	0.146
		Cultivated land area per capita	4	0.109
		The straight-line distance between the center of the village and the main road (the nearest national or provincial highway) (km)	5	0.088
ecosystem	Abundance of natural resources	Number of vegetation species (pcs)	1	0.545
		The area of the water (ha)	2	0.273
		The width of the water system (m)	3	0.182
	The closeness with development	Type of terrain	1	0.480
		Altitude (m)	2	0.240
		Village area (mu)	3	0.160
		The area of the village (km²)	4	0.120
	The degree of harmony between historical style and natural environment	The harmony between the village and the surrounding natural environment	1	0.545
		Pattern integrity	2	0.273
		The integrity of the style, historical authenticity, and spatial pattern characteristics of the core protected area	3	0.182

. Among the 26 indicators, 23 were positive-scoring, while three—the history of construction, the published batch, and the linear distance (in kilometers) between the service village center and the main road (the nearest national or provincial road)—were calculated using the reverse-scoring method. The third-level sustainability index, which is within the second level’s range, was then weighted. The fuzzy evaluation method was used to assign weights to quantify the degree of sustainability of SESs in traditional villages. Through the analysis and rating comparisons of expert evaluators, the field investigation, and research analysis, this study conducted pairwise comparisons to judge the importance of the tertiary indicators within the range of six secondary indicators and sorted them by importance. A combination of the Analytic Hierarchy Process and Fuzzy Evaluation method was used to calculate the weight values of the tertiary indicators within the range of the secondary indicators. Thus, the degree of SES secondary and tertiary sustainability indicators for traditional villages was quantified. In doing so, this study provides a basis for a subsequent discussion of the equilibrium or coupling relationship between social systems and ecosystems through cluster analysis.

3. Results

3.1. Evaluation and Analysis of the SES Sustainable Development Level

Index Evaluation and Clustering Results

Quantifying SES sustainability indicators provided comprehensive data values to reflect the social system and ecosystem indicators of sustainable development among 44 traditional villages in the Jinjiang River Basin. A K-means cluster analysis of three to eight categories was conducted on 44 comprehensive datasets. An analysis of variance (ANOVA) table of the K-means cluster analysis for Categories 3 to 8 was observed and analyzed. When cluster number K equals six, then the mean square error of both the social system and ecosystem is at an overall minimum value of 0.007 with a significance value less than 0.05, indicating that the clustering significance is strong. Simultaneously, observing the histogram of each classification’s final clustering center illustrates that K = 6 reveals more obvious clustering features, and the SES sustainable features are more consistent among the cases in each category. Therefore, this study set the number of clusters as six categories. Simultaneously, observing the histogram of the final cluster center of the cluster inquiry attempt for Categories 3 to 8 indicates that its clustering features are more obvious when K = 6, and sustainable SES features are more consistent among the cases in each category (Figure 6).

According to the clustering results, the six categories exhibited clear differences, and the clustering effect was greater if the distribution was uniform. The point distribution in the scatterplot demonstrates a relatively uniform and clear overall distribution (Figure 7a). The distribution characteristics derived from the social and ecological values of the final cluster center were relatively obvious (Figure 7b).

The cluster analysis revealed six SES types and the following factors were integrated to individually adjust and classify the levels of sustainable development (see

Table 2. List of SES sustainability level types of traditional villages in Jinjiang River Basin.

Characteristics of Sustainable Development		Comprehensive Evaluation of Sustainable Development Level	Equilibrium Coupling State
System Characteristics	Main Characteristics of Subsystem
Fusion developmental type	The sustainable level of the social and ecological subsystems is relatively strong and generally in a relatively balanced state	Stronger	Universal equilibrium
Extensive development type	Compared with the ecological subsystem, the social subsystem is in a strong position, and the overall sustainability level is medium	Medium	General imbalance
Ecological conservation type	Compared with the social subsystem, the ecological subsystem is in a strong position, and the overall sustainability level is medium	Medium
Social frailty type	The sustainable level of the social and ecological subsystems is weak, and the sustainable level rate of the social subsystem is lower than that of the ecological subsystem	Weaker
Ecological asthenic type	The sustainable level of the social and ecological subsystems is relatively weak, and the sustainable level rate of the ecological subsystem is lower than that of the social subsystem	Weaker
Decline atrophy type	The sustainable level of social and ecological subsystems is weak	Weak	Relative equilibrium

). First, this study considered the degree of sustainability of social systems and ecosystems, as this directly reflects the sustainability of traditional villages. The second step involved considering the system balance, as the balance between human (social system) and natural systems is the premise of the sustainable villages’ healthy and sustainable development. Third, unusual cases were considered. Observing the clustering and comprehensive field investigation results led to reasonable adjustments made to abnormal cases.

We subsequently used a socio-ecological framework and multi-source data to assess the sustainability of SESs in 44 traditional villages in the Jinjiang River Basin. The cluster analysis and comprehensive field investigations facilitated the identification of six SES types: SES decay and shrinkage (Type 1), SES fusion and development (Type 2), SES ecological decline (Type 3), SES social decline (Type 4), SES ecological conservation (Type 5), and SES extensive development (Type 6).

According to each type’s overall sustainability evaluation, the sustainability level can be divided into integrated development (Type 2), extensive development (Type 6), ecological conservation (Type 5), social weakness (Type 4), ecological weakness (Type 3), and decay atrophy (Type 1).

3.2. SES Sustainable Development Type Characteristics

Based on the SES sustainability evaluation system framework constructed for traditional villages in the Jinjiang River Basin and the quantification of multi-source data, a cluster analysis and comprehensive field research were conducted to summarize and refine the system. Six SES system types were identified according to their sustainability levels, social and ecological balance, and other characteristics: SES decay and shrinkage (Type 1), SES fusion and development (Type 2), SES ecological decline (Type 3), SES social decline (Type 4), SES ecological conservation (Type 5), and SES extensive development (Type 6). Figure 8 and Figure 9 illustrate their distribution and the following characteristics, respectively.

The SES ecological and social weakness type (Type 1) is characterized by weak social and ecological sustainability levels (sustainable level of approximately 0.2). It is in a relatively balanced coupling state, with weak sustainability, distributed in the Jinjiang River Basin’s middle and lower reaches and mainly near urban construction areas.

The SES ecological and social balanced type (Type 2) is characterized by strong social and ecological sustainability levels (sustainability level greater than 0.4). It is in a relatively balanced coupling state with strong sustainability. It is mainly distributed in the middle and upper reaches of the Jinjiang River Basin. It is significantly closer to the end of the basin, exhibiting characteristics of discrete and independent development in its spatial distribution.

The SES ecological weakness type (Type 3) is characterized by relatively higher social sustainability than ecological aspects (social sustainability level is approximately 0.4, and ecological sustainability level is mostly less than 0.3), with a comparative advantage in social aspects. Medium sustainability is mainly distributed in the basin’s middle and upper reaches, and most are located in mid-mountain areas.

The SES social weakness type (Type 4) is characterized by higher ecological sustainability than the social aspect (the ecological sustainability level is about 0.4, and the social sustainability level is mostly less than 0.3), with a comparative advantage in the ecological aspect and medium sustainability mainly distributed in the middle of the Jinjiang River Basin and near the main water system areas.

The SES ecological conservation type (Type 5) is characterized by its ecological sustainability, which is approximately twice that of the social aspect; this is an absolute ecological advantage. It is medium-sustainable and is mainly distributed in the middle of the Jinjiang River basin and near the main water system areas.

The SES extensive development type (Type 6) is characterized by its social sustainability (social sustainability level is greater than 0.6), which is approximately twice that of the ecological aspect. It is dominant in terms of social aspects and has medium sustainability. This is distributed in the middle of the basin, and most are located at the intersection of water systems and main traffic roads.

Generally, traditional villages in the middle and upper reaches of the Jinjiang River Basin exhibit more sustainable trends than those in the lower reaches with urbanized areas. This manifested as increased sustainability from the lower to the upper reaches of the river basin and increased sustainability diffusion from the urbanized to the mountainous rural areas (Figure 10).

The internal and external connections between traditional village society and the ecosystem objectively exist, which is the basis for the traditional “village by village” protection model to shift towards cluster protection exploration. There are obvious advantages and disadvantages among the types of SES sustainability levels in the Jinjiang River Basin, manifested as strong, medium, and weak complementary strengths (see Figure 11). Strong complementarity is reflected in both social and ecological systems, where each has one aspect that is stronger than the other, and the gap between these two aspects is significant. The moderate complementary strength is reflected in the fact that each aspect of society and ecosystem is stronger than the other, but there is not much difference in one aspect. Weak complementarity is reflected in social systems and ecosystems where both are strong or weak.

3.3. Spatial Distribution Characteristics of Traditional Villages in the Jinjiang River Basin

The ArcGIS average nearest-neighbor spatial analysis tool was used to identify and verify the overall spatial distribution characteristics of the Jinjiang River Basin’s 44 traditional villages (see Figure 12). The analysis results revealed a Z-value of −3.093301, which was the minimum negative value, and a p-value of 0.001979, which was the minimum probability value. Therefore, the Jinjiang River Basin’s 44 traditional villages exhibit obvious clustering characteristics in terms of spatial distribution and do not have random distribution characteristics. From the results of cluster quantification analysis and the spatial distribution of kernel density, the six cluster results have a certain degree of credibility. This is the premise of the spatial-level discussion, from the follow-up cluster analysis of SES sustainability in traditional villages to the cluster model study.

3.4. Delineation of Contiguity of Traditional Villages

Cultural heritage protection focuses on the individual and features. It also involves protecting material form and appearance and the sustainability to be inherited through cultural values. With the idea of integrating cultural resources, the identification and demarcation of centralized contiguous protected areas are crucial in the traditional regions’ sustainable development.

This study acknowledges that coordinating and integrating village resources within different administrative units can be challenging. Still, villages can address this by following the traffic-trunk connectivity principle. Second, the principle of landform continuity must be followed, as water systems and mountain ranges significantly influence communication between villages. Finally, the principle of consistency in administrative management must be followed, as administrative units are an essential category for coordinating resources.

Through changes in understanding, this study considers the impacts of transportation, topography, and administrative management on the spatial connectivity and accessibility of people’s activities and the interaction of human activities to denote five centralized contiguous protection areas (Figure 13). The delineation of the contiguous traditional villages in the Jinjiang River Basin should also consider the principle of consistency with administrative management. Due to the administrative division system of “provincial (city)-county-level-township level” in China, the scope of this study involves a three-level management system of “prefecture (city)-county-level-township level”, where each village is directly under township level management and belongs to the county level. The current prefecture (city) level is Quanzhou City, involving mainly Yongchun County, Anxi County, Nan’an City, etc. At the same time, according to the “Regulations on the Protection of Historical and Cultural Cities, Towns, Villages and Traditional Villages in Fujian Province”, the administrative management of traditional villages is subject to the city and county people’s governments. Therefore, the research on the delineation and protection mode of this contiguous area should fully consider the consistency with the county-level administrative management while also ensuring the smooth connection between the protection mode, strategies, and management methods.

(1) Concentrated contiguous Area 1. The concentrated area is located in the middle reaches of the Jinjiang River Basin, with traditional villages distributed around the built-up area of Yongchun County, mainly concentrated in the southern area of the county, at the intersection of important transportation arteries, important waterfront areas, and water systems. The degree of aggregation is high, with most traditional villages located on flat terrain in mountainous basins and some on high mountain landforms. The sustainability level is at a medium to low level, and the overall system is generally imbalanced, with a convenient location advantage for external transportation. This area includes Yongchun County, with 21 villages and three integrated development villages (Xixi, Helin, and Xichang), all of which are relatively independent and dispersed. There are three decaying and shrinking types (Longshui, Wujiang, and Dayu), which are scattered and located in the fringe area of traditional village concentration; social weakness Type 7 (Maoxia, Tangxi, Shanhou, Puxia, Jiaji, Dayan, and Detian), relatively concentrated, in a close state; and two extensive development types (Hankou and Panxi) are located on the expressway or the important waterfront area in the historical water system, where transportation is more convenient and diplomacy is more complete. There are three ecological conservation types (Pu Shang, Dongli, and Xi’an), which are close to mountainous areas and have relatively good ecological environment preservation practices. Three villages are ecologically weak (Huamei, Putou, and South American Hui Village) and located in a construction area with a certain population gathering and an environment significantly affected by daily construction. Overall, the traditional villages in this contiguous area are close to Yongchun County. These types primarily include social weaknesses, and the number of other types is balanced.

(2) Concentrated contiguous Area 2. The concentrated contiguous area is located in the middle and upper reaches of the Jinjiang River Basin. Traditional villages are distributed along the Anxi section of the Zhengyong Shaxia Expressway in the western part of Anxi County, located at the intersection of important transportation arteries, important waterfront areas, and water systems. The degree of aggregation is low, and most traditional villages are located on flat terrain in mountain basins, with some located in high mountain landforms. The sustainability level is at a moderate level, and the overall system is relatively balanced, with certain advantages in external transportation connections. This centralized contiguity area includes the Zhengyong-Shaxian Expressway Anxi section, with eight villages and three integrated development types (Huer, Wenquan, and Wuhythi). One is relatively independent, while the other is located in the town construction area. Its advantages and characteristics involve relatively well-integrated development: rancorous atrophy Type 1 (Shangzhi), extensive development Type 2 (Husan and Heqian), in a population-gathering construction area; one ecologically weak type (Longju), located halfway up the mountain valley; and one ecologically weak type (Longtong), located in the upper reaches of the basin. Overall, the villages in the concentrated contiguous area are relatively dispersed and independent and are mainly dominated by integrated development and extensive development villages.

(3) Concentrated contiguous Area 3. The concentrated contiguous area is located at the end of the middle reaches of the Jinjiang River Basin. Traditional villages are distributed on both sides of the high mountains along the Xiaolanxi River system in Anxi County, with a relatively high degree of aggregation. All traditional villages are located on the mountainside of the high mountain terrain. External transportation mainly relies on regional transportation arteries, and the efficiency of communication with the outside world is relatively low. The traditional village SES in this concentrated contiguous area is dominated by general equilibrium and relative equilibrium types, so the overall system balance of this contiguous area is general equilibrium. This involves the Xiaolanxi centralized contiguous area of Anxi County. Eight villages, including three integrated development types (Shipan, Nanyan, and Shantan She), are relatively independent and dispersed, with decay and atrophy Type 3 (Yaoshan, Songyan, and Yaoyang).

(4) Concentrated contiguous Area 4. The concentrated area is located in the middle and lower reaches of the Jinjiang River Basin. Except for Duoqiao Village and Zhangzhou Liao Village, which are located on the water system and transportation arteries, the other three traditional villages are distributed on the mountainside of Shigu Mountain in Nan’an City. Among them, Zhangzhou Liao Village is located next to the city, far away from other villages in the concentrated area, and the overall concentration is not high. External transportation mainly relies on regional transportation arteries, and the efficiency of communication with the outside world is relatively low. The overall system balance of the series is unbalanced. This includes the Shigushan centralized contiguous area of Nan’an City, with four villages, three of which are decaying and shrinking (Guanshan, Tianshan, and Duoqiao), and one of which is ecologically weak. Overall, the concentrated contiguous area is relatively loose and located in mountainside areas, with overall weak sustainable development trends.

(5) Concentrated contiguous area 5. The concentrated contiguous area is located at the end of the downstream water system in the Jinjiang River Basin, close to the urban area of Luojiang District, on the mountainside and mountain edge of the high mountain terrain, with a general degree of aggregation. External transportation mainly relies on regional transportation arteries and highways, with proximity to highway intersections, resulting in high communication efficiency with the outside world. The sustainability level is weak, the overall system is imbalanced, and the efficiency of external transportation connections is low. This includes the Luoxi centralized contiguous area of Luojiang District, with two villages, of which one is of the extensive development type (Wengshan) and one is ecologically weak (Xindong).

4. Discussion

4.1. Discussion and Analysis Based on Survey Results

Villages are affected by both internal and external factors. Given a basic analysis of the geospatial characteristics, the external geospatial channel is an important way in which the external system affects the village system. Simultaneously, in exploring the protection and development of traditional villages under the SES sustainability evaluation framework constructed in this research, the characteristics and level of sustainability of each type and village were obtained, and the impacts of external influencing and internal supporting factors were analyzed. In terms of the external influencing factors, the promoting force of the system should be improved. Regarding the internal supporting elements, the system’s promotional force should be improved by integrating internal elements. Therefore, a protection mode and strategy for this cluster should be proposed based on space limitations and the evaluation results of the Jinjiang River Basin’s sustainability. There are still certain limitations in the spatial analysis and background analysis of the distribution of traditional villages, and the proposal of protection strategies mainly targets government-led policy formulation.

4.2. Discussion on SES Spatial Distribution Characteristics

The sustainability level is significantly affected by urbanization construction, showing a trend of traditional villages in the upper and middle reaches of the watershed being more sustainable than concentrated urban areas downstream. Sustainability is enhanced from the downstream to the upstream of the watershed, and sustainability diffusion is enhanced from urban built-up areas to mountainous rural areas. The sustainability level of traditional villages on transportation arteries is generally strong. Meanwhile, there are a few relatively independent and closed traditional villages that demonstrate a strong level of SES sustainability.

In terms of spatial distribution, traditional villages in the middle reaches of the Jinjiang River Basin are relatively concentrated and account for most of the population, with very few in the urban built-up area adjacent to Quanzhou City and only one village (Zhangzhou Liao Village). This indicates that traditional villages are greatly affected by urbanization, and it is difficult for them to survive and develop around the central construction areas of Quanzhou prefecture-level cities. The sustainability of SESs in traditional villages near urban built-up areas is generally low. The sustainability level of SESs in traditional villages around county-level cities and near major transportation roads is generally high. However, there are also a few traditional villages that are neither close to urban built-up areas nor relatively far from transportation arteries. They maintain a certain level of independent development and have relatively strong SES sustainability, such as Wupei Village, which is located at the end of the watershed.

To further analyze the impact of urban built-up areas on the sustainability of the SES in traditional villages, the general spatial distance relationship between each category of traditional villages and urban built-up areas is divided into (see

Table 3. Summary of coupling balance classification for various types of SES.

Category	Mean Sustainability Index		Coupling Status of Social Ecological System
	Social System (S)	Ecosystem (E)
SES Type 1	0.545	0.427	Universal equilibrium (Ue)
SES Type 2	0.705	0.259	Universal imbalance (Ui)
SES Type 3	0.355	0.765
SES Type 4	0.245	0.504
SES Type 5	0.450	0.229
SES Type 6	0.226	0.245	Relative equilibrium (Re)

): Adjacent (Ad) > Near (Ne) > Away from (Af).

4.3. Discussion on Causes of Different Sustainability of SES Types

To further explore the causes of the different sustainability of each SES type, based on secondary indicators, we conducted an overall analysis of the driving degree of internal and external factors in the system. By summarizing the 26 identified tertiary indicators, it was found that six secondary indicators serve as driving factors for measuring the internal and external impact on the sustainability of villages in the Jinjiang River Basin, including “social heritage (S1), social stability (S2), socio-economic productivity (S3), natural resource richness (E1), closeness to development (E2), and coordination between historical features and natural environment (E3)”.

Among them, the three secondary indicators that constitute the ecosystem mainly reflect the internal driving force of the village system. The three secondary indicators that constitute the social system mainly reflect the driving force of the internal and external forces of the village system under the mixed influence of internal and external factors. Combining the sustainability evaluation results of six types of SES, it was found that the higher the overall sustainability level of their influencing factors, the greater the driving force.

Furthermore, the degree to which traditional villages are driven by internal and external factors is a key factor affecting the sustainability level of the SES. The sustainability of traditional villages in the Jinjiang River Basin is more affected by external factors than internal factors.

Meanwhile, based on the spatial distribution of various types, external factors mainly refer to indicators related to urbanization construction, while internal factors are influenced and interfered with by external factors. The sustainability of the SES in traditional villages in the Jinjiang River Basin is influenced by both internal and external indicators of the system (see Figure 14).

Further analysis of the influence of driving force shows that its overall strength is divided into Strong Driving Force (Sd) > Medium Driving Force (Md) > Weak Driving Force (Wd) > Low Driving Force (Ld). Based on the analysis of the characteristics of SES sustainability levels in terms of system balance and spatial distribution, combined with the analysis of dynamic mechanisms, six spatial correlation patterns have been formed (see Figure 15).

4.4. Cluster Protection Mode Policy

Traditional villages are farming settlements that rely on land and other resources. The region’s traditional villages have inseparable material and information exchange activities. It is difficult for a single traditional village to form a regional culture, as inter-correlations between individuals are lacking. Cultivating a regional farming civilization is also difficult. Therefore, the cluster refers to a series of social, cultural, and economic relationships among settlements within a certain regional space, including spatial continuity and non-material interactions between cultures.

Based on the quantitative evaluation of the SES and traditional villages’ sustainable development, this study’s research on the cluster protection mode builds a path for this cluster protection mode from three levels: single village, centralized contiguous village, and watershed cluster protections.

Under the premise of integration and considering the hierarchical relationship between these three levels [52,56], the following cluster protection mode strategies are proposed: a single village implements a self-element optimization strategy; centralized contiguous villages implement a centralized and contiguous sharing and co-governance development strategy; and the basin cluster implements an overall planning strategy driven by the integration of value across the basin (see Figure 16).

4.4.1. Basin Planning Strategy

At the basin level, an overall strategy driven by value integration in the basin cluster is implemented, with a “village + region” + urban-rural linkage (Figure 17). First, regarding the village + region component, the Quanzhou World Cultural Heritage Site should rely on governance in the watershed spatial environment and further embed itself in the protection and inheritance system of world cultural heritage values. In doing so, this site should be enriched, further enhancing the cultural influence of traditional villages in the Jinjiang River Basin.

Second, regarding the urban-rural connection, relying on trunk roads strengthens their connectivity and driving role. These roads can create a more convenient transportation mode between urban and rural areas. Citizens should also rely on the cultural advantages of traditional villages, including cultural heritage buildings, cultural customs, and landscape features [59], establish interactions involving cultural supply between cities and villages, and promote the protection and inheritance of traditional villages with rural revitalization and the rural cultural tourism industry.

Third, consistent development among traditional villages must be coordinated, the timing of this development must be arranged accordingly, and development must be driven from specific points and areas [44].

4.4.2. Continuous Group Development Strategy

A development strategy should be implemented that involves village-sharing and co-governance at the centralized contiguous level as proven by Jinxin Zhu [54], as well as connections between countries’ and towns’ co-governance and traditional villages, led by the county government and coordinated among village governments to implement governance policies. First, co-governance with counties near the urban areas of Yongchun County, such as Xi’an (Type 5), Putou (Type 3), Wujiang (Type 1), and Dayu (Type 1), should occur according to their sustainable development evaluation level to implement integrated development and governance strategies with the county and town.

Second, development strategies should consider that these villages are linked (see Figure 18), as proven by Chengcai Tang [55]. For example, the traditional villages on the south side, which are located a certain distance from the county seat of Yongchun, are traditional villages with beneficial SESs. Their strategies can rely on ecology and center on society-oriented villages to establish public service facilities at their center, such as tourism and cultural activity centers, and implement joint construction and sharing procedures to promote interaction among the villagers. Ultimately, this will promote the inheritance and continuation of area heritage buildings, cultural customs, and landscape features protection [60].

4.4.3. Governance Strategies for Optimizing Village Space

From the evaluation results of the indicator system, in the course of promoting the sustainable optimization of traditional village communities, attention should also be given to the self-optimization strategies of individual traditional villages as proven by Wang Zhaofeng [59]. Based on the measurement results of the indicators, the protection and control of heritage elements should be prioritized for optimization. In the formulation of governance measures, sustainability evaluation analysis should serve as the basis to identify the strengths and weaknesses of the individual villages’ own development. Systematic governance should be conducted by further excavating cultural resources and meeting the public space needs of villagers and adopting spatial system optimization design to enhance the sustainability of villages.

Firstly, with regard to the protection of heritage elements, further investigate the fundamental elements of heritage protection in each village and maximize the exploration of cultural resources that have not been utilized, enriching the content and connotation of protection elements. Stringently control the surrounding historical environmental elements, maintain the authenticity of the village’s historical environment and coordinate the overall style to the greatest extent possible, protect the traditional landscape pattern, and thereby enhance the quality of the entire village’s cultural spatial environment. Strengthen the excavation and inheritance of cultural heritage value, mobilize the initiative of villagers, combine modern information technology and other means, enhance the ability to preserve and showcase the physical cultural heritage of villages, and improve the new ability to inherit traditional village culture.

Secondly, optimize spatial elements, as proven effective by Huang Tingwan [51]. Further identify the traditional landscape pattern space and use it as the background support for the overall spatial environment framework of the village and coordinate the overall spatial relationship of the village. Identify the public space needs of villagers in the village (street and alley spaces, important node locations, courtyard spaces, etc.) and existing unused open public spaces, and use the overall improvement of important open public space renovation design to meet the cultural activity space needs of villagers and enhance the comfort and frequency of their use of open spaces.

5. Conclusions

Given the rapid urbanization and increasing efforts toward rural revitalization and the protection of traditional villages in recent years [54,55,60], this research faces significant challenges, such as achieving an accurate classification of resources and overall protection of village groups. Jinjiang Valley, where traditional villages are highly clustered, was taken as an example. In view of various issues—such as the obstruction of the coordinated development of social and cultural inheritance and the ecological environment and the lack of accurate and effective measurement for SES composite spatial carriers—the SES spatial model of traditional villages in the Jinjiang Basin was quantitatively extracted.

The sustainable development level and types of 44 traditional villages in the Jinjiang Basin were then quantified and divided by applying an SES-based theoretical framework and combining this with a cluster analysis. Traditional villages in the Jinjiang River Basin can be divided into six types (integrated development, extensive development, ecological conservation, social weakness, ecological weakness, and decay and shrinkage), with different sustainable development levels. A cluster protection model and strategic measures were then proposed to overcome two difficult problems: an insufficient understanding of traditional village classification protections and the low-efficiency utilization of resources caused by village-based protections.

From this research perspective, this study covers traditional village functions, space, society, and culture, among other aspects, and constructs a more systematic and comprehensive quantitative evaluation index system given this study’s SES cluster protection model, opening a new research perspective. In terms of research methods, this study first determined a quantitative evaluation index system for SES sustainable development based on the society-ecosystem theory, established a database, applied the K-means cluster analysis method to cluster the data samples of the sustainable development level of traditional villages, and observed and summarized the clustering results combined with field investigations. This confirmed the types of SES sustainable development levels in the Jinjiang River Basin’s 44 traditional villages.

Second, a quantitative evaluation of the traditional villages’ sustainable development level and an analysis of the type characteristics were considered to explore this basin’s cluster protection mode from the single-village perspective. The contiguously centralized results led to this study’s proposed corresponding strategies. Generally, this study constructed a set of research methods involving the “quantitative evaluation + cluster analysis” of the traditional village cluster protection mode. From a research theory perspective, this study built a theoretical system of traditional centralized village protection planning based on the quantitative extraction of the SES spatial model. This study considered the highly clustered Jinjiang Basin as an example to address important challenges, such as how to realize the accurate classification of traditional village resources and the centralized and continuous protection of these villages. At the watershed level, complex and correlated research was conducted on traditional villages’ sustainability, protection, and development to explore a quantitative extraction path for their SES spatial patterns as well as a multilevel nested analysis.

This study proposed classified protection measures for traditional villages in the Jinjiang River Basin and accurate spatial policy suggestions for traditional village groups. It provides theoretical support for solving various issues, such as the obstruction of the social and cultural inheritance of traditional villages, the coordinated development of the ecological environment, and the lack of an accurate, effective measurement system for SES spatial carriers. Simultaneously, it also provides theoretical support for national plans to protect centralized and continuous areas, including traditional villages.

While this study systematically analyzed the sustainable development of traditional villages in the Jinjiang River Basin, the topic still requires further improvement and detailed research in many aspects. Future studies could be conducted to integrate heritage values of traditional villages with regional characteristic industries for development and inheritance and establish a value system systematically associated with modern values.