A New Approach to Rural Classification Based on the Filter-Method System: An Empirical Study in Nanning, South China

Abstract

Rural revitalization is a strategic plan to address sustainable rural development in China and is an important revitalization task for Chinese villages. Rural classification is a key strategy for clarifying the direction and positioning of rural development and providing scientific policy decision-making Based on the findings of previous research on rural classification, we propose a new method for rural classification—the filter-method classification system. The operational steps of the classification are as follows: determining the type of villages, implementing the qualitative filter-method, implementing the quantitative filter-method, testing and feedback, and formulating the development guidelines. A total of 1425 villages in Nanning, the capital city of Guangxi, were classified. The classification results show that villages in Nanning city can be divided into four primary categories and eight secondary categories. The accuracy of the primary categories in the classification results was tested to verify the scientific objectivity and applicability of the classification idea and mode. Finally, development suggestions are presented based on the results of the classification of villages. The study results provide a reference for further rural classification work to help rural revitalization and improve the rural classification methodology and the scientific objectivity of classification. It also provides the basis for sustainable monitoring of rural development.

1. Introduction

Rural classification is important for understanding the characteristics of rural development and formulating rural development policies [1,2], and has received widespread attention [3,4,5,6,7]. In developing countries, the countryside is rapidly urbanizing, changing, and diversifying [8,9,10,11], a fact that calls for scientific management of rural change. The important task is to form a set of criteria to classify the countryside in an integrated and comprehensive way, so that as many elements of the rural environment as possible can be analyzed as a territorial, social, and economic organism. This typology has gained the attention of scholars in the developed world. Developing countries, (e.g., Serbia) are also exploring their classification methods for villages through systematic reference to the Western European experience while following the needs of their society and its potential [12].

China, the world’s largest developing country, is rapidly urbanizing, resulting in a decline in the countryside. China’s central government promulgated the “Strategic Plan for Rural Revitalization” (2018–2022), hereinafter referred to as the Plan, in May 2018 to solve the problem of rural development. The Plan proposes that the management of the countryside should be strict and refined and calls for compliance with the laws of village development and evolution. The classification of villages includes four categories, as follows:

• Agglomeration promotion class;
• Suburban integration class;
• Characteristic protection class;
• Relocation and merger class.

The Plan suggests that revitalization and development be carried out with appropriate strategies. However, there is a lack of clear criteria for discernment or classification instructions in the Plan. Specifically, the government has not uniformly categorized villages across the country. Because of the great regional differences, localities have had to consider the practical needs of their work to implement the rural revitalization strategy. Therefore, these localities have proposed criteria for classifying different types of villages that reflect the development trend of the countryside but still adhere to the four main categories of villages stipulated by the State. The purpose of the classification is to help the management department manage and make decisions and effectively guide the countryside toward rejuvenation. The classification can clarify the direction of development of the countryside and its functional positioning, affect the positioning of rural development and the construction of the countryside, and guide the reasonable allocation of public resources in the countryside and preparation of the village plan. Thus, the classification of the countryside is an urgent task for the revitalization of the countryside in China.

Current research on rural classification suffers from a lack of flexibility and generalizability of the classification system because the meaning of rural varies according to the context in which it is observed. The creation of a set of classification types implies that the researcher needs to have a comprehensive understanding of the rural dimension and to find relatively homogeneous units created for specific research objectives and development policies [13,14,15,16].

This paper explores a technical approach to rural classification suitable for China, introduces the Village Classification Model (VCM) screening process [17], reconstructs a set of technical modeling methods, such as the Filter-Method System, and conducts a classification empirical study based on more than 1400 villages in Nanning city, which reveals the feasibility and universality of this new classification method through testing and feedback. Not only can it provide technical methods and guidelines for rural revitalization in China, but also can it be extended to other regions. Connecting the rural classification with the work of government management, we have deeply explored the inherent mechanism and logic, and complemented the blank of the rural classification theory system. To address the above efforts, the following three questions were asked:

• How can qualitative classification be quantitatively identified?
• How do quantitative studies highlight the various types of village differences?
• Can the classification model be quickly adapted to accommodate differences in different areas?

The rest of the paper is as follows: Section 2 provides an overview of domestic and international rural classification methods and development trends; Section 3 presents a critique of the problems of the current rural classification methods and presents two hypotheses. Also included in this section is a description of the construction of the theoretical framework and technical modeling method and a clarification of the data sources. In Section 4, the results of rural classification, based on the filter-method are presented, including additional tests and feedback. Finally, in Section 5, our findings are summarized and discussed, and policy recommendations are made concerning the classification results.

2. Literature Review

At present, the classification of the countryside is conducted using a combination of qualitative and quantitative research methods. Qualitative research in rural classification is generally based on a typology, whose classification criteria are determined by the researcher’s academic point of view and subjective perspective. Quantitative research is generally based on a collection of quantifiable data and statistical data analysis. Rural development is evaluated by constructing and using a system of key indicators to ensure the classification results are as objective as possible.

2.1. Qualitative Research

Traditionally, the main method of classifying village types has been based on empirical data (i.e., observational, primary data) and qualitative analyses [18,19]. Early European rural typologies were generally one-dimensional and could not adequately define the diversity of the areas observed. The identification of a typology of rural areas and the assessment of various attributes describing rural diversity is a complex issue that requires a multidimensional approach. Inspired by the so-called “post-rural approach”, current rural studies focus on the diversity and variability of rural areas, their dynamic components, and transformations [6,20,21,22]. In the UK, since the 1970s, academics and government departments have proposed a variety of methods of rural classification. In the UK, qualitative classification is usually characterized by the researchers’ academic and social perspectives and the substantive differences in rural spaces from several dimensions [20,23,24,25], rather than on a set of universal classification criteria. Some scholars have argued that this typological approach has certain limitations, such as too many elements to analyze and the difficulty of developing criteria [13].

Along with urbanization in developing countries, the countryside is also in a state of dynamic development. Thus, more attention to rural issues and sophisticated management is required, including research on rural classification projects such as the study by Li [26]. Research on qualitative classification of villages includes direct classification from a single perspective [27,28], comprehensive classification of a variety of factors [29], and other approaches to qualitative classification, based on the classification process and logic. Classification methods include constructing classification frameworks or models [17,30], partitioning, and step-by-step classification methods.

Classifications have been based on the geographical environment of the countryside and the relationship between the countryside and towns [31], as well as on the theory of the urban–rural dichotomous structure. Researchers have also directly classified the countryside based on the detailed classification of the countryside categories determined at the national level [32]. In Serbia, research on rural settlements classified the countryside, typologically, into five categories: demographic typology, urban form typology, functional typology, socio-economic typology, and complex typology [12]. The purpose of the typological classification is to coordinate and plan the development of rural areas per the social needs and future potential.

The studies of population typology and urban morphology typology are qualitative classifications. The demographic typology is based on the population size of the settlement [33], but scholars have argued that more interrelated characteristics should be added. For example, the classification of urban and rural settlements per the demographic changes due to a variety of daily factors [34], and classification per the ages of the population [35] are classifications that reflect demographic trends in rural settlements.

2.2. Quantitative Research

Quantitative classification is generally based on statistics. One or more key indicators released by the government or authoritative organizations are selected to quantitatively describe the development status of villages and urban–rural relations. Intuitive data can explain abstract rural areas more graphically. For example, British scholar Cloke used principal component analysis combined with census data analysis to identify key rural indicators. The 2011 version of the British Rural-Urban Classification System [36] is the most widely used in the British public sector and government documents. The new classification adopts a combination of spatial grid divisions, census data, and postcode data as the core parameter indicators to (a) analyze the size of settlements and “sparsity” of settlements and (b) divide rural and urban areas into four urban types and six rural types. In the current mainstream quantitative evaluation, a single or multifactor indicator evaluation system is used, with methods such as principal component analysis or PCA [13,37], cluster analysis (CA) [38], multivariate analysis methods, or a combination of PCA, FA, and CA applications [39]. Current scholars believe that single-factor analyses cannot accurately identify rural characteristics [40], and that rural areas have multidimensionality [41].

In recent years, scholars in developing countries have used the quantitative analysis of data in rural classification. They have adopted the multifactor comprehensive evaluation method [42,43,44,45], the principal component analysis method, and the hierarchical analysis method; constructed a system for evaluating the development potential of villages [46,47]; built a classification model for screening villages; and adopted other innovative classification ideas and methods for quantitatively evaluating and classifying villages. Most scholars use Arcgis 10.2 software to assist spatial analyses in the quantitative approach to rural classification. Some scholars have also used multiple methods in a step-by-step study to identify rural types [48,49]. Other scholars have attempted to innovate quantitative categorization methods. They argue that the a priori urban-rural continuum model should be abandoned in favor of a more open-ended approach to categorization through CA methods. This approach would avoid the errors associated with relying on the rurality presupposition in defining rural types and improve the broader understanding of rural heterogeneity [38]. They also support the typological “concrete-abstract-concrete” method, which establishes the degree of location, value of resources, and economic volume as the criteria for rural classification. This method supports the natural settlement as the classification scale unit and adopts the superposition of the protection and development categories to carry out the classification [50].

Although there are differences in the models and methods used in quantitative rural classification research, they are all used to select evaluation indicators of rural development for comprehensive analysis. The selected indicators tend to be comprehensive and complex. However, there have been few theoretical and practical discussions on how to use indicator data to reasonably reflect the need for rural classification.

2.3. Research Trends

The current trend in international research is a gradual shift toward the use of an integrated typology to classify villages. This trend moves away from one-sided and simple classifications to more complex, systematic, and applied classifications and the use of a multifaceted classification methodology to classify villages. A considerable number of scholars in European countries are also currently working on a typology of the countryside [3,4,5,6,7], using a systematic and interdisciplinary approach and a complex methodology. The trend toward the establishment of such typologies is justified by the fact that the results of the research provide an integrated picture of the actual situation in the countryside.

Scholars consider the selection of indicators to be of primary importance. Functional typology is widely used to distinguish between rural and urban areas. Socio-economic typology is in line with the current research trends. The current rural typology classification criteria in European countries are generated using a systematic and interdisciplinary approach, so are limited in their use in countries where the data indicator base is not well developed.

Data analysis methods differ based on the type of data. Some kinds of data are difficult to analyze quantitatively and require multidisciplinary cross-study. Thus, scholars have attempted to combine qualitative and quantitative research [51,52]. Others have constructed a framework for rural appraisal and then analyzed the data qualitatively [2,53].

2.4. Critique of the Problem

Studies on rural classification methods use qualitative or quantitative methods or a combination of the two. However, the classification results of studies using qualitative and quantitative methods, separately or in combination, have limitations, as follows:

• Are not sufficiently objective.
• Are not derived from a large number of samples.
• Do not identify core differences among villages.
• Are not universally applicable to all regions of China.
• Are not tested using technically appropriate testing tools.

A description of the limitations of classification results is presented in the following paragraphs.

Are not sufficiently objective or derived from a large number of samples. Qualitative research is based on typological research, with inductive analysis and type comparison as the main analysis methods. Current qualitative research on rural classification focuses more on exploring the connotation of rural differences and predicting the direction of rural diversification. In addition, qualitative research based on staff field surveys can be subjective and can lead to overly one-sided and subjective classification results. The classification of rural types through a single element lacks adequate data analysis and is unable to address a large number of rural samples.

Do not identify core differences among villages. Most quantitative studies on rural classification are based on statistics. These studies used constructed evaluation systems and weighting indicators that are practical at the macro and regional policymaking levels. Current studies using quantitative research methods for rural classification describe the static regional situation and explain the process of change. However, they place too much emphasis on the data. Specifically, the classification results, weighted by the use of indicators, only reflect the differences in the overall potential of villages or the development level of a single dimension. The results do not reflect the specific characteristics of villages and the pros and cons of their development. Finally, the results are not significant enough to guide plans for villages with different characteristics.

Are not universally applicable to all regions of China. Rural classification techniques have been developing over the years in China. However, China is a vast country with huge differences in geography, climate, economy, and people, and different demands for rural development. At present, typology-based qualitative analysis and quantitative, statistics-based evaluation tend to formulate the index system for specific research areas only. Most of the classification models are not universally applicable and are not flexible enough to be adapted to the needs of rural classification in different regions.

Are not tested using technically appropriate testing tools. Research on rural classification has mainly focused on the construction of technical ideas, determination of technical methods, classification of rural types, and analysis of actual cases, rather than on testing and feedback of classification results. The results of rural classification are closely related to the technical ideas and methods adopted by researchers. Results obtained by different technical ideas and methods for the classification of the same region will differ. Therefore, technical ideas and methods used to obtain classification results need to be tested for validity and reliability.

The core reason for these limitations is that the theoretical understanding is insufficient, the purpose of rural classification is not clear, and the focus of attention is not clear, which in turn leads to the inconsistency of the classification methods used in many studies. Therefore, we need to discuss the theory of rural classification and set clear theoretical assumptions.

2.5. The Aim of the Present Study

The research objectives of this paper are as follows: (1) propose research hypotheses based on the constructive modeling approach and to enrich the theoretical foundation; (2) combine typology and statistics to effectively synthesize the advantages of quantitative and qualitative rural classifications; and (3) optimize and improve the VCM screening classification method, and establish the filter-method classification system, which can quickly adjusting the model and is more generalizable.

3. Materials and Methods

3.1. Research Hypotheses

Different technical approaches—systemic in quantitative research and typological in qualitative research—to rural categorization reflect different ways of thinking about research. Given the knowledge and understanding of village systems, this study explores a theoretical elaboration of the rural classification framework, based on the following assumptions and related research hypotheses.

Assumption 1: 

Quantitative rural classification can be disaggregated into multi-directional factor evaluations.

The countryside is often regarded as a complex system that is characterized by “elements” forming a “system whole”. This has led to the mainstream of current classification methods treating the countryside as a whole and adopting a “systematic” approach to classification techniques [54,55]. However, it is premature to define the current status of the countryside or to treat it as a whole, systemic entity, while ignoring the analysis of its internal components. Rural villages are smaller and inhabited by more independent individuals than the more complex systems of cities. In presupposing ontological reductionism (i.e., a belief that the whole of reality consists of a minimal number of parts), villages can be broken down into smaller parts, and their characteristics can be simplified and abstracted more easily. Reductionism can be used to dismantle and study the elements affecting all aspects of rural development [56], and to divide these elements into different factors to comprehensively evaluate the countryside. The sum of the parts can be deduced and explained as the nature of the whole, which approximates the overall characteristics of the rural system.

Assumption 2: 

The core key point of qualitative rural classification screening is the variability of villages.

In the process of development, villages are characterized by small scale, high spatial dispersion, and slow development. Therefore, the impact of individual rural elites or sudden policy variables (e.g., road construction, poverty alleviation policies) has a huge impact on rural development decisions that can produce directional changes in rural development [57]. This phenomenon of discontinuous and sudden changes in socio-economic activities from the outside is difficult to describe in longitudinal studies. Therefore, this study introduces the research method of mutation theory to investigate the possibility of finding small differences in the villages amid similarities based on the stability of the village structure under strictly controlled conditions. The differences point to the loss of the stable structure and the formation of the heterogeneity of the villages. Therefore, using “difference” as the screening key, villages that can mutate can be screened out based on their distinctive differences.

3.2. Methods

Based on an understanding of the rural classification problem and guidance provided by the theoretical method, the qualitative VCM proposed by Li [17] was improved and enhanced. A filter-method rural classification model was constructed. It consists of a set of rural classification models that qualitatively identify core differences, quantitatively evaluate multiple dimensions, flexibly adjust the filter tests and provide feedback to the classification results, and guide the practical application of the model. The model designs the distinctive features of the countryside and different dimensions of the evaluation indicators into several sets of filters, sets the order and thresholds of each set of filters, and uses a three-step process. These steps are described in the following paragraphs (Figure 1).

The first is the qualitative filter-method. Villages are put into the filter-method model one by one. Villages with obvious characteristics—villages with special characteristics in border areas, villages in special protection categories on various lists, and villages affected by ecological environments, geological hazards, and mining zones that need to be relocated and merged—are first identified and classified through qualitative judgments.

The second is the quantitative filter-method. Based on rural resource endowment, construction status, location and traffic, industry and economy, the degree of infrastructure support, and other factors affecting rural development, the following tasks were completed: Construction of a system of indicators for evaluating the potential of villages in various dimensions, grading of the results of the dimensions evaluation, and screening of the remaining villages. These tasks were conducted to classify villages in the suburban integration class, agglomeration promotion class, and industrial development class.

Third, technical inspection and feedback. The results of the classification of the filter-method will be tested in the field, sampled, and analyzed. The similarities and differences between our categorization results and grassroots feedback will be compared; the reasons for the differences will be fed back into the filter-method model system, which can dynamically adjust the hourglass level and order and optimize the working mechanism.

3.3. Study Area

Nanning is the capital city of Guangxi province in China (Figure 2), with seven districts, four counties, and one city under its jurisdiction. In 2022, the household population was 8,100,800, of which 4,303,500 were in urban areas; the city’s resident population was 8,891,700, of which 6,256,200 were in towns and cities. The urbanization rate of the resident population was 70.36%. Nanning City was selected as the study area based on the following considerations. (a) Nanning City is dominated by the Zhuang people and inhabited by many other ethnic groups. With its historical heritage of ethnic culture, the countryside has precipitated many tourism landscape resources. (b) The topography of Nanning city is 62.18% hilly with a fragile ecological environment composed of karst landforms. The well-developed river systems and monsoon climate make for a complex and contradictory relationship between the Nanning City area’s agricultural environment, arable land, residential areas, and population. (c) The urbanization rate of the resident population in Nanning city is over 70%. Thus, the development and transformation of the countryside, integration and development of urban-rural relations, and revitalization of the countryside makes for a special situation.

3.4. Explanation of Village Types in Nanning City

Currently, the types of villages in Nanning City include four categories: characteristic protection class, suburban integration class, agglomeration promotion class, and relocation and merger class. The secondary classifications are agglomeration development type villages, sustenance and enhancement type villages, industry development type villages, governance improvement type villages, suburb type villages, function undertaking type villages, natural ecological landscape type villages, and historical and cultural protection type villages (

Table 1. Countryside types and characterization in Nanning city.

Category I	Type Description	Category II	Type Description
Relocation and merger class	Refers to villages that have been identified in the relevant plans as needing to be relocated for reasons such as ecological protection, geological hazards, mining, and construction of major projects.	Relocation and merger type villages B1	Villages with a poor living environment and a serious lack of resources needed for survival, necessitate relocation. Villages with extremely fragile ecological environments that cannot be effectively improved through ecological engineering measures. Villages located in the core and buffer zones of various types of national protected areas that need to be forcibly relocated according to relevant requirements. Villages where the frequent occurrence of various natural disasters strongly affects the life and property of villagers. Villages that need to be relocated due to the construction of major projects and national defense projects. Villages that are close to large sewage treatment plants, landfills, and other places that are not conducive to survival.
Characteristic protection class	Refers to villages that have been listed for protection or are rich in natural ecological landscapes and historical and cultural characteristics.	Natural ecological landscape type villages T1	Famous villages with characteristic landscape tourism. Villages in the list of “Famous Towns and Villages with Characteristic Landscape Tourism” issued by governments at all levels. Rural villages with good natural landscape resources and a foundation for the development of tourism resources or local consensus that can be included in the category of natural landscape tourism.
		Historical and cultural protection type villages T2	Famous historical and cultural villages. Villages in the list of “Famous Historical and Cultural Towns and Villages” issued by all levels of government. Traditional villages. Villages in the list of “Traditional Villages” issued by governments at all levels. Minority Characteristic Villages. Minority villages in the list of “Chinese Minority Characteristic Villages”. Villages with historical and cultural heritage, including minority characteristics, which the local community agrees can be included in the characteristics protection category.
Suburban integration class	Primarily, this refers to the countryside immediately adjacent to the town’s development boundary and heavily influenced by the town’s development.	Suburb type villages C1	Villages within city clusters, city circles, and non-urban construction land within cities that are subject to planning control due to urban development. Villages within proximity to county towns and townships, closely related to township development, and greatly affected by township development (the situation of being cut off by township development boundaries needs to be considered). Villages within the direction of town expansion and its influence.
		Function undertaking type villages C2	Rural villages that are close to towns and are greatly affected by the development of towns and take over the transfer of industries and functions from the towns
Agglomeration promotion class	General villages other than those in the relocation and merger class, characteristic protection class, and suburban integration class are categorized as villages in the agglomeration promotion class, which includes villages with relatively high development potential and villages with average development potential.	Agglomeration development type villages J1	Existing central villages and key villages of larger scale and better development conditions, as well as villages established as central villages in the relevant plans. Villages with relatively good location conditions, relatively concentrated population, and relatively complete public services and infrastructure support. Newly built communities or villages after relocation and annexation and newly built rural communities outside the planned construction sites of towns. Villages that need to be partially relocated due to the protection of ecology, construction of major projects, expansion of towns and cities, threats of geological disasters, restricted conditions for survival and development, and comprehensive improvement of relocated villages and points. Other villages whose forms and organizations are relatively stable and can be used as a cluster development type. Villages under the jurisdiction of state-owned farms and state-owned forests.
		Sustenance and enhancement type villages J2	Villages that have a certain foundation for socio-economic development, with little change in the size of the population and little need for growth in the size of village construction, and that will continue to exist for a long time. Villages where most of the village area is located within the ecological protection zone and its area of influence. Villages with population loss and village decline, but with no temporary change in the short term and needing to retain the status quo.
		Industry development type villages J3	Rural villages where agriculture, industry, or services are prominent, where resource conditions are relatively favorable, and where there is a certain foundation for development. Villages with a good basis for the development of agriculture, industry, or services, which provide material production or various services for the development of towns and industries. Rural villages with rich tourism resources and a tourism industry that supports development.
		Governance improvement type villages J4	Villages with a relatively poor living environment or a fragile ecological environment, which can be effectively managed through certain engineering measures without being relocated and annexed.

).

3.5. Data Collection

3.5.1. Setting and Selection of Indicators

Whether a qualitative, quantitative, or mixed-methods rural research study, an indicator evaluation system is usually established [58] to judge the development potential of the countryside and its various functions. This indicator evaluation system is a combination of multidimensional factors [59]. In this study, the process of establishing a multidimensional rural potential evaluation index system involved the selection of key indicators. The selection of indicators is determined by consulting relevant experts and scholars and referring to existing research results. They are also based on the development needs of rural revitalization, following the principles of comprehensiveness, practicability, and operability. The selected indicators reflect the current state of rural development and also consider the development trend of the countryside in the future [60].

Based on the urban-rural relationship and village characteristics of Nanning City, this study evaluated the development potential of villages in Nanning City from five dimensions: ecological environment, location conditions, population vitality, village construction, and industrial economy. A total of 20 evaluation indexes were selected to construct the evaluation index system of village development potential (

Table 2. Multidimensional Rural Potential Evaluation Index system.

Dimensions	Evaluation Indicators	Indicator Weight	Data Processing	Indicator Attributes
Location conditions A1	Distance to city center D1	0.20	GIS computation	Negative
	Distance to district center D2	0.44	GIS computation	Negative
	Distance to highways D3	0.08	GIS computation	Negative
	Distance to provincial highways and above D4	0.28	GIS computation	Negative
Ecological environment A2	Number of disaster sites D5	0.16	GIS computation	Negative
	Distance from nature reserves D6	0.09	GIS computation	Positive
	Percentage of ecological land area D7	0.39	(Woodland area + grassland area)/Total village area	Positive
	Area of open water D8	0.36	Open water area	Positive
Population vitality A3	Village population D9	0.41	Data from the Seventh National Population Census	Positive
	Percentage of resident population D10	0.11	Resident Population/household population	Positive
	Population change rate D11	0.19	Five-year population Increase/decrease in current resident population	Positive
	Aging rate D12	0.29	Population over 60 years of age/household population	Negative
Village construction A4	Public Service Facilities Construction D13	0.09	Expert Scoring	Positive
	Residential Infrastructure Construction D14	0.46	Expert Scoring	Positive
	Village group infrastructure D15	0.18	Expert Scoring	Positive
	Per capita construction land area D16	0.27	Expert Scoring	Negative
Industrial economy A5	Disposable income per capita D17	0.52	Gross output value/resident population	Positive
	Per capita agricultural land area D18	0.22	Land area (garden land + arable land)/resident population	Positive
	Per capita industrial and mining land area D19	0.10	Industrial and mining land area/resident population	Positive
	Number of tertiary industries D20	0.16	Number of points of interest related to the tertiary industry	Positive

). The judgment in the selection of key indicators is consistent with previous research [61,62].

When selecting evaluation dimensions and related indicators, care should be taken to judge whether they reflect the core differences of the villages. The five dimensions and key indicators selected for this study are based on the fact that natural environmental conditions and the level of regional socio-economic development are the main factors affecting rural development [63]. The ecological dimension is crucial to Nanning, the “Green City”, as the basis for sustainable development. The location dimension reflects not only the favorable geographical location of villages but also the convenience of villages and towns. Accessibility is, to a certain extent, also related to development [64]. One of the key indicators is the distance to the city center. The closer the countryside is to the city center, the stronger the town’s economic and industrial development drives. Accessibility is conducive to the interconnection of facilities between urban and rural areas and the promotion of integrated urban and rural development. It also has a unique development advantage in terms of population movement, commodity trading, and consumer services.

In some studies of developing countries, population size and density and occupational patterns are the main indicators for classifying cities and villages [10]. This study argues that the population vitality dimension reflects the coordinated relationship between the rural population and various types of land use and settlements. When the indicator of the total population of villages shows positive growth, the population density is high, and the age structure of the population is predominantly young and middle-aged. In such villages, the overall development potential of the village will be higher than in a decline-type village. The indicator of the aging rate is an important indicator for measuring the future development of the countryside. When the population shows negative growth, the population conservation rate is low, the age structure of the population is dominated by the elderly, the local economy develops slowly, and the local pension financial pressure is high. In such villages, the overall development potential of the countryside will be small [65]. The village construction dimension reflects the villagers’ housing conditions and living environment. The better the villagers’ housing conditions and living environment, the greater the livability of the village and its population agglomeration capacity and development potential. Housing conditions include the construction of public service facilities, residential infrastructure, villagers’ group infrastructure, and per capita construction land area. The industrial economy dimension refers to the economic and social development of villages, the status quo of industrial development, the level of industrial output, the affluence of villagers, and their sources of income. The economic development of villages is one of the key issues of rural revitalization. A guarantee of the quantity of arable land resources ensures the security of China’s food supply [66]. Intensive and efficient land utilization is crucial for villages with scarce land resources and an outflow of laborers. Thus, indicators such as the area of agricultural land per capita were selected as they reflect the abundance of agricultural resources and the potential for sustainable development in the countryside.

3.5.2. Sources of Qualitative Data

The qualitative data for this study come from the following sources/lists:

• “Traditional Villages” and “Towns and Villages with Characteristic Landscapes for Tourism”, issued by the Ministry of Housing and Urban-Rural Development and other departments (https://www.mohurd.gov.cn/) [67].
• “Historical and Cultural Towns and Villages”, and the list of “Characteristic Villages of Ethnic Minorities” issued by the State Ethnic Affairs Commission (https://www.neac.gov.cn/seac/xxgk/201703/1079595.shtml) [68].

3.5.3. Qualitative Data Processing

Villages in Nanning City that are on the “Famous Historical and Cultural Towns and Villages” and “Villages with Minority Characteristics” lists were screened and included in the study. Also screened and included are villages that have been established as central villages in the previous Plan. Vector data, such as the “three zones and three lines” and the third land survey issued by the Guangxi Department of Natural Resources, were used to identify villages in “scenic areas”, villages prone to geological disasters, and villages in the core areas of protected areas at all levels. This step is completed by using the Arcgis10.2 software.

3.5.4. Sources of Quantitative Data

Statistical type data came from the Guangxi Zhuang Autonomous Region Statistical Yearbook (2022), the China Statistical Yearbook (2022), and statistical yearbooks of cities and counties in the Guangxi region. Population data and industry data, among others, came from various types of census data published by the National Bureau of Statistics (https://www.stats.gov.cn/). Road data and information on nature reserve boundaries and administrative village boundaries, among others, were provided by the Natural Resources Survey and Monitoring Institute of the Guangxi Zhuang Autonomous Region.

3.5.5. Quantitative Data Processing

The researchers calculated and normalized the data in categories A1/A2/A3/A5 using GIS neighborhood tools, raster calculation tools, analysis tools, and Excel calculations, among others. The data in category A4 is difficult to quantify. Therefore, expert scoring was used to analyze the data. Under each dimension, the importance of each evaluation index was compared, and a judgment matrix was constructed with the formula, as follows:

$$a_{ij}={\displaystyle \frac{1}{a_{ji}}}$$

In the formula: $a_{ij}$ is the result of the comparison of the importance of factor $i$ and facto $j$; next, through hierarchical ordering and testing consistency, the weight of each evaluation index was obtained. The formula is as follows:

Normalize each column of the judgment matrix, where

$$\overline{W_{ij}}={\displaystyle \frac{a_{ij}}{{\displaystyle {\sum }_{k=1}^n{a}_{ij}}}}.$$

Sum up normalized judgment matrices by rows, where

$$\overline{W_i}={\displaystyle \sum _{j=1}^n\overline{W_{ij}}}.$$

Normalize processing vectors, where $\overline{W}={\left[\overline{W_1},\overline{W_2},\overline{W_3}\cdots \overline{W_n}\right]}^T$.

$$W_i=\frac{\overline{W_i}}{{\displaystyle {\sum }_{j=1}^n\overline{W_j}}}.$$

Calculate the maximum eigenvalue, where

$${\lambda }_{\max }={\displaystyle \sum _{i=1}^n\frac{{(AW)}_i}{n{W}_i}}.$$

This is the consistency (CI) test formula for judgment matrices. The larger the CI value, the weaker the consistency of the judgment matrix, as follows:

$$CI={\displaystyle \frac{{\lambda }_{\max }-n}{n-1}}.$$

Based on the results of the above calculation, a multidimensional village potential evaluation index system was established, and is shown in Table 2.

The research team processed the evaluation index data for 1425 villages in Nanning City using the existing data. The natural breakpoints using GIS were divided into five categories, including lowest, low, medium, high, highest, and assigned a score value of 1–5 points, respectively. Combined with the evaluation model weight measurement results and the weighted summary of each dimension score value, the formula is as follows:

$$Z={\displaystyle \sum }_{i=1}^n{P}_i{Q}_i\left(i=1,2,3\dots \right)$$

where Z is the score of each dimension of the village; P_i is the score of evaluation indicators; Q_i is the weight of evaluation indicators; n is the number of evaluation indicators of each dimension. The dimension scores were divided into five levels: lowest, low, medium, high, highest.

3.5.6. Test and Feedback Data Collection

In previous studies, the results of the rural classification were not tested for scientific objectivity. Therefore, the research team in this study developed a set of test criteria by selecting three township government staff in each township totaling 267 people to score and evaluate the seven dimensions of villages. If the scoring results are consistent, the results will be used as feedback for the test; if there is a big difference between the scores, the final results will be determined after an arbitration discussion (see Supplementary Materials for scoring questionnaire).

3.6. Description of the Screening Sequence

3.6.1. Qualitative Screening Sequence

In determining the qualitative hourglass screening order of Nanning City, this study proposes the following screening order according to the regional characteristics and development needs of Garden City Nanning City as follows: ecological landscape → protection of regional cultural characteristics → ecological safety bottom line → project impact. The screening rationale per each of the regional characteristics is as follows (Figure 3):

• Ecological landscapes were selected for special protection because the Nanning Municipal Government attaches the highest importance to ecological landscapes. Villages in Nanning City that are located in scenic areas and those that are included in the list of “Famous Towns and Villages with Special Landscapes for Tourism” at all levels are classified as natural ecological landscape type villages (T1).
• Regional cultural characteristics. Nanning City is a place with ethnic minority residents and therefore has a special ethnic regional culture that needs to be protected. Villages listed in “Famous Historical and Cultural Towns and Villages” and “Villages with Ethnic Minority Characteristics” pre-2023 will be classified as historical and cultural protection type villages (T2).
• Screening of villages within ecological zones where ecological security is the foundation of sustainable regional development requires the evacuation and continued subsidization of villages involved in the ecological red line. The villages located in the core area of the nature reserve will be classified as relocation and merger type villages (B1).
• Screening villages involved in the impact of government projects and organizing villages for relocation. Villages that need to be relocated within the scope of construction of major projects adopted by governments at all levels are also classified as relocation and merger type villages (B1).

Figure 3. Nanning qualitative filter-method technical route.

Figure 3. Nanning qualitative filter-method technical route.

3.6.2. Quantitative Screening Sequence

To determine the order of quantitative hourglass screening in Nanning City, this study refers to previous rural research studies [69,70] and the reality of Nanning City and proposes the following order of screening: location evaluation→ ecological evaluation → population evaluation → construction evaluation → industrial evaluation. The rationale for the screening ordering is as follows (Figure 4):

• Screening villages with good location. Location factors determine the degree of connection between villages and the external environment, the accessibility of resources, and market potential. Location can also influence the policy and financial support provided by the government. Location and transport have a far-reaching impact on economic development, social progress, and ecological and environmental protection of villages. According to the A1 rating score for location conditions, rank 5 outputs are suburb type villages (C1) and rank 4 outputs are function undertaking type villages (C2).
• Screening villages with poor ecological conditions. Ecological factors such as the ecological environmental dimension affect the sustainable development of villages. Rural ecosystems are the foundation of rural socio-economic development, and their stability and sustainability are directly related to agricultural production, biodiversity, natural disasters, and rural habitat. Ecological factors form the basis for the long-term stable development of the countryside. Ecologically poor villages should be gradually declining under the guidance of government policy. According to the ecological conditions A2 scoring level, level 1 outputs are relocation and merger type villages (B1), and level 2 outputs are sustenance and enhancement type villages (J2).
• Screening villages with a low demographic dividend. To develop the countryside, the labor force is an important influencing factor. The population size, mobility, and age composition are directly related to the construction of the countryside and the development of industries. In recent years, the population size of the countryside has decreased significantly, the young labor force has migrated to the city, farmers are aging, and portions of arable land are deserted and uncultivated. These factors affect the development of countryside industries and also threaten food security. According to the population vitality A3 scoring level, level 1 outputs are sustenance and enhancement type villages (J2).
• Screening of villages with significantly better/worse construction conditions. The evaluation of the construction conditions in villages can reflect the current construction conditions in villages. Specifically, the construction of rural infrastructure and public service facilities provide a material basis for industrial development. The evaluation of the construction conditions in villages also reflects the villagers‘ living environment conditions. The better the villagers’ housing conditions and living environment, the more livable the countryside, and the greater the rural population agglomeration capacity and development potential. Additionally, the evaluation of the construction conditions in villages can also reflect shortcomings in rural construction. According to the rating scale, rank 4/5 outputs are agglomeration development type villages (J1), and rank 1 outputs are governance improvement type villages (J4).
• Screening villages with good industries. Industrial revitalization plays an important role in rural revitalization and is the foundation and key to rural revitalization. Rural revitalization is a comprehensive revitalization process, including industrial revitalization, talent revitalization, cultural revitalization, ecological revitalization, and organizational revitalization, of which industrial revitalization is considered to be the most fundamental. Rural revitalization helps to promote the sustained development of the rural economy and improve the living standards of farmers. It also injects sustainable momentum into the comprehensive revitalization of the countryside and promotes the coordinated development of urban and rural areas. According to the scoring levels, level 1 outputs are sustenance and enhancement type villages (J2), and level 2/3/4/5 outputs are industry development type villages (J3).

Figure 4. Quantitative filter-method technical route in Nanning city.

Figure 4. Quantitative filter-method technical route in Nanning city.

4. Empirical Results

4.1. Qualitative Classification Results

It was determined that 53 villages in Nanning City can be included in the characteristic protection class, including 7 natural ecological landscape types and 46 historical and cultural protection types. There are 20 villages in the relocation and merger class (Figure 5).

4.2. Quantitative Classification Results

The final classification of villages in Nanning City is as follows: 286 suburban integration villages (154 function undertaking type villages, 132 suburb type villages) and 1066 agglomeration promotion villages (435 agglomeration development villages, 213 sustenance and enhancement type villages, 354 industry development type villages, and 64 governance improvement type villages) (Figure 6).

4.3. Detection and Feedback

The qualitative and quantitative results were combined and then clustered to obtain the results of the first level of classification (Figure 7).

The research team hired one expert and one government worker each to visit a total of 1367 villages in Nanning. They conducted field surveys on the economy, ecology, population and other aspects, and obtained the types of villages through subjective evaluation. As comparative data, the first-level classification results of filter-method were tested and analyzed. The results showed that there were 18 villages in the first level of characteristic protection class, 90 villages in the first level of suburban integration class, 1235 villages in the first level of agglomeration promotion class, and 24 villages in the first level of relocation and merger class. In this study, 1367 villages out of 1425 villages in the whole area of Nanning City were compared by type, of which the number of villages that matched the locally reported village types was 997, or 72.9 percent.

The filter-method is more accurate in practice. As per Figure 8, the results are inconsistent. Specifically, the number of villages with obvious characteristics, such as characteristic protection, suburban integration, and relocation and merger, is higher than the number of villages reported by localities. This finding indicates that the filter rural classification model is more sensitive to the identification of typical characteristics of villages but less effective in determining the coverage of typical characteristics (administrative villages, natural villages). Therefore, the judgment on the coverage of typical features (administrative villages and natural villages) needs to be improved. The results of the technical test were fed back into the specific workflow of the rural classification model of the filter-method. For the identification of the characteristic protection villages, it was necessary to refer to the relevant documents of the local government for the identification of villages. In field research, it is necessary to focus on the collection of scenic spots, nature reserves, and historical and cultural relics concerning their scale and radial scope. To evaluate rural villages in the suburban integration class, it is necessary to quantitatively evaluate the degree of interconnection between rural villages and the central urban area, industrial parks, population, economy, and transportation. The distance from the central urban area and industrial parks must also be factored into the evaluation. For the classification of villages in the relocation and merger type, the evaluation should be conducted cautiously and comprehensively after collecting information on government departments’ village management plans and relocation and resettlement funding arrangements. In addition, factors such as living conditions, ecological environment, frequency of natural disasters, and impacts of major construction projects should also be considered.

5. Discussion and Conclusions

Based on the implementation of the primary classification of villages and current practical village planning, the researchers of this study completed a comprehensive multidimensional reference index system for rural classification based on the five existing primary classifications of villages in Guangxi. They established the filter-method and further clarified the secondary classification and the principles and methods of classification. The researchers used 1425 administrative villages and their pre-existing data in Nanning City, Guangxi Zhuang Autonomous Region, Nanning as case studies, analyzed the characteristics of the county and the current status of rural development, and innovatively adopted the filter-method rural classification model to classify the villages. This study also analyzed the relationship and feedback between top-down classification management and bottom-up local practice. The rural classification exercise can help policymakers to identify villages with differentiated development potential and adopt differentiated management policies, as discussed in Section 5.2.

The research results confirm the rationality of the two research assumptions. The operation results of the filter-method in Nanning fully prove the advantages of the combination of qualitative and quantitative classification methods. From the experiment, it is found that the parameters of the model can be flexibly adjusted, and the results of the field survey can be quickly fed back and optimized.

5.1. General Discussion

Different rural classification results were obtained based on different classification perspectives and classification methods. In the case of a land-use perspective, scholars generally explore the appropriate transformation mode of rural residential land and use the classification results to guide adjustments to the rural spatial structure [71]. When using the functional perspective of rural areas, the focus is on agricultural and economic development, and the classification results are used to guide planning and zoning [72]. As the functional perspective is usually based on a single perspective, the classification results reflect only a certain perspective on rural issues. When adopting the perspective of spatial optimization, scholars consider the elements of rural revitalization and the elements of social mobility of rural residents and use the classification results to guide the optimization of settlements [73]. The depth of this type of classification usually reaches the first level of major categories. From the perspective of regional development goals and land assessment, scholars will divide rural areas into functional areas to distinguish different development goals, and then guide the classification of rural areas. This type of research needs to obtain more detailed land indicators [74,75].

This study is based on a qualitative identification of core differences and a quantitative multidimensional evaluation method, integrating multiple perspectives to stratify and screen villages. Due to the differences in national conditions and policies, the classification results are partially similar to the results of studies in developed countries and other developing countries [53]. The findings of first-level categories in this study are similar to the findings of studies by Chinese scholars. The findings of second-level categories are a refinement of this study. As the method and basis of rural classification in this paper are different from those of previous studies, the relative number of results in each category varies. The distribution of the number of villages of each type is different from that of previous studies [76]. The results of the classification of the number of results are in the order of agglomeration promotion class > suburban integration class > characteristic protection class > relocation and merger class. Li’s [76] study found a category of villages that remain ambiguous. The proportion of villages in the relocation and merger class in this study is the smallest, accounting for 1.4% of the total. This result is significantly smaller than the results of previous studies, which identified the type of rural revitalization from the perspective of factor endowment 71.2% [19], and may be attributed to differences in the scope of the study and local policies. The proportion of villages in the agglomeration promotion class is 74.8%, a result close to the 72% in Zhou’s study [19]. This result may be because this study has a clearer basis for the classification of villages in the agglomeration promotion class and carried out the classification as the priority in the quantitative analysis session. This is similar to Zhou’s study [19] on sorting priority, with a smaller number of villages in the characteristic protection class.

Many scholars have attempted to construct classification models in the study of villages [71,77]. The new classification method proposed in this paper, the filter-method, is an adaptive improvement of Li Yurui’s VCM model. The filter-method can solve the limitations of qualitative or quantitative methods in the current classification methods and has strong adaptability. It applies not only to China but also to other regions. Its technical advantages are described below:

• Can objectively reflect the characteristics of villages that cannot be quantified, based on the typology of the qualitative method.
• Can make Yes/No judgments on the screening conditions layer by layer, avoiding the interference of the staff’s subjective will.
• Can distinguish the core differences of villages in different dimensions.
• Can improve the algorithm of weighted calculation of comprehensive potential in quantitative evaluation, distinguish the scores of different dimensions, and reflect the core differences of villages in different directions through multiple high/low screening.
• Has high flexibility and universality. The order and control threshold of each filter can be adjusted to better suit the classification needs of different regions.
• Has enhanced technical testing and feedback of classification results, effective integration of top-down data analysis, and bottom-up field surveys.

5.2. Policy Recommendations

Based on the classification results obtained from the filter-method classification model and the characteristics of different types of villages, village planning and rural development guidelines and governance strategies are proposed in terms of human habitat, infrastructure, public service facilities, industrial development, historical and cultural preservation, and ecological protection. The results of the classification provide an important reference for the government departments, so that the government can make more targeted policies for the villages.

For villages in the characteristic protection class, historical and cultural protection type villages should undertake the following: prepare special plans for history and culture and identify unique regional cultural connotations and local customs through the in-depth excavation of local historical and humanistic resources and characteristic landscape resources; revitalize key cultures, convert historic architectural features and other features directly into industrial capital, and focus on protection with gradual and prudent development. Natural ecological landscape type villages should undertake the following: conduct landscape character assessment to identify charming spaces; fully integrate agricultural and tourism landscape resources; prepare special plans for ecological landscapes; vigorously develop tertiary industries; and carry out characteristic tourism around natural ecological landscapes.

For villages in the suburban integration class, community planning for suburb type villages has been prepared with the aim of improving land-use efficiency, strengthening integrated management of the human environment, and the allocation of public services. These activities have been undertaken to prepare for the transition to urban expansion and avoid disorderly development. Function undertaking type villages need to strengthen their central position in the regional context in their planning and to guide the construction of rural recreational support services, such as rural parks, country parks, regional green belts, and other spaces.

For villages in the agglomeration promotion class, agglomeration development type villages should undertake the following: focus on exploring new rural communities with a synergy of residence and industry; promote population agglomeration and development; tap advantageous industries; and carry out industrial upgrading and transformation in parallel with creating specialized villages. Sustenance and enhancement type villages should be tailored to local conditions and undertake the following: give priority to improving the configuration of basic public service infrastructure; carry out comprehensive improvement of the human environment; promote the development of characteristic and efficient industries; and increase farmers’ incomes. Industry development type villages should link up with neighboring villages to form industrial clusters and continuously optimize the industrial structure. In village planning, the comparative advantages of industries should be analyzed, and guidance should be provided to determine the leading industries. Governance improvement type villages should aim to improve the living environment. In village planning, it is necessary to control the continued expansion of the countryside in construction space. Therefore, planners should strictly control the construction of too large an area of land and too much construction and pay attention to the protection of the ecosystem.

5.3. Implications and Limitations

Rural classification is the prerequisite and foundation of village planning. Scientifically classifying village types and formulating differentiated development policies are the focus of village planning. Based on existing rural classification research, a set of qualitative identifiers of core differences, quantitative multidimensional evaluation, flexible adjustment of the filter feedback of classification results, and guidance for practical application of the filter-method VCM were constructed. The model performed the classification work as per the following operational steps: determining the type of village, implementing the qualitative filter-method, implementing the quantitative filter-method, testing and feedback, and formulating the development guidelines. Nanning City, the capital city of Guangxi, was selected as a case for the empirical study. The results of the case study verify the scientific objectivity and applicability of the classification idea and the classification model.

The fundamental purpose of rural classification is to promote the implementation of the rural revitalization strategy in a differentiated and precise manner. Therefore, rural classification must consider management needs at the administrative level. The results of rural classification determined at the technical level will have to be constantly revised and improved before they can be specifically applied to management.

Although the filter-method rural classification model solves the problem of scientific universality of classification methods, it has two limitations. First, there are difficulties in obtaining data. Vector data, such as the “three zones and three lines” and the third national land survey data available from the Natural Resources Department, are needed to determine village boundaries. Data on the indicators referenced in the development potential evaluation indicator system are needed. They are available from the statistical yearbook but may be incomplete. Second, there is uncertainty in the testing and feedback process. The testing method of this study requires grassroots townships to cooperate with the natural resources sector to report their self-identified village types and then compare them with the classification results of this study. The three difficulties in this process are as follows: most townships self-classify themselves up to the first level of the major categories according to the national classification standard and cannot be refined to the second level to satisfy the test. However, grassroots workers may not be sure of their judgment on classification standards and may be too subjective, which may lead to the test results being inaccurate. Additionally, there are difficulties in collecting and counting the results of their self-classification due to the excessive number of villages. In the future, in-depth research will be carried out in these two areas to promote the continuous updating and improvement of classification techniques and methods.