Traditional Village research based on culture-landscape genes: a Case of Tujia traditional villages in Shizhu, Chongqing, China

ABSTRACT

Global urbanization has led to severe damage and even disappearance of traditional villages in large numbers, significantly impacting the diversity of cultural landscapes. To effectively protect and inherit the cultural landscape of traditional villages, this study proposes the “culture-landscape genes” theory and its double-chain model. Taking the traditional Tujia villages in Shizhu County, Chongqing Municipality, China as an example, we identify, extract, correspond, encode, and comprehensively evaluate their culture-landscape genes. Based on the evaluation and analysis results, corresponding protection and development strategies are formulated. The study indicates that: firstly, the identification, extraction, and correlation of genes directly influence the construction of the evaluation system and the assessment of the protection level. Secondly, the comprehensive evaluation system under the double-chain model is more scientific and reasonable compared to the single-gene model of cultural or landscape genes. The culture-landscape genes theory proposed in this study promotes the development of the gene theory of traditional villages, and its double-chain research model effectively supplements the current methods for the protection and sustainable development of traditional villages, demonstrating a wide range of application value.

KEYWORDS:

• culture-landscape genes
• landscape genes
• double-chain model
• protection
• traditional villages

1. Introduction

1.1. Background

Traditional villages, an integral part of cultural heritage, possess significant cultural, economic, and artistic value (Iwata, Fukamachi, and Morimoto 2011). Nevertheless, due to the influence of global urbanization, populations, industries, and resources continue to accumulate in cities, resulting in a “siphon effect” that depletes rural areas (Antrop 2004a). This has led to the depopulation of rural areas, the disappearance of traditional villages, and a rapid decline in the diversity of cultural landscapes across various countries, particularly in developing nations. Consequently, the sustainable development of the countryside has been severely impeded (Ruda 1998). Concurrently, traditional villages have given rise to numerous homogenized landscape forms (Hill 2003b). Throughout the process of construction and development, there has been considerable destructive development and blind growth, leading to the wasteful use of resources and significantly impacting the sustainability of traditional villages (Antrop 2004b). The rational protection and sustainable development of traditional villages have emerged as a pressing concern, especially for developing countries (Giordano 2020; Zhang, Lijuan, and Renxi 2019).

1.2. Related works

1.2.1. Early research on traditional villages

Traditional villages, garnering scientific interest since the 18th century (Dawkins 2006), have developed a relatively robust theoretical framework by the 20th century. In the 18th century, European and American scholars initiated research on traditional villages primarily from the perspectives of anthropology and geography, exploring multiculturalism worldwide (Liu 2011). Towards the end of the 19th century, Brunhes and others delved into the classification of settlement spaces, which became a crucial aspect of settlement research at that time (Bailuna 1935). In the 20th century, scholars from Germany, France, and the United Kingdom conducted extensive research on the natural environment of settlements (Conzen 1988; Sakamoto and Hiromichi 2004), their morphology and formation mechanisms (Conzen 1988), evolutionary patterns (Deadman, Brown, and Gimblett 1993; Stone 1996), and influencing factors (Hall 1996; Rey and Bachvarov 1998). Nevertheless, early settlement research was greatly influenced by mainstream scientific values, such as empiricism and positivism. Researchers commonly held the belief that the relevant elements of settlements were primarily shaped by the natural environment, a concept referred to as “environmental determinism,” thereby neglecting the status and role of culture in settlements (Cloke 1997; Isabel 2001).

1.2.2. Protection and sustainable development of traditional villages

The protection of traditional villages has emerged as a prominent topic in settlement research, encompassing both physical and digital preservation methods (Kuroda 2019; Sauer 1925). The inception of traditional village protection can be traced back to the conservation and restoration of historical monuments (Chen, Nakama, and Zhang 2017). In the mid-20th century, scholars progressively introduced two theories: wind restoration and anti-restoration (Azman, Asmaa, and Rozali 2014; Sanjay 2007). Building on relevant theories from anthropology and sociology, novel concepts for ecological museums and community development were proposed (Bagbanci 2013; Carrion-Flores and Irwin 2004). The United Nations Educational, Scientific and Cultural Organization (UNESCO) has safeguarded traditional villages by establishing regulations and advocating for the sustainable utilization of these natural and cultural heritage sites (Liu and Bohua 2018; Neumann, Anderson, and Denich 2018). The majority of related research has focused on the micro level, examining specific buildings, but there has been relatively little investigation on the macro level of the entire settlement, resulting in insufficient depth (Marschalek 2008; Taylor 2019). In the contemporary era, the digital preservation and utilization of traditional villages have garnered widespread attention due to the emergence and advancement of technologies such as GIS, BIM, drones, 3D scanning, and virtual reconstruction (Cormier and Elliott 2017). However, there are currently challenges with digital preservation technology, including insufficient overall research, an incomplete technical system, and non-standard operating procedures (Adrian and Clemencia 2011; Juan et al. 2013).

Research on the sustainable development of traditional villages has yielded rich results but still lacks in practical application. Research on the sustainable development of traditional villages covers a wide range of aspects, including the preservation of traditional culture, improvement of the quality of life, ecological sustainability and environmental protection, economic development and community participation (Akkar Ercan 2011; Yung and Chan 2012). These research results have provided useful insights into the conservation and development of traditional villages, and have helped to formulate targeted policies and measures to promote the sustainable development of traditional villages (Auclair and Fairclough 2015). However, research on the sustainable development of traditional villages still suffers from insufficient practice and case studies, as well as insufficiently clear guidance on practical applications (Auclair and Fairclough 2015).

1.2.3. Cultural landscape and settlement genetics theory

At the start of the 20th century, the notion of the cultural landscape was introduced, highlighting the interconnected relationship between culture, landscape, and settlements. In the early 20th century, Sauer introduced the concept of cultural landscape, asserting it to be a core element of regional human geography. He critiqued the previous environmental determinism and accentuated the significance of human culture in shaping cultural landscapes (Sauer 1925). The concept of cultural landscape has exercised a considerable influence on the direction of settlement research.

The concept of cultural genes represents a significant breakthrough in the field of settlement research (Taylor 2009). In the mid-20th century, Alfred L. Kroeber and Clyde Kluckhohn introduced the hypothesis of “cultural genes” (Wilson and Lumsden 1981). In 1976, Richard Dawkins conducted groundbreaking research on cultural genes, suggesting that cultural genes were the fundamental unit of cultural “inheritance” (Griffith 1942). However, the notion of cultural genes tends to focus on ideological levels, such as rules and spirit, without delineating external physical forms, and it does not fully encompass the comprehensive scope of traditional village heritage values.

The introduction of the landscape gene theory represents a significant advancement in settlement research. In the 1990s, Liu Peilin proposed the concept of “landscape gene,” derived from the “cultural gene.” The landscape gene is an extension of the cultural gene concept. However, the studies did not reveal the inherent relationship between cultural genes and landscape genes, nor did they discuss the potential use of both in combination.

Currently, research on traditional village genes is primarily focused on the following aspects: Firstly, local identity formation and cultural heritage preservation from the perspective of cultural genes (Hill 2003a; Medina 2003); Secondly, the principles and methodologies for identifying, extracting, and categorizing landscape genes (Auclair and Fairclough 2015; Taylor 2009); Thirdly, the construction, expression, and variation mechanism of landscape gene information (Hu et al. 2015). However, there are still significant shortcomings in existing research. The distinctions and connections between cultural genes and landscape genes are relatively ambiguous, particularly the role of their combination in the integrity of genetic information expression has not been elucidated, and the concept of “culture-landscape genes” has not been precisely defined (Hu and Peilin 2009). Closing these research gaps is crucial for fostering the advancement of traditional village gene theory. Furthermore, there is a dearth of applied research in these areas.

In conclusion, the study of traditional villages has a longstanding history, with considerable accomplishments in areas such as settlement forms, characteristic values, textures, classifications, and heritage preservation. Over the past few decades, particularly from the perspective of cultural landscape and traditional village genes theory, significant breakthroughs have been made in research. However, there remain challenges, such as the incomplete Settlement Genes theory and the lack of systematic and applied research (Li 2021; Qi et al. 2019).

1.3. Our study

This study is founded on the “culture-landscape genes” theory for the sustainable development of traditional villages. In light of the limitations of past single settlement gene research perspectives, this study proposes the culture-landscape gene and its double-chain model. The objective of this model is to promote the conservation and sustainable development of traditional villages, and it offers methodology and practical experience to resolve the real issues of the disappearance of traditional villages and the diminishing cultural landscape diversity worldwide. In parallel, this study lays the groundwork for the construction of a cultural landscape gene database for traditional villages, facilitating digital conservation and utilization.

The article primarily centers on three research inquiries: First, it delves into the method of creating a double-chain model for culture-landscape genes, elucidating the underlying principles; Second, it scrutinizes the procedural steps and scope of the double-chain model, which involves identifying, extracting, corresponding, encoding, mapping, and comprehensively appraising culture-landscape genes; Third, building on the research findings, it examines how to categorize and grade traditional village resources, and further proposes sustainable development strategies.

2. Conceptual framework

2.1. Cultural genes

Cultural genes are non-biological genes relative to biological genes. It mainly refers to the smallest information unit and the smallest information link that are inherited and acquired, active or passive, consciously or unconsciously, and put into the human body. It is mainly manifested in beliefs, habits, values and so on (Dawkins 2006). Research has shown that cultural genes are inherent cultural factors unique to traditional settlements, serving as the basic structure for carrying cultural genetic information, an important reference for identifying traditional villages’ characteristics (Dawkins 2006; Liu 2011).

2.2. Landscape genes

The cultural factors that have been passed down from generation to generation in traditional settlements and have a decisive impact on the formation of settlement landscapes are defined as landscape genes. Landscape genes usually refer to the form of material existence, mainly including explicit content, such as historical buildings, totem symbols, spatial layout, environmental factors (Hu and Peilin 2009).

2.3. “Culture-landscape genes” and “double-chain” research model

2.3.1. Culture-landscape genes

Based on previous research results, this study proposes the concept of “culture-landscape genes” and its “double-chain” research model. The culture-landscape genes of traditional villages combine external landscape genes and internal cultural genes that are organically combined through corresponding relationships. The external landscape genes include physical forms such as architectural genes, environmental genes, layout genes, and logo genes, specifically manifested as residential buildings, churches, terrain, landform, settlement layouts, totems, etc. Cultural genes include historical genes, national cultural genes, regional cultural genes, etc., which can be specific rules or ideological forms such as language, behavior, festival customs, craftsmanship, patriarchal rituals, beliefs, Feng-shui, etc (Hu and Peilin 2009). The culture-landscape genes contain the complete genetic information of traditional villages and are the core research object for the protection and sustainable development (Table 1).

Table 1. Comparison of gene research in traditional settlements.

Difference and relation		Cultural genes	Landscape genes	culture-landscape genes
Definition		Cultural genes are the fundamental unit of cultural inheritance, comparing the transmission process of languages, concepts, beliefs, and behavioral patterns to the evolutionary process of genes within an organism (Dawkins 2006).	Landscape genes refer to cultural factors that have been passed down from generation to generation in traditional settlements and have a decisive impact on the formation of settlement landscape characteristics (Liu 2011).	The culture-landscape genes are an organic combination of external landscape genes and internal cultural genes through corresponding relationships, containing complete genetic information of settlements.
Expressions		Beliefs, habits, rules, thoughts, spirits, beliefs, etc.	Environment, architecture, layout, facilities, signage, decoration, etc.	The combination of cultural genes and landscape genes
Characteristic		Intrinsic and invisible	External and explicit	Inside-out
Concrete content		Language, behavior, festival customs, craftsmanship, patriarchal rituals, religious beliefs, feng shui ideas, etc.	Traditional dwellings, churches, terrain, landforms, courtyards, totems, etc.	Ancient towns and their historical and cultural heritage; Tusi architecture and Tusi system; Church and its teachings; National festivals and their decorations, etc.
Correspondence	One-to-one	Construction ideas adapted to mountainous terrain	Stilted building	The cultural gene chain and landscape gene chain form a double-chain model through corresponding. relationships
	One-to-many	Ethnic culture	Ancestral halls, festivals, costumes
	Many-to-one	Defending against external enemies, avoiding natural disasters, and facilitating daily life	Layout of settlements

2.3.2. “Double-chain” research model

Drawing on the DNA double helix and its internal relationship, and combining the characteristics of traditional villages, the study proposes a “culture-landscape genes double-chain model” for traditional villages (Figure 1), which means that corresponding relationships between external landscape gene chains and internal cultural gene chains organically combine the “genetic information” of traditional villages. The landscape gene elements of traditional villages form a landscape gene chain through a particular arrangement and combination. The same goes for cultural genes. The two form a double-chain genome by establishing relationships similar to biological gene base pairs (Liu, Liuchunla, and Yunyuan 2011). The process is “Cultural or landscape gene element – Cultural or landscape gene chain – Culture-landscape double-chain genome”, which preserves the complete genetic information of traditional villages (Yang 2019) (Figure 2).

Figure 1. “Culture-landscape genes double-chain” research model (revised based on Xiaojun Yang in 2019 (Yang 2019)).

Figure 2. Analysis of the culture-landscape gene double-chain model.

3. Materials and methods

3.1. Research area

Shizhu Tujia Autonomous County (hereinafter referred to as “Shizhu County”) is located on the southern bank of the upper reaches of the Yangtze River in the eastern part of Chongqing, China. It is situated between 107 ° 59 ”−108 ° 34‘ E and 29 ° 39 ’−30 ° 33” N, with a total area of 3014 km² (Yu 2021). It belongs to the humid monsoon zone of the central subtropical region. The annual average temperature is 16.5 ℃ (Yu 2021). Shizhu County is a national-level comprehensive tourism zone and a forest health base in China. The traditional villages in Shizhu County have undergone a long history of over 1400 years and have unique advantages in natural scenery, ethnic customs, historical heritage, cultural resources and ecological environment. Villages mainly composed of the Tujia ethnic group have obvious characteristics, prominent culture and inheritance values. Shizhu County exhibits unique cultural differences in terms of settlement morphology, living customs, and cultural beliefs. It is a typical representative of Tujia people settlements in Chongqing and even in China, with important cultural value and protection significance.

There are a total of 17 traditional villages in Shizhu County until 2022 (Yu 2021). Among them, 11 traditional villages of Tujia people nationality were included in the sixth batch of Chinese traditional villages list, and selected as the research objects in this study (Table 2, Figure 3). Basic data are collected by online and offline surveys simultaneously. And geographic coordinates data are obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn/) (Li and Huang 2022). Digital Elevation Model (DEM, 30 m × 30 m) data are from geospatial data clouds (http://www.gscloud.cn/). Data on urban boundaries, roads, mountains, water systems, natural resources, and climate are provided by the local Natural Resources and Planning Bureaus, Meteorological Bureaus, and other departments (Yang and Peilin 2010). The layout, architecture, culture, and evaluation data are obtained through an extensive collection, comprehensive comparison, and systematic organization through various methods such as literature review, social surveys, on-site surveys, and questionnaire surveys (Crouch 1992).

Figure 3. (a) China; (b) Chongqing; (c) study area.

Table 2. Basic situation of Tujia traditional villages of this study in Shizhu County.

Serial number	Village name	Township	Longitude	Latitude
1	Shanhe Village	Huanghe Town	108.337996	29.878464
2	Honghe Village	Xinle Town	108.479347	29.897946
3	Dabao Village	Sanyi Town	108.28672	30.157305
4	Muping Village	Longtan Town	108.311875	29.812472
5	Huayuan Village	WangjiaTown	108.321167	30.369379
6	Shuangtang Village	Fengmu Town	108.502871	30.204276
7	Taoyuan Village	Sand Town	108.484995	30.073755
8	Anqiao Village	Shijia Town	108.342827	30.309326
9	Yuquan Village	Shazi Town	108.448043	30.050734
10	Shangsheng Village	Jinzhu Town	108.468721	29.981503
11	Xinjian Village	Xinle Town	108.478611	29.931632

3.2. General research ideas

Based on the research theory proposed in this article, combined with the characteristics of the research object, the connotation of culture-landscape genes and the double-chain research model are extended to guide the protection and sustainable development of traditional villages. Therefore, the following research ideas are proposed. Firstly, we should extract the cultural and landscape genes of the research object, and identify the expression forms, and build corresponding relationships between them. Secondly, we can encode culture-landscape genes and construct their maps, providing a basis for constructing an evaluation index system. Thirdly, we could establish a culture-landscape genes evaluation system, and conduct the comprehensive evaluation. Finally, protection and development strategies for traditional villages are formulated to achieve sustainable development (Figure 4).

Figure 4. General framework of the study.

3.3. Gene identification, extraction and correspondence

3.3.1. Gene identification and extraction

The task of gene recognition and extraction is to establish a complete model of gene structure. The four principles of landscape genes recognition, namely the intrinsic uniqueness (intrinsic causes), extrinsic uniqueness (extrinsic landscapes), local uniqueness (essential elements), and overall dominance (factors that appear unique than other similar regional phenomena) of landscape features are used for the culture-landscape genes identification (Hu et al. 2015). Recognition experiences such as record extraction, structure extraction, element extraction, pattern extraction, meaning extraction, region extraction, reference extraction, and tools such as GIS, BIM, CAD and 3D scanning are utilized to identify and extract cultural and landscape genes (Hu et al. 2015). If the culture or landscape has multiple features, the most important and easily recognizable features are extracted as the Culture-landscape Gene elements (Yang 2019).

3.3.2. Establishment of correspondence relationships

Based on the culture-landscape double-chain model and the characteristics of traditional villages in Shizhu County, the identified cultural and landscape genes are recognized as target genes, then decomposed into criterion and indicator layers (Li and Huang 2022). Then the corresponding landscape and cultural genes are identified to correspond to them, respectively, forming a double-chain model. The identification of culture-landscape genes and the establishment of their corresponding relationships provide essential references for the construction of gene evaluation indicators and the determination of their weights.

3.4. Gene coding and map construction

3.4.1. Gene coding

The culture-landscape genes are encoded and classified according to the principle of merging similar species (Yang 2019). Referring to information coding theory and combining the characteristics of culture-landscape Gene classification, we propose a coding model “Regional administrative + English letters + Arabic numerals” (Yang 2019). This code has five levels, region, gene, criterion, indicator and gene element. The regional category is represented by the first 6 Arabic numerals of the regional administrative code. For example, “500240” is the first six digits of the regional administrative code in Shizhu County, which is convenient for regional identification and conducive to building a unified database. The combination of “gene layer” and “criterion layer” uses the initial letters of this type in English, such as “EC,” representing the climate in the environmental genes. The “indicator layer and gene element” are represented by 2 Arabic numerals, such as EC01 (temperature) and EC02 (precipitation). The gene element is the numbering of the final feature types presented by the “indicator class,” such as mountains (01), hills (02), flat land (03), etc. If the levels cannot be subdivided, “00” represents their code point (Hu et al. 2015). The gene coding methods lay the foundation for the indicator coding of the following gene evaluation system and the future construction of the regional culture-landscape genes database.

3.4.2. Gene map construction

The typical maps of landscape genes are constructed through plane geometry symbols, solid geometry symbols, image symbols, pictographic symbols, GIS special maps (obtained through ArcGIS spatial analysis and overlay analysis), and other data types (Deng and Yong 2006). In addition, the graphic expression of prominent culture-landscape features such as the location, shape, color, size, texture, and connotation of genetic information provides necessary preparations for the further detailed and intuitive description of culture-landscape genes, determining the importance and completeness of indicators, contributing to the construction of a cultural landscape gene database (Yang 2019).

3.5. Establishing an evaluation system

3.5.1. Establish a comprehensive evaluation index system

Drawing on the feature deconstruction recognition method (Hu et al. 2015) and combining with local genetic characteristics, the comprehensive evaluation (P) of culture-landscape genes in the sustainable development of traditional villages is taken as the target layer. Environmental genes (E), layout genes (L), cultural genes (C), and architectural genes (A) are the criterion layers. The criteria layer consists of terrain slope (ET), climate (EC), landscape pattern (EM), location transportation (EL), land resources (ES), settlement layout (LW), street space (LS), historical and cultural (CH), folk culture (CF), building (AM), and ancillary facilities (AS); Terrain (ET01), elevation (ET02), slope (ET03), temperature (EC01), precipitation (EC02), etc. constitute indicator layers. A total of 1 target layer, 4 gene layers, 11 criterion layers, and 26 indicator layers are constructed as a comprehensive evaluation index system for the culture-landscape genes of traditional villages in Shizhu County (Li and Huang 2022) (Table 3).

Table 3. Comprehensive evaluation index system for culture-landscape genes.

Target layer	Gene layer	Weight	Criterion layer	Weight	Indicator layer	Weight
Comprehensive evaluation of indicator layer culture -landscape Genes in the sustainable development of traditional villages (P)	Environmental genes (E)	0.2654	Terrain and slope (ET)	0.0274	Terrain (ET01)	0.0148
					Elevation (ET02)	0.0081
					Slope (ET03)	0.0045
			Climate (EC)	0.0215	Temperature (EC01)	0.0143
					Precipitation (EC02)	0.0072
			Landscape pattern (EM)	0.0165	Mountain range (EM01)	0.0110
					River system (EM02)	0.0055
			Location and transportation (EL)	0.1348	Location (EL01)	0.0449
					Transportation (EL02)	0.0898
			Land resource (ES)	0.0652	Farmland（ES01）	0.0217
					Woodland (ES02)	0.0435
	Layout genes (L)	0.1104	Settlement layout (LW)	0.0946	Overall layout (LW01)	0.0631
					Individual layout (LW02)	0.0315
			Street space (LS)	0.0158	Flat space (LS01)	0.0105
					Cross-sectional space (LS02)	0.0053
	Architectural genes (A)	0.2150	Building (AM)	0.1792	Building structure (AM01)	0.0966
					Roof form (AM02)	0.0533
					Building material (AM03)	0.0293
			Ancillary facilities (AS)	0.0358	Color decoration (AS01)	0.0090
					Architectural courtyard (AS02)	0.0269
	Gene of culture (C)	0.4092	History and culture (CH)	0.1364	Historical time (CH01)	0.0455
					Historic site (CH02)	0.0909
			Ethnic and folk culture (CF)	0.2728	Ethnic culture (CF01)	0.0262
					Religious belief (CF02)	0.0439
					Folk art (CF03)	0.1271
					Living customs (CF04)	0.0756

Note: Consistency of judgment matrix: 0.0086.

We use the Delphi method to determine the weight consultation value of the indicator layer. This survey invites a total of 16 practitioners (associate professors and above) from the landscape and related industries to jointly rate the weight of landscape gene evaluation, including 8 professionals in landscape architecture, 5 professionals in planning, and 3 professionals in architecture. We use the AHP method to determine the final weight value. The basic principle is to use YAAHP software to compare the importance of evaluation indicators with respect to a certain evaluation objective, obtain the judgment matrix A, and then calculate the eigenvector corresponding to the maximum eigenvalue of A, normalize it to obtain the weight value of the evaluation indicators and pass consistency check (Tang 2020) (Table 3).

3.5.2. Obtaining evaluation index values

The basic data of the 26 evaluation indicators were quantified (Table 4). The quantitative processing was carried out using the grading scoring method, and in order to make the evaluation results comparable in other regions, the maximum, minimum and plural values of the values of each indicator in the study area or in a wider range were considered, and the grading standard of each quantitative indicator (e.g., ET02, ET03, EC01, EC02, ES01, ES02, and CH01) was calibrated based on the plural number; the qualitative indicators were determined by referring to the relevant literature of the previous studies and determined by combining the characteristics of traditional villages (Li and Huang 2022; Yang and Peilin 2010).

Table 4. Quantitative scoring criteria for indicators.

Indicator layer	Quantitative scoring of evaluation indicators
	First class (5 points)	Second class (4 points)	Third class (3 points)	Fourth class (2 points)	Fifth class (1 point)
ET01 (Li and Huang 2022)	Plain	Hilly	Low mountain	Medium height mountains	High mountain
ET02	Below 500 m	500~1 000 m	1 001~2 000 m	2 001~3 000 m	Above 3 000 m
ET03	0~8°	8.1~15°	15.1~25°	25.1~35°	35.1~90°
EC01	15.1~20 ℃	20.1~25 ℃	5~15 ℃	25.1~30 ℃	<5 °C or >30 °C
EC02	1 001~1 200 mm	801~1 000 mm	500~800 mm	1 201~1500 mm	<500 mm or>1 500 mm
EM01 (Li and Huang 2022)	Very rich	Richer	General	Lesser	Very little or none
EM02 (Li and Huang 2022)	Very rich	Richer	General	Lesser	Very little or none
EL01 (Li 2021)	Very good	Relatively good	General	Poor	Very poor
EL02 (Yang and Peilin 2010)	Very convenient	Convenient	General	Less convenient	Very inconvenient
ES01	More than 100,000 hm^2	50,000~100,000 hm^2	30,000~50,000 hm^2	10,000~30,000 hm^2	Less than 10,000 hm^2
ES02	More than 150,000 hm^2	100,000~150,000 hm^2	50,000~100,000 hm^2	30,000~50,000 hm^2	Less than 30,000 hm^2
LW01 (Li and Huang 2022)	Very complete	Relatively complete	General complete	Incomplete	Very incomplete
LW02 (Li 2021)	Very complete	Relatively complete	General complete	Incomplete	Very incomplete
LS01 (Li and Huang 2022)	Very reasonable	Relatively reasonable	General	Unreasonable	Very unreasonable
LS02 (Li 2021)	Very reasonable	Relatively reasonable	General	Unreasonable	Very unreasonable
AM01 (Yang and Peilin 2010)	Very complete and typical	More complete and typical	General	Incomplete or atypical	Very incomplete or atypical
AM02 (Yung and Chan 2012)	Quite typical	Classic	General	Not typical	Very atypical
AM03 (Yang and Peilin 2010)	Very characteristic	Distinctive	General	Less distinctive	Featureless
AS01 (Yung and Chan 2012)	Very characteristic	Distinctive	General	Less distinctive	Featureless
AS02 (Li and Huang 2022)	Quite typical	Classic	General	Not typical	Very atypical
CH01	More than 2,000 years	1,001 to 2,000 years	501 to 1,000 years	100–500 years	Less than 100 years
CH02 (Li 2021)	Very complete and typical	More complete and typical	General	Incomplete or atypical	Very incomplete or atypical
CF01 (Li and Huang 2022)	Very rich	Richer	General	Lesser	Very little or none
CF02 (Li 2021)	Very rich	Richer	General	Lesser	Very little or none
CF03 (Li and Huang 2022)	Priceless	More valuable	General	less valuable	valueless
CF04 (Li 2021)	Very characteristic	Distinctive	General	Less distinctive	Featureless

The basic evaluation data is mainly obtained through on-site visits, interviews, questionnaire surveys, literature review, social surveys, open-source data analysis, expert consultation, and other methods. Among them, ET01, ET02, ET03, EC01, EC02, and CH01 are mainly obtained through open-source data analysis, supplemented by literature review. Other evaluation indicators were mainly obtained through on-site surveys (3 times) from February to April 2023, on-site interviews (22 local villagers), questionnaire surveys (200 copies, 100 copies online and 100 copies offline), and expert consultations (over 40 people including face-to-face interviews, phone calls, WeChat, etc.) (Diane, Stokes, and Atsuko 2001). The questionnaire survey takes local residents and tourists in Shizhu County as the survey objects, and the evaluation index system (Table 3) and the scoring criteria (Table 4) are used as the questionnaire content. A total of 300 questionnaires were distributed in this survey, and 288 valid questionnaires were collected. This method corrects the data appropriately. Firstly, we need to eliminate data that is highly repetitive, logically inconsistent, and does not answer the question correctly. Secondly, we use SPSSPRO software to identify outliers in the data. Finally, based on the characteristics of this type of data, we replace outliers with averages or outliers to reduce the interference of outliers on the results (Crouch 1992). We use the weighted average method in the fuzzy comprehensive evaluation method. And the calculation formula is as follows:

$\begin{array}{rl}& Tij=\sum _{i=1}^{n}DiQij\\ & Ti{j}^{\prime }=Min\left[Tij,1\right]\end{array}$

Where, T_ij is the calculated result vector, and D_i represents the weight value of the indicator layer. Q_ij is the evaluation result of different levels of a single indicator, where i is the number of indicator layers, j is the number of evaluation levels, and T_ij’ is the smaller value between T_ij and 1. The resulting vector is calculated using the above formula (Diane, Stokes, and Atsuko 2001; Li and Huang 2022). Subsequently, the fuzzy evaluation result vector is transformed into specific numerical values using grade parameters, thus completing the comprehensive evaluation of the culture-landscape genes of traditional villages in Shizhu County.

4. Results

4.1. Identification of culture-landscape genes and establishment of corresponding relationships

Based on the method of identifying, refining, and corresponding culture-landscape genes proposed in Chapter 3.3, the culture-landscape genes and their corresponding relationships of traditional villages are shown in Table 5.

Table 5. Traditional village culture-landscape genes and the corresponding relationships.

Target gene		Criterion layer	Indicator layer	Gene element	Corresponding genes
External landscape genes	Environmental genes	Terrain and slope	Terrain	Mountainous region	For defense and convenience in life	Corresponding cultural genes
			Elevation	Altitude 500-1000m	To avoid natural disasters
			Slope	Slope 8–15°	Easy to build
		Climate	Temperature	Cool summer	Suitable for avoiding heat
			Precipitation	Spring plum rain season	Beneficial to agricultural production
		Landscape pattern	Mountain range	Wushan, Zhongshan	Feng-shui thought
			River system	Upper Yangtze River	Beneficial to production and daily life
		Location and transportation	Location	Eastern Chongqing	Beneficial to development
			Transportation	Convenient transportation	For the convenience of travel
		Land resource	Farmland	Cultivated land resources are relatively average	Ensuring survival
			Woodland	Rich forest resources	Beneficial to production
	Layout genes	Settlement layout	Overall layout	Stripmap	Easy to connect
			Individual layout	Quadrangle dwellings	Defensive ideology
		Street space	Flat space	Vertical contour line	Utilizing mountain terrain
			Cross-sectional space	D/H approximates to 0.618	Easy to layout
	Architectural genes	Building	Building structure	Stilted building	Adapt to mountainous terrain
			Roof form	Suspended peak	Adapt to rainy weather
			Building material	Grey tile	Durable
		Ancillary facilities	Color decoration	White, gray and black	The color preferences of the locals
			Architectural courtyard	Patio courtyard	Gatherings and chats
Intrinsic cultural genes	Gene of culture	History and culture	Historical time	Over 1000 years of history	Historical site of Qin Liangyu cemetery	Corresponding landscape genes
			Historic site	Ancient town culture	Xituo Ancient Town
		Ethnic and folk culture	Ethnic culture	Tusi culture	Tusi architecture
			Religious belief	Buddhist culture	Buddhist resort Ginkgo Hall
			Folk art	Waving dance	Hand waving dance costumes
			Living customs	Bizka Festival	Bizka Festival decoration

4.2. Culture-landscape gene coding and map construction

According to the method described in 3.4, the results of culture-landscape gene coding and mapping are shown in Table 6. In addition, GIS analysis methods are used to construct terrain elevation maps (Figure 5a), slope maps (Figure 5b), location maps (Figure 3), transportation maps (Figure 5c), and land resource maps (Figure 5d).

Figure 5. (a) Topographic elevation map of traditional villages in Shizhu County; (b) slope map of traditional villages; (c) map of traditional village location; (d) distribution map of main land resources.

Table 6. Gene coding and mapping of culture-landscape.

Indicator system and codes	Gene elements	Gene coding	Typical graphs
Terrain (ET01)	Mountainous region	500240ET0101	Figure 5a
Elevation (ET02)	Altitude 500-1000m	500240ET0202	Figure 5a
Slope (ET03)	Slope 8–15°	500240ET0303	Figure 5b
Temperature (EC01)	Cool summer	500240EC0102	—
Precipitation (EC02)	Spring plum rain season	500240EC0201
Mountain range (EM01)	Wushan, Zhongshan	500240EM0102
River system (EM02)	Upper Yangtze River	500240EM0201
Location (EL01)	Eastern Chongqing	500240EL0101	Figure 3
Transportation (EL02)	Convenient transportation	500240EL0202	Figure 5c
Farmland（ES01）	Cultivated land resources are relatively average	500240ES0103	Figure 5d
Woodland (ES02)	Rich forest resources	500240ES0202	Figure 5d
Overall layout (LW01)	Strip map	500240LW0103
Individual layout (LW02)	Quadrangle dwellings	500240LW0201
Flat space (LS01)	Vertical contour line	500240LS0102
Cross-sectional space (LS02)	D/H approximates to 0.618	500240LS0203
Building structure (AM01)	Stilted building	500240AM0103
Roof form (AM02)	Suspended peak	500240AM0202
Building material (AM03)	Grey tile	500240AM0301
Color decoration (AS01)	White, gray and black	500240AS0101
Architectural courtyard (AS02)	Patio courtyard	500240AS0204
Historical time (CH01)	Over 1000 years of history	500240CH0104	—
Historic site (CH02)	Ancient town culture	500240CH0201
Ethnic culture(CF01)	Tusi culture	500240CF0101
Religious belief (CF02)	Buddhist culture	500240CF0203
Folk art (CF03)	Waving dance	500240CF0301
Living customs (CF04)	Bizka Festival	500240CF0401

4.3. Culture- landscape gene evaluation results

4.3.1. Gene evaluation results

The collected data from the questionnaire survey are organized, calculated, and summarized, and combined with the method described in section 3.5, the genetic evaluation results of the traditional village cultural landscape in Shizhu County are obtained in Table 7. Both the Cronbach coefficient and the standardized Cronbach coefficient of the project obtained by SPSS are above 92%, indicating that the data have high consistency and strong reliability (Tang 2020).

Table 7. Genetic evaluation results of traditional village culture-landscape in Shizhu County.

Gene layer	Criterion layer	Indicator layer	Evaluation score (QL)
			Shanhe Village	Honghe Village	Dabao Village	Muping Village	Huayuan Village	Shuangtang Village	Taoyuan Village	Anqiao Village	Yuquan Village	Shangsheng Village	XinjianVillage	Arithmetic mean
Environmental genes (E)	Terrain and slope (ET)	Terrain (ET01)	3.4897	3.0756	3.9135	2.8768	3.9787	3.7653	3.5231	3.3944	3.2331	3.6578	3.6261	3.5031
		Elevation (ET02)	3.5043	3.8578	4.5152	3.7764	4.6183	4.5123	3.7212	3.46335	3.8465	3.5786	3.42575	3.8927
		Slope (ET03)	2.823	3.1876	3.6322	3.1655	3.6334	3.5352	3.1568	3.0876	3.2567	2.9123	2.76457	3.1959
	Climate (EC)	Temperature (EC01)	4.1078	3.6653	4.4325	4.0983	4.1896	4.3643	4.10678	4.2832	3.8876	3.6764	3.79432	4.0551
		Precipitation (EC02)	3.7658	3.8863	4.6432	3.9876	4.1763	4.3653	3.6214	3.5325	3.7568	3.8643	3.6954	3.9359
	Landscape pattern (EM)	Foothill(EM01)	4.5631	3.4323	4.6135	3.5897	4.7635	4.6543	4.4322	4.7157	3.8988	3.4112	3.6318	4.1551
		Rivers (EM02)	4.2157	4.2976	4.4123	3.7895	4.2398	4.5678	4.1568	4.4679	4.1893	4.1865	3.6317	4.1959
	Location and transportation (EL)	Location (EL01)	3.0878	3.3568	4.0345	3.2789	4.2326	4.1078	3.2233	3.2136	3.2976	3.3753	3.3347	3.5039
		Transportation (EL02)	3.9887	3.1678	4.6123	3.9898	4.6328	4.4123	3.9987	3.9893	3.9789	3.9637	4.07531	4.0736
	Land resource (ES)	Farmland（ES01）	2.9976	3.4689	3.3865	3.1643	3.7623	3.8197	2.9632	3.6231	3.3135	3.5632	3.3333	3.3996
		Woodland (ES02)	4.1768	4.0189	4.7087	4.2878	4.5658	4.5678	4.3758	4.3689	4.3324	4.1789	4.0449	4.3297
Layout genes (L)	Village layout (LW)	Overall layout (LW01)	2.8765	2.9863	3.3213	3.0987	3.1678	3.2876	3.0876	3.1897	2.8767	3.1232	3.0846	3.1
		Individual layout (LW02)	2.9753	3.0345	3.5136	2.3562	3.4789	3.3232	3.2976	3.0987	2.9532	2.8568	2.9073	3.0723
	Street space (LS)	Flat space (LS01)	3.5769	3.3896	3.9326	2.9893	3.8149	3.6467	3.6873	3.5389	3.5973	3.0785	3.3668	3.5108
		Cross-sectional space (LS02)	3.7864	3.0132	4.2356	3.1578	4.1236	3.7998	3.8978	3.8867	3.8635	3.5898	3.8067	3.7419
Architectural genes (A)	Building (AM)	Building structure (AM01)	3.8783	3.8213	4.5789	3.1892	4.4872	4.2756	4.0389	3.9232	3.8017	3.1135	3.2994	3.8552
		Roof form (AM02)	3.5672	3.7122	4.3632	3.1735	4.4321	4.2538	3.5121	3.3356	3.5987	3.1135	3.0265	3.6444
		Building material (AM03)	3.4213	3.5987	4.2211	2.7876	4.3028	4.3323	3.1245	3.4899	3.2436	3.3233	2.9046	3.5227
	Ancillary facilities (AS)	Color (AS01)	3.3218	2.8893	3.9213	3.0122	3.8328	3.7314	3.6454	3.5578	3.5768	2.9891	3.0409	3.4108
		Courtyard (AS02)	3.5672	3.3122	3.8632	3.6735	3.8321	3.7538	3.6121	3.5356	3.4987	3.1135	3.2265	3.5444
Gene of culture (C)	History and culture (CH)	Time (CH01)	3.6976	4.0533	4.3578	3.3893	4.3123	4.1221	3.9873	3.8689	3.7998	3.4356	3.4129	3.8579
		Historic site (CH02)	3.7567	3.8976	4.0367	2.7869	4.1897	3.9128	3.8378	3.9562	3.8211	3.5788	3.6286	3.7639
	Ethnic and folk culture (CF)	Ethnic culture (CF01)	3.5135	3.4914	3.7321	2.8796	3.8136	3.6097	3.3355	3.1896	3.0344	3.0135	2.76745	3.3073
		Religious belief (CF02)	3.7993	3.2355	4.1233	3.6123	4.6135	4.0897	3.7989	3.8899	3.7706	3.5012	3.368	3.8002
		Folk art (CF03)	3.6125	3.2873	4.1567	3.0869	4.1762	4.0356	3.8098	3.6893	3.7879	3.2238	3.0838	3.6318
		Living customs (CF04)	3.6876	3.0332	3.8233	2.9135	3.9012	3.7099	3.5767	3.4989	3.5312	3.1418	2.8357	3.423
Comprehensive scores			3.6258	3.4607	4.1395	3.2526	4.1746	4.0231	3.7074	3.6927	3.6348	3.3785	3.3315	3.6746

According to the scores of the culture-landscapes genes (Table 7), the comprehensive scores of traditional villages are mainly concentrated in three intervals. Traditional villages with a comprehensive score of 4.0 or above include Dabao Village, Huayuan Village, and Shuangtang Village. The overall scores of the three villages are high, especially in terms of terrain slope, climate, mountain and water pattern, location transportation, forest resources, historical culture and traditional architecture, with scores above 4.0. The traditional villages with a comprehensive score of 3.5–4.0 include Taoyuan Village, Yuquan Village, Shanhe Village, and Anqiao Village. The overall score is relatively high, with individual scores exceeding 4.0 for climate, landscape pattern, and forest resources. traditional villages with a comprehensive score of 3.0–3.5 include Shangsheng Village, Muping Village, Xinjian Village, and Honghe Village. Overall, the scores are relatively low, especially in location, transportation, layout, folk art, building materials, and color decoration, with most scoring below 3.5 points. However, Honghe Village had a higher score in the building, exceeding 3.5 points. The “Arithmetic mean” in Table 7 represents the overall evaluation of various indicators of the traditional villages. Among them, the evaluation of temperature, mountains, water systems, transportation, forest resources and other indicators are relatively high, with the average scores of more than 4 points. The evaluation of indicators slope, cultivated land resources, individual layout, ethnic culture, and color decoration is relatively low, with an average score of less than 3.5 points.

5. Discussion

5.1. Discussion on the grading of traditional villages

Based on the culture-landscape gene evaluation scores (Table 7), combined with field investigations, the traditional villages in Shizhu County are categorized into three levels (Table 8, Figure 6). Those scoring 4.0 or higher are classified as first-class traditional villages, including Dabao Village, Huayuan Village, and Shuangtang Village. Dabao Village and Shuangtang Village benefit from their proximity to Huangshui National Forest Park, exhibiting clear advantages in transportation, location, and forest resources. Meanwhile, Huayuan Village, situated close to the national primary road and religious center, possesses significant advantages in transportation, religion, and architecture. Villages scoring between 3.5 and 4.0 are considered second-class traditional villages, including Taoyuan Village, Yuquan Village, Shanhe Village, and Anqiao Village. In addition to their attractive environments and pleasant climates, most of these villages are located near national or provincial roads, thereby boasting notable transportation advantages. Villages with scores below 3.5 are labeled as third-class traditional villages, including Shangsheng Village, Muping Village, Xinjian Village, and Honghe Village. These villages lack significant transportation and location advantages. However, a stable ecological environment and suitable climate represent significant potential factors.

Figure 6. Classification and evaluation of traditional villages in Shizhu County.

Table 8. Evaluation results and suggestions for traditional village classification.

traditional village classification	Scores	Including villages	Recommendation strategies
First-class traditional villages	Above 4.0 points	Dabao Village, Huayuan Village, Shuangtang Village	They should be given priority protection and promotion, and can be listed as a demonstration village for traditional villages.
Second-class traditional villages	3.5–4.0 points	Taoyuan Village, Yuquan Village, Shanhe Village, Anqiao Village	Settlements focused on construction and improvement, can be listed as backup targets for traditional demonstration villages.
Third-class traditional villages	Below 3.5 points	Shengsheng Village, Muping Village, Xinjian Village, Honghe Village	Conservative development strategies should be adopted.
traditional village groups		Taoyuan Village, Yuquan Village, Shangsheng Village, Xinjian Village, Honghe Village	They can integrate the resources of 5 villages to form a scale effect.
Characteristic traditional village tourism demonstration county		All traditional villages in Shizhu County	By constructing a Culture-landscape Gene chain and network, they can create a demonstration county for traditional village tourism across the entire region.

5.2. Recommendations for different levels of traditional villages

The following recommendations are proposed for the protection and development of traditional villages at various levels. First-class traditional villages exhibit clear advantages in accessibility, natural resources, ecological environment, and historical culture, among other factors. They should be prioritized for protection and promotion, and listed as demonstration villages for the exhibition of Chinese traditional culture. Although traditional second-class villages may not match the first-class villages in terms of objective conditions and comprehensive scores, some possess strong potential, such as Anqiao Village and Taoyuan Village. These villages are close to national forest parks and have convenient transportation. With strengthened traditional architecture, historical inheritance, and cultural influence, these villages have a high likelihood of being upgraded to first-class settlements and possess significant investment value. Conservative development strategies should be adopted for third-class traditional villages to preserve resources and avoid destructive damage. However, Honghe Village maintains relatively intact traditional architecture, effectively displays ethnic heritage culture, and has considerable protection and development value.

t should be noted that the five villages with relatively concentrated distribution, such as Taoyuan Village, Yuquan Village, Shengsheng Village, Xinjian Village, and Honghe Village, can form traditional village groups through regional planning, integrating the advantageous resources of each village. For instance, the traditional buildings and culture of Honghe Village, the transportation of Taoyuan Village and Yuquan Village, and the social governance and environmental advantages of Shengsheng Village and Xinjian Village. Additionally, through the gene elements extracted from this study, combined with the advantages and characteristics of each traditional village, landscape nodes with different culture-landscape gene elements can be constructed. Using roads or rivers, culture-landscape gene chains and networks can be formed, creating a demonstration county of traditional village across the entire region (Table 8), thereby forming a scale effect and driving local tourism and economic development (Haiyang 2019). This approach is beneficial for the sustainable development of traditional villages.

5.3. Exploration of the impact of genome identification, extraction, and association on results

The identification, extraction, and association of culture-landscape genomes have a direct and critical impact on research outcomes. Firstly, the accuracy and completeness of gene extraction are crucial to the preservation and protection of the essential genetic information of traditional village culture-landscapes. Incorrect associations between cultural and landscape genes can influence the expression of genetic information in cultural landscapes, consequently affecting the effectiveness and sustainability of cultural heritage preservation. Variations in genomes influence the construction of subsequent evaluation systems, determination of evaluation weights, establishment of evaluation level standards, and ultimately shape the strategies and approaches for protection and development.

It is important to note that the quality and reliability of research findings depend heavily on the careful execution of each step in the process, including the identification, extraction, and association of culture-landscape genomes. This emphasizes the necessity of adopting rigorous methodologies and using reliable data sources to ensure the accuracy and integrity of research results.

5.4. Discussion on the comparison of research results between double strand model and single gene model

In the double-chain model of culture-landscape genes, the inherent cultural genes and external landscape genes of traditional village genetic information are identified and extracted from two dimensions, establishing associations between them. This approach offers a more accurate and comprehensive understanding of traditional village genetic information compared to a single gene model. Additionally, by exploring the internal mechanism of cultural or landscape formation through the association of gene chains, the expression form of genes can be improved, fostering sustainable preservation, development, and utilization of heritage information.

Under the dual chain model, the comprehensive evaluation of culture-landscape genes is based on the evaluation system developed after dual measurement of the target gene and its associated genes. This evaluation system and weight determination are more scientific, comprehensive, and objective than those of the single gene model, allowing for the formulation of more reasonable protection strategies.

It is important to note that the double-chain model of culture-landscape genes provides a more nuanced and insightful approach to understanding and evaluating traditional villages, their cultural and landscape features, and the complex interplay between them. This model enhances the ability to generate accurate and meaningful insights, ultimately supporting more effective and sustainable heritage preservation and development efforts.

5.5. Discussion on the conceptual framework of the cultural-landscape gene double-chain model

This study contributes to the further advancement of traditional village gene theory. It facilitates a deep and comprehensive understanding of the genetic value of traditional villages, effectively addressing issues such as “valuing landscape over culture,” “disconnection between landscape and culture,” and “constructive destruction,” and promoting the sustainable development of traditional villages.The double-chain model, as an innovative approach to the study of culture-landscape genes, offers a systematic and thorough methodology for exploring the intricate relationship between cultural and landscape elements in traditional villages. By adopting this model, researchers can gain a more comprehensive understanding of the genetic information and value of traditional villages, paving the way for more effective preservation and sustainable development strategies.

5.6. Discussion on the applicable scope and advantages of evaluation results

The methodology system rooted in the theory of culture-landscape genes and the double-chain model is extensively applicable in evaluating and devising traditional villages within the research domain. From the perspective of the research area, this approach holds potential to advance traditional villages globally, particularly in regions lacking top-down protection policies for traditional villages, such as underdeveloped areas in developing countries. The double-chain model’s theory and methodology facilitate scientific, systematic, and practical quantitative research on traditional village cultural heritage, which is advantageous for minimizing the influence of subjective judgments on evaluation outcomes and offers a foundation for formulating rational strategies for the preservation of regional cultural heritage.

5.7. Suggestions for research on sustainable development of traditional villages

The theory of culture-landscape genes and the double-chain model offer a comprehensive and systematic perspective for the sustainable development of traditional villages. Recommendations include: firstly, continuous study and improvement of the theory of culture-landscape genes and the dual chain models, to provide a more comprehensive theoretical system and methodology for the sustainable development of traditional villages; secondly, construction of a cultural landscape gene database during the identification, correspondence, and map-building process, laying the foundation for digital protection and utilization; thirdly, synchronizing the protection and utilization of traditional villages: protection provides the foundation for utilization, and utilization provides motivation for protection, fostering a virtuous cycle; fourthly, keeping the protection and development methods of traditional villages up-to-date with the times by incorporating modern technology and methods, necessary improvements, modifications, and innovations to adapt the expression of settlement genes to contemporary people’s material and spiritual needs; and lastly, organically linking, protecting, and developing cultural and landscape genes simultaneously to achieve sustainable development of traditional villages.

6. Conclusion

Under the culture-landscape genes theory and its double-chain model, this study focuses on traditional Tujia villages in Shizhu County, Chongqing, China, systematically developing a methodology for identifying, corresponding, coding, mapping, and comprehensively evaluating culture-landscape genes of such villages. Based on this methodology, traditional villages are categorized and evaluated, and corresponding protection and development strategies are proposed. The research demonstrates that the identification, refinement, and association of culture-landscape genomes have a direct impact on research outcomes. Compared to the single-gene research model of either culture genes or landscape genes, the double-chain model’s evaluation system and weights are more scientific, resulting in more comprehensive and reliable conclusions.

This research is beneficial for the conservation and sustainable development of regional traditional villages and can be adapted for other villages around the world after adjusting the indicator system according to regional characteristics, particularly for those lacking top-down policy support. The study promotes the advancement of the genetic theory of traditional settlements, provides novel theoretical support and practical reference for the sustainable development of such villages, and establishes a foundation for researching digital preservation and utilization of regional traditional culture. Future research will optimize the culture-landscape gene double-chain model and its methodology, expand the study scope to the macro level, further analyze and improve the evaluation index system, and promote the development and application of the culture-landscape genes theory and its double-chain model for traditional villages.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets used or analyzed during the current study are available in the article/from the corresponding author on request.

Additional information

Funding

This research was funded by the Natural Science project of Chongqing College of Humanities, Science & Technology (grant number CRKZK2023010) and the National Natural Science Foundation of China (grant number 51978093).

Notes on contributors

Guoqing Li

Guoqing Li, associate professor (Senior Engineer), PhD student, research direction in cultural landscape and urban planning.

Binqing Chen

Binqing Chen, lecturer, research direction in industrial landscape design

Jie Zhu

Jie Zhu, professor, research direction in urban design and landscape planning

Lei Sun

Lei Sun, professor, research direction in environmental landscape design