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Article

Trends and Future Directions in Research on the Protection of Traditional Village Cultural Heritage in Urban Renewal

by
Jun Xia
1,
Xuefei Gu
2,
Tianru Fu
3,
Yangzhi Ren
4 and
Yazhen Sun
5,6,*
1
Department of Environmental Design, Dongseo University, Busan 47011, Republic of Korea
2
Department of Residential Environment, Yeungnam University, Gyeongsan 38541, Republic of Korea
3
School of Art Design and Cultural Media, Guangxi City Vocational University, Chongzuo 532199, China
4
College of Architectural Engineering, Beijing University of Technology, Beijing 100124, China
5
School of Design, ERICA Campus, Hanyang University, Seoul 04763, Republic of Korea
6
School of Art and Design, Ningxia Polytechnic University, Yinchuan 750000, China
*
Author to whom correspondence should be addressed.
Buildings 2024, 14(5), 1362; https://doi.org/10.3390/buildings14051362
Submission received: 6 April 2024 / Revised: 29 April 2024 / Accepted: 8 May 2024 / Published: 10 May 2024
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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Abstract

:
The process of urbanization has accelerated economic growth while also presenting social challenges. Urban renewal is crucial for achieving sustainable urban development, especially by preserving traditional villages as cultural heritage sites within cities. This study employs Python algorithm programming and visual analysis functions to conduct a bibliometric analysis of 408 research papers on the preservation of traditional village cultural heritage in urban renewal from 1999 to 2023 in the Web of Science core database. The objective is to examine the historical background, current status, and future trends in this area. The analysis explores cooperation networks, co-citation relationships, co-occurrence patterns, and emerging characteristics of research on traditional village cultural heritage protection in urban renewal. It focuses on various aspects, such as authors, institutions, countries, journals, documents, and keywords. The results indicate that the study of traditional village cultural heritage protection in urban renewal can be divided into three developmental stages. “Sustainable development”, “cultural heritage”, “historic urban landscapes”, and “rural revitalization” are the research hotspots and future trends in this field. The results of this study provide a comprehensive overview of the evolution of research hotspots in this field and can help researchers willing to work in this research area quickly understand the research frontiers and the general situation.

1. Introduction

Over the past decade, the global urban population has exceeded the rural population for the first time, signifying a major milestone in the global urbanization trend. To foster sustainable urban development and uphold high urbanization standards, there is a growing demand for the reorganization and enhancement of the built environment in urban areas. Urban renewal has emerged as a pivotal strategy to bolster sustainable urban development, attracting considerable attention from researchers, professionals, and government entities [1,2,3,4,5]. Urban renewal is a multifaceted process that aims to revitalize urban areas through improvements in social, economic, physical, and environmental aspects [6,7,8]. The discourse on urban renewal often emphasizes the significance of partnerships and community empowerment for achieving successful outcomes [9,10]. Atkinson (1999) examined the construction of partnership and empowerment in British urban renewal, emphasizing the role of official documents in guiding community participation [11]. McDonald et al. (2009) also highlighted the significance of multi-agency and partnership programs in implementing renewal projects for sustainable communities [12,13]. Rae (2009) compared international urban renewal strategies to analyze whose interests are prioritized in these initiatives [13]. The study demonstrated that place and identity play a crucial role in shaping the meanings and identities associated with regenerated areas. While urban renewal has gained traction in European countries such as the UK and Turkey, challenges persist in ensuring project sustainability. Korkmaz et al. (2020) noted the need for a stronger emphasis on sustainable urban renewal practices, as current initiatives have not significantly contributed to urban sustainability [14]. This underscores the importance of continuous research and enhancement in urban renewal practices for long-term positive impacts on urban areas [15,16].
The preservation of traditional village cultural heritage is becoming an increasingly important issue in urban renewal [17,18,19]. Numerous studies have addressed the challenges and opportunities related to safeguarding the cultural heritage of traditional villages worldwide [20,21]. Öter (2010) examined the impact of touristification on cultural heritage, specifically focusing on the marketing of handicrafts to tourists in Turkey. The study revealed how tourism can influence the identities of traditional villages and their cultural heritage [22]. Meskell (2013) outlined three critical challenges faced by the UNESCO World Heritage Convention, emphasizing the need for international cooperation in preserving cultural and natural heritage sites, including traditional villages [23,24]. Radzuan et al. (2015) investigated incentives for conserving traditional settlements in Japan. The study emphasized the importance of public awareness and legal frameworks for protecting cultural properties, providing valuable insights into residents’ perspectives on heritage conservation [24,25]. Giannakopoulou et al. (2016) examined the attitudes of local residents and visitors towards conserving architectural heritage in a Greek village. Their research demonstrated that well-maintained local heritage can enhance tourism development and yield economic benefits by preserving cultural heritage [26,27,28]. Li et al. (2020) conducted a case study evaluating and optimizing traditional dwelling conservation practices in China. The study focused on the restoration project of Cheng Zhi Hall in Hongcun, emphasizing the significance of identifying and resolving issues in conservation practices to preserve the authenticity and sustainability of traditional village architecture [29]. Therefore, research findings on the protection of traditional village cultural heritage during urban renewal are increasingly emerging and have gradually become a pivotal issue for the coordinated development of urban and rural areas and the advancement of human civilization.
Urban renewal is the process of repurposing resources and reconstructing urban environments to align with the needs of modern urban development [30,31]. Traditional villages serve as important repositories of historical memory, human ecology, architectural aesthetics, and social development [32,33]. However, traditional villages, with their unique historical and cultural significance, are often undervalued during urban renewal efforts, leading to the alteration or disappearance of these important heritage sites and resulting in irreversible cultural losses and social issues [34,35,36]. Traditional villages, as distinctive rural entities, hold significant historical and cultural meanings and distinctive attributes that play crucial roles in rural–urban development [37].

2. Research Gap

Existing research has explored the safeguarding of cultural heritage in traditional villages during urban renewal from various perspectives, including community involvement, government policies, and the delicate balance between economic gains and cultural preservation [38,39,40,41]. These studies underscore the importance of empowering and engaging communities to improve the social acceptance and sustainability of preserving traditional village cultural heritage [42]. Moreover, the implementation of protection standards, financial incentives, and legal frameworks ensures a harmonious coexistence between development and preservation [43]. The integration of traditional village restoration with tourism development not only safeguards cultural heritage but also fosters local economic growth [44]. Despite the macro perspective provided by studies such as “A Comprehensive Bibliometric Analysis of Urban Renewal Research during 2012–2022” [45] and their broader exploration of urban renewal content and practices, there remains a lack of theoretical discourse specifically focusing on the protection of cultural heritage in traditional villages within urban renewal. The protection of cultural heritage in traditional villages has emerged as a key concern in urban renewal efforts. To address this research gap, the study utilized Python programming in PyCharm Community Edition version 2023.1 (JetBrains) and network analysis tools to visually analyze the literature on cultural heritage protection in traditional villages during urban renewal.
Python offers superior data processing and visualization capabilities compared to bibliometric visualization software such as Citespace [46]. It allows for the customization of complex network analysis and graphic generation algorithms to effectively showcase information within literature data [47]. This enhances data processing efficiency and visually presents analysis results through charts, improving transparency and interpretability [48]. By filtering cutting-edge articles, analyzing research trends and hotspots, and examining collaboration relationships, co-citations, and keywords, we can gain a deeper understanding of the current status, development trends, and key areas of traditional village cultural heritage protection in urban renewal.

Purpose of the Study

This study will use Python as the analytical tool to conduct cooperation, co-citation, and keyword co-occurrence analyses on reference literature related to the preservation of traditional village cultural heritage in urban renewal. The specific objectives are as follows:
  • Identify the main research forces in the field of protecting traditional village cultural heritage in urban renewal at the individual, institutional, and national levels.
  • Determine the distribution of core journals relevant to research on the protection of traditional village cultural heritage in urban renewal.
  • Distinguish the main research topics in the field of protecting traditional village cultural heritage in urban renewal and explore their knowledge structure.
  • Detect the research hotspots and frontiers in the field of protecting traditional village cultural heritage in urban renewal.

3. Research Methods

3.1. Data Collection

The Web of Science (WoS) is widely recognized as a prestigious tool for indexing scientific literature, offering valuable insights into various fields of scientific and technological research [49]. It is commonly utilized as a reliable data source for bibliometric analyses [50]. The research data for this study were primarily sourced from the Web of Science Core Collection database, focusing on the theme of “protection of cultural heritage of traditional villages in urban renewal”. Our search strategy focused on four main aspects—“urban renewal”, “traditional villages”, “cultural heritage”, and “conservation”—which were used as subject terms. To ensure a comprehensive search for keywords with similar meanings, we expanded the expressions of these four components, as shown in Table 1. The four categories were connected using “AND”, while terms within each category were linked with “OR”. Searches were conducted in the Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), and Conference Proceedings Citation Index—Science (CPCI-S) within the Web of Science core database, yielding a total of 601 articles. Furthermore, searches in the Conference Proceedings Citation Index—Social Science and Humanities (CPCI-SSH) produced an additional 205 articles, bringing the total count to 806 articles. The search was limited to articles published in English between 1999 and 2023.
Following the aforementioned search strategy, after data cleaning (standardizing formats, removing blanks, and removing duplicates), 408 articles were obtained from the 806 articles in the Web of Science core database (as of 14 September 2023). These were saved in plain text file formats (CSV and TXT), including complete bibliographic records and references. The selection process is illustrated in Figure 1.

3.2. Data Analysis

Bibliometrics is a discipline that utilizes statistical and mathematical tools to quantitatively analyze literature information, focusing on evaluating the quantity, quality, impact, and interrelationships of scientific research outputs [51]. It is an efficient method for searching, mining, analyzing, and summarizing large-scale data, utilizing modern big data and computer technologies to present analysis results in clear and concise visual knowledge graphs [52]. This enables detailed insights into quantitative information related to publications, authors, journals, countries, institutions, cited references, keywords, and more [53]. The advancement of bibliometrics provides valuable data support for academic research and research management, facilitating the development and management of scientific research [54].
Python, a high-level programming language known for its readability and scientific computing libraries, is widely used in bibliometric studies due to its scalability and conciseness [55]. Social network analysis and graph theory are common techniques in this research field, addressing topics like academic collaboration and disciplinary evolution [56]. Python excels in network data processing and analysis with libraries like NetworkX, enabling tasks such as computing centrality metrics and community structures. Additionally, Python provides visualization tools like Matplotlib to graphically represent network structures, showing node characteristics and dynamic changes. Overall, Python is crucial in bibliometric research, offering strong capabilities in social network analysis and graph theory to assist researchers in handling and analyzing complex data effectively [57]. Researchers can take advantage of Python’s capabilities to process and analyze web data more efficiently, thereby contributing to the development and innovation of the bibliometrics field [58].

4. Results

4.1. Cooperation Relationship Analysis

Collaborative paper writing is a crucial aspect of scientific cooperation, which encompasses collaborations at various levels—individual, institutional, and national [59]. By conducting collaborative writing analysis, we can delve into the status and roles of authors across different levels of collaboration networks, namely, micro, meso, and macro. This analysis allows us to identify outstanding researchers in the global realm of urban renewal for the preservation of cultural heritage in traditional villages [60].

4.1.1. Author Collaboration Analysis

Author collaboration analysis is a valuable approach for assessing the research productivity and collaboration level of key authors within a specific research domain [61]. In Figure 2, the academic collaboration network among authors is depicted, which was created by considering the analysis units, setting thresholds, and excluding isolated nodes. The size of the nodes corresponds to the number of publications, with larger nodes representing more publications, while the line thickness between nodes indicates the frequency of collaboration on papers.
In the Web of Science core database, a total of 1238 authors are involved in researching urban renewal for the preservation of cultural heritage in traditional villages, forming 2193 collaborative relationships. The network has an overall density of 0.0029. To ensure high cohesion and low coupling within the author group, the Louvain algorithm was utilized to detect and group nodes in the collaboration network, aiming to maximize modularity [62]. Figure 2 illustrates authors who have published at least one paper, showing several isolated subnetworks where authors tend to collaborate in small teams with limited communication. The largest research team, led by Muriel Figueroa Jesus and including Guzzon Filippo, consists of 18 nodes, while the second-largest subnetwork, with 15 researchers, includes Rodriguez Gonzalvez Pablo. Other subnetworks involve smaller teams with fewer publications. Overall, the connectivity density in the author collaboration network is low, with relatively isolated nodes, indicating that academic collaboration in this field is still developing, characterized by few collaborative relationships and weak efforts [63]. This suggests an “overall dispersion with limited concentration” characteristic, indicating that large-scale collaboration patterns have yet to fully emerge.
In the Web of Science core database, researchers generally participate in small group research with limited collaboration and communication among teams. The top ten most prolific authors represent three countries—China, Spain, and Italy—showcasing a diverse distribution.

4.1.2. Institutional Collaboration Analysis

Institutional collaboration network analysis effectively demonstrates collaboration patterns among research institutions, revealing the network structure and predicting collaboration trends [64]. The NetworkX function library in Python was utilized with the Louvain algorithm to detect and identify nodes, grouping them into graphs that represent collaboration clusters. Figure 3 illustrates academic collaboration relationships in urban renewal for the preservation of cultural heritage in traditional villages. The node size reflects publication volume, while the line width indicates collaboration frequency.
In the analysis of institutional collaboration networks in research on urban renewal for the preservation of cultural heritage in traditional villages, using the Web of Science core database, 451 institutions were identified, forming 404 collaborative relationships. The network’s overall density is 0.0040, with an average clustering coefficient of 0.3347 for nodes. Notably, institutions with more than three publications are emphasized. The collaboration network in this field highlights a core group of institutions, with Peking University, Tongji University, and the National Research Council of Italy (CNR) at its focal points. Peking University anchors the largest collaboration group, involving 22 institutions and contributing to 13.73% of total publications. These institutions maintain direct connections with each other, fostering a closely knit collaboration network.
The network analysis revealed that only 0.40% of the potential connections among institutional nodes are actually established, indicating a lack of collaboration both between different institutional groups and within internal subnetworks. This highlights the need for stronger collaborative efforts. Among the 451 collaborating institutions, 80.49% are universities, 5.54% are research institutions, and 13.97% are enterprises. This distribution indicates a global research emphasis on universities, with research institutes and enterprises playing supporting roles in the study of urban renewal to preserve cultural heritage in traditional villages.

4.1.3. National Collaboration Analysis

The national collaboration network diagram of articles focusing on urban renewal for the preservation of cultural heritage in traditional villages within the Web of Science core database is illustrated in Figure 4. This diagram visually represents the collaborative relationships in research on this topic across various countries. Each node in the diagram represents a country, with the size of the node reflecting the number of articles produced by that country. The thickness of the links connecting the nodes indicates the level of collaboration between countries. The network consists of 69 nodes and 92 links, with a density of 0.0392. The nodes are distributed across six continents, including notable countries such as the People’s Republic of China, the USA, Brazil, Italy, Australia, and Egypt [65]. Overall, the collaboration network demonstrates a high level of cooperation among the 69 countries involved.
Table 2 presents the top 10 countries with the highest number of articles on urban renewal for the conservation of cultural heritage in traditional villages within the Web of Science core database. The People’s Republic of China leads with 130 publications, followed by Italy (85), Spain (35), England (32), and the USA (22). A detailed analysis revealed that China surpasses other countries in articles focusing on urban renewal for cultural heritage preservation in traditional villages. This is attributed to substantial government funding and specialized laboratories at various levels—national, provincial, municipal, institutional, and corporate.
Additionally, China ranks second in betweenness centrality, highlighting its significant role in network stability. On the other hand, Turkey stands out for its high article output but low betweenness centrality, indicating a gap between its research productivity and network centrality. This suggests that Turkey is actively conducting research due to its strong research institutions, abundant resources, and sustained investment in scientific research related to urban renewal and cultural heritage preservation. However, limited scientific collaboration with other nations may be due to focused research activities, a lack of partnerships, or factors such as language, culture, and geography. Despite productivity in research output, these countries may face challenges in global scientific cooperation due to their relative isolation in the research network [66]. To enhance the international scientific collaboration network of these countries, proactive measures should be taken to promote scientific cooperation, engage in international projects and collaborative research, and strengthen the development of platforms for international exchange and cooperation [67]. These actions will help strengthen their influence in the global scientific community, leading to increased cooperation opportunities and resource sharing.
In recent years, the rapid development of urban and rural planning design, tourism development, creative industries, and community construction has sparked growing research interest in urban renewal to preserve cultural heritage in traditional villages. Italy, China, the United Kingdom, Spain, and Mexico are key players in maintaining the network of urban renewal for cultural heritage preservation. China stands out for its abundant output of research papers in this field, supported by strong government funding and laboratory resources.

4.2. Analysis of Co-Citation

Co-citation analysis is a method that utilizes reference lists from documents to assess the similarity or relevance between multiple documents [68]. This analysis can visually map out the structure of scientific fields, monitor their developmental trends, and evaluate the level of interdisciplinary collaboration across various disciplines [69]. As a result, co-citation analysis offers insights into the structure and connections within scientific research by examining journals, documents, and authors [70].

4.2.1. Journal Co-Citation Analysis

Journal co-citation analysis is a method that utilizes reference lists of documents to assess the similarity or relevance between different journals. When at least one article from two journals is cited by the same article, they are considered co-cited [71]. This analysis can provide insight into the structure and development of academic fields, where scholarly journals play a crucial role in scientific communication [72]. For this particular study, we extracted 2666 journals related to urban renewal and traditional village cultural heritage conservation from the Web of Science Core Collection database. By creating a journal co-citation network, we identified 5319 directed edges with a network density of 0.0007. The total number of citations for all journals in the network amounted to 6821, including 214 self-citations and 6607 citations from other journals.
A co-citation network graph was created using the NetworkX library in Python to analyze academic journals related to urban renewal and the conservation of traditional village cultural heritage, as shown in Figure 5. The graph visualizes journals as nodes, where the size of each node reflects the frequency of citations. Only journals cited more than 20 times are displayed, with labels showing their names. The edges represent co-citation relationships, with the thickness of the edge indicating frequency. Larger nodes and thicker edges suggest higher importance and citation frequencies [73]. The arrow indicates the direction of citation; A points to B, meaning that journal A cites journal B. “Sustainability-Basel” emerges as the most cited journal, with a total of 133 citations, including 56 self-citations and 77 from other journals. This journal is co-cited by 1008 journals, most frequently with “Cities” (25 times), and it cites 32 different journals, with “Land-Basel” being the most cited (14 times). This study conducted cluster analysis on academic journals, identifying 15 clusters with a silhouette coefficient of 0.8231 [74]. This was achieved by creating feature value vectors of journal keywords using the LLR algorithm, calculating similarity with cosine correlation coefficients, and applying the K-means method for clustering. The graph displays journals from two distinct categories. For example, “Sustainability-Basel” is categorized under #14, focusing on sustainable urban development, cultural heritage management, and related topics. Conversely, “Landscape Res” is classified as number 3, emphasizing urban renewal, sustainable development, and heritage conservation.
Journal co-citation analysis is a method used to assess the internal structure and dissemination of knowledge within academic fields [75]. This study concentrated on urban renewal and the preservation of traditional village cultural heritage, utilizing this method to analyze pertinent literature. The findings suggest that this subject encompasses the interdisciplinary intersection of architecture and history, showcasing significant academic impact and research engagement. By scrutinizing the cited journals, the research uncovered the principal professional publications in this area, along with their citation distribution patterns and biases, offering scholars valuable insights into the academic framework and communication dynamics of this domain. This promotes collaborative ventures and advancements between architecture and history.

4.2.2. Literature Co-Citation Analysis

Literature plays a vital role in disseminating knowledge. This study focused on analyzing a selection of research works to create a co-citation network with the goal of investigating the academic structure and trends in a specific field [76]. By utilizing the NetworkX library in Python, a network graph was generated, with nodes representing cited literature. The top 50 nodes, ranked by citation frequency, were annotated with the first author and publication year. The edges in Figure 6 illustrate the co-citation relationships among the literature nodes, with node size and edge thickness indicating the frequency of citations and co-citations [77]. The arrow indicates the direction of citation. A pointing to B means that the article published by author A cites the article by author B.
A thematic clustering analysis was conducted on the literature related to the protection of traditional village cultural heritage in urban renewal. The study identified 8828 articles in the Web of Science (WoS) core database and their references, which were categorized into 15 clusters with a silhouette coefficient of 0.9627. Figure 6 illustrates the different clusters of literature, with a total of seven distinct research themes identified. The clustering of literature themes was ranked based on the citation frequency of the most cited articles in each cluster [78]. The top two clusters are as follows: Cluster #7, with characteristic keywords such as sustainable development, urban renewal, urban regeneration, and cultural heritage. Representative literature includes the article “Built Cultural Heritage and Sustainable Urban Development” by Tweed C (2007) in the journal “Landscape” and “Measuring Links between Cultural Heritage Management and Sustainable Urban Development: An Overview of Global Monitoring Tools” by Guzman PC (2017) in the journal “Cities”. Cluster #11 features characteristic keywords such as cultural heritage, sustainable development, industrial heritage, sustainability, China, adaptive reuse, urban heritage, urban regeneration, and literature review. Representative literature includes the article “Measure for Measure: Evaluating the Evidence of Culture’s Contribution to Regeneration” by Evans G. (2005) in “Urban Studies”, as well as two articles by Landorf C. (2009): “A Framework for Sustainable Heritage Management: A Study of UK Industrial Heritage Sites” and “Managing for Sustainable Tourism: A Review of Six Cultural World Heritage Sites”.
The analysis suggests that the preservation of traditional village cultural heritage in urban renewal is an evolving concept. Co-citation analysis assists experts and scholars in identifying highly cited and influential research articles while also offering insights into the fundamental knowledge of research areas such as sustainable development, urban renewal, urban regeneration, and cultural heritage [79].

4.2.3. Author Co-Citation Analysis

Author co-citation analysis not only reveals the distribution of highly cited authors within a specific field, identifying influential authors, but also provides insights into research themes and the disciplinary distribution of peer authors through co-citation networks [80]. In this study, a directed network graph of co-cited authors in the field of urban renewal for the protection of traditional village cultural heritage was created using the NetworkX database in Python. A total of 7322 authors from selected literature and their references were included, establishing 9190 co-citation relationships among authors, resulting in 9285 citations. The overall network density was calculated to be 0.0002.
Cluster analysis was conducted on authors who published articles related to urban renewal for the protection of traditional village cultural heritage in the Web of Science (WoS) core database. Setting the total number of clusters to 15 resulted in a silhouette coefficient of 0.9406, indicating a reasonable partitioning of the literature. The analysis focused on the top 100 nodes and visualized a directed graph of co-cited authors, as shown in Figure 7. Each node in the figure represents an author, with the node size reflecting the number of citations received [81]. The edges show co-citation relationships among authors, with colors representing clusters where nodes of the same color belong to the same cluster [82]. The arrow indicates the direction of citation. A pointing to B means that the article published by author A cites the article by author B.
The study identified three clusters labeled as #5, #10, and #14. By ranking these clusters based on the citation count of the most cited author in each, the research focused on analyzing the top two clusters [83]. Cluster #10 was ranked first, with the most cited author being Yung E.H.K., whose research interests encompass cultural heritage, urban regeneration, industrial heritage, sustainable development, remote sensing, conservation, and heritage conservation. Yung E.H.K. primarily focuses on urban renewal to preserve traditional village cultural heritage. Cluster #14 was ranked second, with the most cited author being Bullen P.A. His research interests include cultural heritage, China, literature review, urban regeneration, sustainability, industrial heritage, sustainable development, conservation, and heritage conservation. Bullen P.A. also focuses on urban renewal to preserve traditional village cultural heritage. In terms of citation count, Yung E.H.K.’s papers ranked first with 27 co-citations by journals like “Buildings-Basel” from 2014 to 2023, averaging 2.7 citations annually. Citing authors belonged to clusters #0, #1, #2, #3, #4, #5, #8, #9, #10, #11, #13, and #14, with cluster #14 authors citing the most. Retti V.’s papers ranked second with 18 co-citations by journals such as “Energies” from 2016 to 2023, averaging 2.2 citations annually. Citing authors were from clusters #0, #1, #4, #5, #7, #10, #11, and #14, with authors from cluster #14 citing the most. Ed C.’s papers ranked third with 16 co-citations by journals such as “Energies” from 2014 to 2023, averaging 1.6 citations annually. Citing authors were from clusters #1, #4, #6, #10, #12, and #14, with authors from cluster #10 citing the most. These findings greatly contribute to urban renewal by preserving traditional village cultural heritage.
Author co-citation analysis is a valuable method for assessing the academic impact of authors, identifying experts, pinpointing research focal points, evaluating research quality, and filtering literature. Through examining citation data, one can understand authors’ standing and recognition in the academic sphere, recognize leading figures in the urban renewal field concerning traditional village cultural heritage preservation, reveal cutting-edge research areas and directions, assess the academic importance of research results, and aid in literature selection and information retrieval. This method has profound implications for academic research and fostering collaboration [84].

4.3. Keyword Analysis

4.3.1. Keyword Co-Occurrence Analysis

Keywords play a crucial role in academic literature, encapsulating the essence of the documents. Analyzing keyword co-occurrence networks can reveal research trends, with frequently appearing keywords indicating the forefront of research [85]. This study utilized Python’s Networkx function to conduct keyword co-occurrence analysis on literature related to the preservation of traditional village cultural heritage in urban renewal. The resulting keyword co-occurrence network, as illustrated in Figure 8, involved 1455 keywords and 4768 connections, with a filtering threshold of 2. Each node in the network represents a keyword, and the size of the node reflects its frequency of occurrence. Larger nodes signify higher frequencies. The betweenness centrality of a node measures its importance as a mediator within the network. Nodes with more connections exhibit stronger centrality. In Figure 8, the node representing “cultural heritage” stands out as the largest, with a betweenness centrality of 0.28, highlighting its substantial co-occurrence weight and crucial role in the network. “Conservation” (betweenness centrality of 0.09) and “sustainable development” (betweenness centrality of 0.06) follow in importance, spanning the research timeline and connecting to various research directions.
As shown in Table 3, this study sorted keywords based on their co-occurrence weight and applied Zipf’s law to determine research hotspots. The critical value for identifying hotspot keyword frequency was calculated using the formula M = 0.749 N m a x 1 / 2 , where M represents the lower bound for hotspot frequency and Nmax is the highest occurrence frequency. With Nmax set at 54, M was calculated as 5.50, indicating that keywords with frequencies above 5.50 are considered research hotspots [86]. Therefore, the identified research hotspots in urban renewal and traditional village cultural heritage include cultural heritage conservation, sustainable development, sustainability, urban regeneration, heritage preservation, adaptive reuse, heritage conservation, industrial heritage, and urban renewal.

4.3.2. Keyword Emergence Analysis

Keyword burst analysis is a text mining technique that identifies keywords with significantly increased frequency in a text, reflecting the dynamic changes, trend evolution, and frontier hotspots in a research field [87]. In this study, the Kleinberg algorithm, based on the hidden Markov model, was utilized to conduct keyword burst analysis. This algorithm considers the ranking changes of keywords in different time periods as a state transition process, enabling the identification of burst keywords, their burst time range, and intensity. The Kleinberg algorithm relies on three key parameters: the minimum duration of bursts (t), the multiplicative distance between states (s), and the difficulty of state transitions (γ). These parameters play a crucial role in influencing the results and sensitivity of keyword burst analysis [88].
Based on the Kleinberg algorithm, Figure 9 illustrates the results of keyword burst analysis in the research field of urban renewal and preservation of traditional village cultural heritage from 1999 to 2023. The parameters used are as follows: a minimum burst duration of 2 years (t), indicating the selection of keywords with bursts lasting more than 2 years; a multiplicative distance between states of 1.2 (s), indicating significant changes in keyword rankings across different time periods; and a state transition difficulty of 0.28 (γ), suggesting relatively easy transitions of keywords to higher states. Blue indicates the occurrence of the keyword from the beginning to the end. Red indicates that the keyword is at its peak research period and has high research interest. In Figure 9, the red area represents the duration of keyword bursts lasting more than 2 years, indicating keywords with significantly increased frequencies for at least two consecutive years. The blue area represents the time span during which keywords appear in the dataset. The data on the right side of the figure indicate burst strength, with higher values reflecting greater research intensity on the respective keywords. The keyword burst analysis histogram reveals that research on urban renewal and the preservation of traditional village cultural heritage can be categorized into three stages.
The initial phase of research on urban renewal and the preservation of traditional village cultural heritage, spanning from 1999 to 2016, served as a foundation for subsequent studies. During this period, “cultural heritage” emerged as a key focus, with scholars like Ipekoglu B1 highlighting its importance in understanding and promoting urban renewal and preservation efforts [17]. Research in this area aims to recognize the value of cultural heritage, explore conservation methods, address challenges, and offer guidance for sustainable development [40]. The MCLAREN AE2 further underscores the role of conservation in enhancing cultural diversity, social cohesion, and creativity within urban environments, ultimately driving cultural innovation and economic growth [89].
During the second stage of research between 2016 and 2020, there was a shift in focus towards urban renewal and the preservation of traditional village cultural heritage. Key areas of study included sustainability, GIS technology, urban regeneration, historic center preservation, values, frameworks, stakeholders, and heritage conservation. This period marked a shift from individual research on urban renewal and traditional village preservation to more comprehensive studies that integrated various perspectives, methodologies, and applications [90]. Traditional villages, as significant bearers of historical culture, are recognized as important resources in the field of architecture [91]. The challenge of preserving traditional village cultural heritage during urban renewal while balancing historical authenticity with modern functional needs, became a major focal point. The intersection of architecture and history offers diverse analytical perspectives, providing scientific theories and methodological support for urban renewal through the exploration of aspects such as the formation, development, evolution, and value of traditional villages [92]. Consequently, research on urban renewal and traditional village cultural heritage within the context of architecture and history garnered considerable attention. Scholars in this field approached research from various perspectives, such as sustainability, GIS technology, urban regeneration, historic core preservation, value research, framework studies, stakeholder engagement, and heritage conservation [93]. These studies not only addressed the sustainability of urban materials and environmental aspects but also highlighted the cultural and social sustainability of traditional villages [94]. The research emphasized the significant cultural value of traditional villages, proposing sustainability charters and objectives to guide urban renewal [95]. GIS technology plays a key role in planning and conserving traditional village cultural heritage by analyzing and visualizing geographic information [96]. Research encompassed heritage regeneration, sustainable urban renewal, and culture-led renewal, offering both theoretical and practical insights for urban sustainable development [78]. Special attention was given to historic core areas to promote sustainable development and cultural inheritance through protection, enhancement, and regeneration strategies [97]. Decision-makers were aided by the development of multi-criteria assessment frameworks and performance-based frameworks to understand various schemes and formulate strategies in alignment with sustainable development goals [98]. Research on stakeholder interactions facilitated cooperation and communication among diverse parties, fostering consensus for coordinated and sustainable urban renewal and cultural heritage protection [99]. In conclusion, the research and practices in urban renewal and preservation of traditional village cultural heritage strongly supported urban sustainable development and the inheritance and protection of cultural heritage [100].
During the third stage, from 2020 to 2023, there was a significant advancement in research on urban renewal and the preservation of traditional village cultural heritage. Keywords such as historic urban landscape, energy efficiency, historic buildings, adaptive reuse, survey, photogrammetry, conservation planning, sustainable development, circular economy, revitalization, resilience, rural revitalization, influencing factors, and earthquakes emerged as prominent research areas during this period [101]. Particularly at the intersection of architecture and history, there was a growing focus on urban renewal and the preservation of traditional cultural heritage. This field emphasized landscape assessment, risk analysis, and the application of landscape metrics and archaeological methods to preserve the cultural value of historical cities and enhance overall experiences [102]. Additionally, energy efficiency research became essential, involving sustainable energy planning and energy-saving strategies to optimize energy use in traditional buildings while safeguarding cultural heritage [103]. The utilization of non-destructive testing and measurement technologies, digital photogrammetry techniques, and the advancement of urban planning and community resilience strategies all contributed to the advancement of urban renewal and cultural heritage preservation [104]. Ultimately, by analyzing driving and attracting forces, as well as studying the impacts of natural disasters such as earthquakes, we can establish a scientific foundation for urban renewal and cultural heritage preservation, thereby achieving sustainable development.

5. Discussion

This article presents a comprehensive bibliometric analysis of literature concerning the safeguarding of cultural heritage in traditional villages during urban renewal. It involved searching and collecting literature from 1999 to 2023 related to this topic from the Web of Science (WoS) Core Collection database and processing the data using Python programming and network analysis tools. By examining collaboration relationships, co-citation analysis, keyword co-occurrence, and emergent trends, this study delved deeply into the developmental trajectory, research hotspots, and evolving trends in the field of cultural heritage protection in traditional villages amidst urban renewal. Some key findings of the study are as follows:
(1)
The analysis of collaboration relationships reveals that researchers tend to work in small groups with limited cooperation and communication between different teams. The authors with the highest number of published articles are from various countries, including China, Spain, and Italy. In the study of protecting traditional village cultural heritage during urban renewal, there is no significant clustering of cooperation among research institutions. Research is mainly concentrated in universities and research institutions. The top three institutions in terms of the number of published articles are Tongji University (eight articles), the University of Hong Kong (eight articles), and Hong Kong Polytechnic University (seven articles). Countries such as Italy, China, the UK, Spain, and Mexico play critical roles in international cooperation to preserve traditional village cultural heritage during urban renewal projects.
(2)
Research on preserving traditional village cultural heritage during urban renewal spans various disciplines. Noteworthy researchers such as Wang Fang, Chan Edwin H.W., Trivino Tarradas Paula, Jim C.Y., and Cantatore Elena have made significant contributions to this field. Key journals such as “Sustainability-Basel”, the “Journal of “Cultural Heritage”, “Cities”, “Habitat International”, and “Land Use Policy” regularly publish a significant number of influential papers on this topic.
(3)
The field of cultural heritage protection in traditional villages during urban renewal involves several major research hotspots, such as “urban renewal”, “cultural heritage”, “sustainability”, “historic urban landscape”, and “rural revitalization”. These topics are closely related and mutually influential, reflecting the knowledge structure and thematic evolution of the field. The development of this area can be divided into three main stages: the initial stage (1999–2016), the stable development stage (2016–2020), and the mature development stage (2020–2023). Each stage emphasizes specific keywords that indicate the research focus and dynamics of that period.
During the initial stage, “cultural heritage” was one of the trending keywords, indicating the early development of awareness and the significance of the cultural value of traditional villages. Research mainly focused on identifying and documenting culturally significant heritage and exploring its role and significance in modern urban development. This period emphasized the cultural identity and historical continuity of traditional villages, exploring ways to protect these cultural heritages from being marginalized or lost under the pressures of urban expansion and modernization.
In the stable development stage, “sustainability” became one of the prominent keywords, signifying that research started to explore sustainable protection and development strategies for traditional villages. The focus was on how to achieve a harmonious coexistence between the preservation of cultural heritage and local economic and social development. This involved emphasizing the use of environmentally friendly materials and technologies in cultural heritage restoration as well as exploring ways to sustain the vitality of cultural heritage through increased community participation and stakeholder cooperation. Additionally, it aimed to promote economic development, for example, through cultural tourism.
In the mature development stage, “historic urban landscape” and “rural revitalization” were prominent keywords. The concept of “historic urban landscape” emphasizes the significance of incorporating cultural heritage protection into urban planning. It underscores the importance of urban renewal projects that respect historical contexts and cultural characteristics. Meanwhile, research on “rural revitalization” indicates that stimulating the cultural and economic vitality of rural areas can achieve a blend of tradition and modernity, enhancing the quality of life and sense of social identity in rural areas. This includes improving infrastructure, promoting local characteristic industries and cultural activities, and enhancing the participation and sense of belonging in rural communities.

6. Conclusions

6.1. Cooperation and Impact Analysis

This study employed bibliometric methods to comprehensively analyze the literature concerning the preservation of traditional village cultural heritage in urban renewal. It explored collaboration relationships, co-citation relationships, and keyword co-occurrence analysis, offering valuable scientific insights for academic research, policy formulation, and future development directions in this field. Interdisciplinary collaboration highlights the synergy among experts from different fields, effectively addressing the complexity and diversity of the research area [105]. International cooperation emphasizes consensus and the need for global collaboration, highlighting common goals and cooperative intentions among different countries [106]. Italy, China, and the United Kingdom play leading roles in this research area. The significance of institutional collaboration lies in the integration of resources and the complementarity of strengths [107]. Universities like Politecnico di Milano and Tongji University have made significant contributions, playing a crucial role in promoting the output and application transformation of research results. Individual collaboration enhances the exchange of knowledge and promotes innovative thinking within the academic community [108]. Co-citation analysis reveals the interdisciplinary integration among environmental science, social science, and architecture. Keyword co-occurrence analysis identifies “sustainable development”, “cultural heritage”, “historic urban landscapes”, and “rural revitalization” as research hotspots. This provides clear evidence for formulating related policies and guiding future research directions, especially in strategies for cultural heritage protection and regional economic development. These outcomes not only reflect current academic research trends but also provide direction for future research [109].

6.2. Future Research Prospects

As research on urban renewal and the protection of traditional village cultural heritage deepens, future studies should focus more on several emerging key terms with great potential, especially “sustainable development”, “cultural heritage”, “rural revitalization”, and “historic urban landscapes”.
Firstly, the core of the research will be to explore how integrated planning and protection strategies can promote the sustainable development of historic urban landscapes and contribute to the economic and cultural revival of rural areas. This involves utilizing advanced GIS technology and remote sensing data to evaluate and design historic urban areas, guaranteeing that new urban developments coexist harmoniously with the historical culture [110]. In this way, we can ensure that urban renewal not only meets modern needs but also protects the unique cultural heritage of rural areas.
Secondly, future research will also focus on community-driven development models. This involves revitalizing rural areas by promoting tourism and local handicraft industries focused on cultural heritage, thereby encouraging sustainable economic growth at the local level. For example, revitalizing the local economy can be achieved through the exploration of traditional knowledge and skills, as well as through the development of small enterprises and craft markets that are based on cultural heritage [111]. This approach not only protects the environment but also enhances community identity and social cohesion. This community participation model helps ensure the feasibility and sustainability of policy-making and implementation processes [112].
In the context of a rapidly developing society and the era of AI, the integration of modern technology and traditional conservation methods becomes particularly important. For example, utilizing digital technologies for 3D reconstruction and augmented reality displays of cultural heritage can significantly enhance public awareness of the value of cultural heritage [113]. These research directions not only deepen our understanding of past studies but also provide innovative strategies and theoretical support for the preservation of traditional village cultural heritage in urban renewal.

6.3. Limitations of the Study

While our study utilized the core dataset from the Web of Science database, it is important to acknowledge several limitations. We focused solely on one database and did not consider others such as Google Scholar, ProQuest, SpringerLink, and CNKI, which may have introduced certain limitations. Despite our efforts to explore discourses on the preservation of traditional village cultural heritage in urban renewal across different periods, there is a possibility that we may have overlooked relevant literature. Additionally, our research only examined highly cited literature and did not delve into subsequent studies by the authors. It is crucial to note that databases are regularly updated, which can potentially impact the results of bibliometric analysis over time. Therefore, further research is needed to address these limitations. Moving forward, we aim to expand our selection of databases to gain a more comprehensive understanding of the global development of preserving traditional village cultural heritage in urban renewal. This will enable us to monitor the latest research trends in various disciplinary fields.
Overall, this study conducted an in-depth analysis of the literature on traditional village cultural heritage protection in urban renewal using bibliometric methods. The results reveal the developmental history, key research hotspots, and collaboration models in this field. The research identifies interdisciplinary and international collaborations as key drivers for advancing scientific research and practical applications in this area. It also highlights emerging key terms and research directions that need further exploration in future studies. This study offers valuable scientific insights and theoretical support for safeguarding traditional village cultural heritage during urban renewal, laying the groundwork for future research and policy development.

Author Contributions

Conceptualization, Y.S.; methodology, J.X. and Y.S.; software, X.G. and T.F.; validation, J.X. and Y.R.; investigation, X.G. and T.F.; data curation, J.X.; writing—original draft, J.X.; writing—review and editing, J.X.; visualization, X.G., Y.R. and T.F.; supervision, Y.S.; Resources, Y.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Cruz, C.O.; de Brito, J. Role of public administration in fostering urban housing rehabilitation. J. Urban Plan. Dev. 2015, 141, 06014002. [Google Scholar] [CrossRef]
  2. Zheng, W.; Shen, G.Q.; Wang, H.; Hong, J.; Li, Z.J. Decision support for sustainable urban renewal: A multi-scale model. Land Use Policy 2017, 69, 361–371. [Google Scholar] [CrossRef]
  3. Grodach, C.; Loukaitou-Sideris, A.J. Cultural development strategies and urban revitalization: A survey of US cities. Int. J. Cult. Policy 2007, 13, 349–370. [Google Scholar] [CrossRef]
  4. Turok, I.; Parnell, S. Reshaping cities, rebuilding nations: The role of national urban policies. In Proceedings of Urban Forum; Springer: Berlin/Heidelberg, Germany, 2009; pp. 157–174. [Google Scholar]
  5. Angelidou, M.; Psaltoglou, A.; Komninos, N.; Kakderi, C.; Tsarchopoulos, P.; Panori, A. Enhancing sustainable urban development through smart city applications. J. Sci. Technol. Policy Manag. 2018, 9, 146–169. [Google Scholar] [CrossRef]
  6. Križnik, B.J. Transformation of deprived urban areas and social sustainability: A comparative study of urban regeneration and urban redevelopment in Barcelona and Seoul. Urbani Izziv 2018, 29, 83–95. [Google Scholar] [CrossRef]
  7. Huston, S.; Rahimzad, R.; Parsa, A.J. ‘Smart’sustainable urban regeneration: Institutions, quality and financial innovation. Cities 2015, 48, 66–75. [Google Scholar] [CrossRef]
  8. Sepe, M. Urban transformation, socio-economic regeneration and participation: Two cases of creative urban regeneration. Int. J. Urban Sustain. Dev. 2014, 6, 20–41. [Google Scholar] [CrossRef]
  9. Bianchini, F.; Parkinson, M. Cultural Policy and Urban Regeneration: The West European Experience; Manchester University Press: Manchester, UK, 1993. [Google Scholar]
  10. Mayer, M. The onward sweep of social capital: Causes and consequences for understanding cities, communities and urban movements. Int. J. Urban Reg. Res. 2003, 27, 110–132. [Google Scholar] [CrossRef]
  11. Atkinson, R.J. Discourses of partnership and empowerment in contemporary British urban regeneration. Urban Stud. 1999, 36, 59–72. [Google Scholar] [CrossRef]
  12. McDonald, S.; Malys, N.; Maliene, V. Urban regeneration for sustainable communities: A case study. Technol. Econ. Dev. Econ. 2009, 15, 49–59. [Google Scholar] [CrossRef]
  13. Rae, A. Whose Urban Renaissance? An International Comparison of Urban Regeneration Strategies; Taylor & Francis: London, UK, 2009. [Google Scholar]
  14. Korkmaz, C.; Balaban, O. Sustainability of urban regeneration in Turkey: Assessing the performance of the North Ankara Urban Regeneration Project. Habitat Int. 2020, 95, 102081. [Google Scholar] [CrossRef]
  15. Clement, F.D.; Shutian, Z.; Mehdipour, A. Inheriting and Restoring Historic Structures in Urban Renewal: A Study of ”Jiangcuo and Lucuo” in Xiamen, China. Res. Sq. 2024, 3. Available online: https://www.researchsquare.com/article/rs-3999445/v1 (accessed on 20 March 2024).
  16. Suzuki, H.; Cervero, R.; Iuchi, K. Transforming Cities with Transit: Transit and Land-Use Integration for Sustainable Urban Development; World Bank Publications: Washington, DC, USA, 2013. [Google Scholar]
  17. Tweed, C.; Sutherland, M. Built cultural heritage and sustainable urban development. Landsc. Urban Plan. 2007, 83, 62–69. [Google Scholar] [CrossRef]
  18. Xie, K.; Zhang, Y.; Han, W. Architectural Heritage Preservation for Rural Revitalization: Typical Case of Traditional Village Retrofitting in China. Sustainability 2024, 16, 681. [Google Scholar] [CrossRef]
  19. Li, B.; Yang, F.; Long, X.; Liu, X.; Cheng, B.; Dou, Y. The organic renewal of traditional villages from the perspective of logical space restoration and physical space adaptation: A case study of Laoche village, China. Habitat Int. 2024, 144, 102988. [Google Scholar] [CrossRef]
  20. Zhou, M.; Chu, S.; Du, X. Safeguarding traditional villages in China: The role and challenges of Rural Heritage preservation. Built Herit. 2019, 3, 81–93. [Google Scholar] [CrossRef]
  21. Tengberg, A.; Fredholm, S.; Eliasson, I.; Knez, I.; Saltzman, K.; Wetterberg, O. Cultural ecosystem services provided by landscapes: Assessment of heritage values and identity. Ecosyst. Serv. 2012, 2, 14–26. [Google Scholar] [CrossRef]
  22. Öter, Z. Touristification of cultural heritage, identities tested by marketing of handcrafts to tourists in Turkey: The case of Görece: Supervisor: Christian Bataillou, Ph. D. Institution awarding the Ph. D. Degree: University of Perpignan Via Domitia, Transborder Franco Catalan Institute, Center of Catalan Research and Education, Perpignan, France Date of defence: 10 th July 2009. Eur. J. Tour. Res. 2010, 3, 77–79. [Google Scholar]
  23. Meskell, L. UNESCO’s World Heritage Convention at 40: Challenging the economic and political order of international heritage conservation. Curr. Anthropol. 2013, 54, 483–494. [Google Scholar] [CrossRef]
  24. Liu, S.-J. Enlightenment to Our Country Based on Europe and the United States National Non-Material Cultural Heritage Legal Protection Experience. In Proceedings of the 2015 International Conference on Management Science and Management Innovation (MSMI 2015), Guilin, China, 15–16 August 2015; pp. 15–20. [Google Scholar]
  25. Mat Radzuan, I.S.; Fukami, N.; Ahmad, Y. Incentives for the conservation of traditional settlements: Residents’ perception in Ainokura and Kawagoe, Japan. J. Tour. Cult. Change 2015, 13, 301–329. [Google Scholar] [CrossRef]
  26. Giannakopoulou, S.; Kaliampakos, D. Protection of architectural heritage: Attitudes of local residents and visitors in Sirako, Greece. J. Mt. Sci. 2016, 13, 424–439. [Google Scholar] [CrossRef]
  27. Rees, H. Environmental crisis, culture loss, and a new musical aesthetic: China’s “original ecology folksongs” in theory and practice. Ethnomusicology 2016, 60, 53–88. [Google Scholar] [CrossRef]
  28. Yunxia, W.; Prott, L.V. Cultural revitalisation after catastrophe: The Qiang culture in A’er. Int. J. Herit. Stud. 2016, 22, 26–42. [Google Scholar] [CrossRef]
  29. Li, T.; Zhang, M.; Gu, X. The Research on the Evaluation and Optimization of the Traditional Dwelling Conservation Practice: A Case Study of Cheng Zhi Hall Restoration Project within Hongcun. J. Archit. Res. Dev. 2020, 4, 4. [Google Scholar] [CrossRef]
  30. Bourne, L.S. Reurbanization, uneven urban development, and the debate on new urban forms. Urban Geogr. 1996, 17, 690–713. [Google Scholar] [CrossRef]
  31. Guo, P.; Li, Q.; Guo, H.; Li, H. Quantifying the core driving force for the sustainable redevelopment of industrial heritage: Implications for urban renewal. Environ. Sci. Pollut. Res. 2021, 28, 48097–48111. [Google Scholar] [CrossRef]
  32. Zeng, Z.; Li, L.; Pang, Y. Analysis on climate adaptability of traditional villages in Lingnan, China—World Cultural Heritage Site of Majianglong Villages as example. Procedia Eng. 2017, 205, 2011–2018. [Google Scholar] [CrossRef]
  33. Stara, K.; Tsiakiris, R.; Wong, J.L. Valuing trees in a changing cultural landscape: A case study from northwestern Greece. Hum. Ecol. 2015, 43, 153–167. [Google Scholar] [CrossRef]
  34. Bleibleh, S.; Awad, J. Preserving cultural heritage: Shifting paradigms in the face of war, occupation, and identity. J. Cult. Herit. 2020, 44, 196–203. [Google Scholar] [CrossRef]
  35. Lloyd, R.; Clark, T.N. The city as an entertainment machine. Crit. Perspect. Urban Redev. 2001, 6, 357–378. [Google Scholar]
  36. de Freitas, I.V.; Koskowski, M.R. Heritage and sustainable development: Capacity building through tourism. In Capacity Building through Heritage Tourism; Apple Academic Press: Waretown, NJ, USA, 2021; pp. 113–131. [Google Scholar]
  37. Wang, Z.; Zhuang, Q.; Ma, Y.; Li, P. A Study on the Path of Narrative Renewal of Traditional Villages: A Case of Shawan Ancient Town, Guangdong, China. Int. J. Environ. Res. Public Health 2022, 20, 372. [Google Scholar] [CrossRef] [PubMed]
  38. Chirikure, S.; Pwiti, G. Community involvement in archaeology and cultural heritage management: An assessment from case studies in Southern Africa and elsewhere. Curr. Anthropol. 2008, 49, 467–485. [Google Scholar] [CrossRef]
  39. Zhai, B.; Ng, M.K. Urban regeneration and social capital in China: A case study of the Drum Tower Muslim District in Xi’an. Cities 2013, 35, 14–25. [Google Scholar] [CrossRef]
  40. McKercher, B.; Du Cros, H. Cultural Tourism: The Partnership between Tourism and Cultural Heritage Management; Routledge: New York, NY, USA, 2002. [Google Scholar]
  41. Couch, C.; Sykes, O.; Börstinghaus, W. Thirty years of urban regeneration in Britain, Germany and France: The importance of context and path dependency. Prog. Plan. 2011, 75, 1–52. [Google Scholar] [CrossRef]
  42. Li, Y.; Hunter, C. Community involvement for sustainable heritage tourism: A conceptual model. J. Cult. Herit. Manag. Sustain. Dev. 2015, 5, 248–262. [Google Scholar] [CrossRef]
  43. Olujobi, O.J.; Okorie, U.E.; Olarinde, E.S.; Aina-Pelemo, A.D. Legal responses to energy security and sustainability in Nigeria’s power sector amidst fossil fuel disruptions and low carbon energy transition. Heliyon 2023, 9, e17912. [Google Scholar] [CrossRef] [PubMed]
  44. Nocca, F. The role of cultural heritage in sustainable development: Multidimensional indicators as decision-making tool. Sustainability 2017, 9, 1882. [Google Scholar] [CrossRef]
  45. Zhang, B.; Xiong, Y.; Liu, H.; Lyu, S.; Skitmore, M. A Comprehensive Bibliometric Analysis of Urban Renewal Research during 2012–2022. Buildings 2023, 13, 2826. [Google Scholar] [CrossRef]
  46. Huo, D.; Malik, A.W.; Ravana, S.D.; Rahman, A.U.; Ahmedy, I. Mapping smart farming: Addressing agricultural challenges in data-driven era. Renew. Sustain. Energy Rev. 2024, 189, 113858. [Google Scholar] [CrossRef]
  47. Madnick, S.; Woon, W.L.; Henschel, A.; Firat, A.; Ziegler, B.; Camina, S.; Seshasai, S.; Vidican, G.; Zeineldin, H.; Mezher, T. Technology Forecasting Using Data Mining and Semantics; Massachusetts Institute of Technology: Cambridge, MA, USA, 2008. [Google Scholar]
  48. Barcellos, R.; Viterbo, J.; Miranda, L.; Bernardini, F.; Maciel, C.; Trevisan, D. Transparency in practice: Using visualization to enhance the interpretability of open data. In Proceedings of the 18th Annual International Conference on Digital Government Research, Staten Island, NY, USA, 7–9 June 2017; pp. 139–148. [Google Scholar]
  49. Pranckutė, R. Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications 2021, 9, 12. [Google Scholar] [CrossRef]
  50. Moral-Muñoz, J.A.; Herrera-Viedma, E.; Santisteban-Espejo, A.; Cobo, M.J. Software tools for conducting bibliometric analysis in science: An up-to-date review. Prof. Inf. 2020, 29, e290103. [Google Scholar] [CrossRef]
  51. Verbeek, A.; Debackere, K.; Luwel, M.; Zimmermann, E. Measuring progress and evolution in science and technology–I: The multiple uses of bibliometric indicators. Int. J. Manag. Rev. 2002, 4, 179–211. [Google Scholar] [CrossRef]
  52. Saeidnia, H.R.; Hosseini, E.; Abdoli, S.; Ausloos, M. Unleashing the power of AI: A systematic review of cutting-edge techniques in AI-enhanced scientometrics, webometrics and bibliometrics. Libr. Hi Tech 2024. [Google Scholar] [CrossRef]
  53. Kostoff, R.N.; Toothman, D.R.; Eberhart, H.J.; Humenik, J. Text mining using database tomography and bibliometrics: A review. Technol. Forecast. Soc. Chang. 2001, 68, 223–253. [Google Scholar] [CrossRef]
  54. Forliano, C.; De Bernardi, P.; Yahiaoui, D. Entrepreneurial universities: A bibliometric analysis within the business and management domains. Technol. Forecast. Soc. Chang. 2021, 165, 120522. [Google Scholar] [CrossRef]
  55. Ho, L.; Goethals, P. Machine learning applications in river research: Trends, opportunities and challenges. Methods Ecol. Evol. 2022, 13, 2603–2621. [Google Scholar] [CrossRef]
  56. Subramanyam, K. Bibliometric studies of research collaboration: A review. J. Inf. Sci. 1983, 6, 33–38. [Google Scholar] [CrossRef]
  57. Si, L.; Zeng, Y.; Guo, S.; Zhuang, X. Investigation and analysis of research support services in academic libraries. Electron. Libr. 2019, 37, 281–301. [Google Scholar] [CrossRef]
  58. Mariani, M.; Borghi, M. Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries. Technol. Forecast. Soc. Chang. 2019, 149, 119752. [Google Scholar] [CrossRef]
  59. Kumar, S. Ethical concerns in the rise of co-authorship and its role as a proxy of research collaborations. Publications 2018, 6, 37. [Google Scholar] [CrossRef]
  60. Wang, Q.; Luo, S.; Zhang, J.; Furuya, K. Increased attention to smart development in rural areas: A scientometric analysis of smart village research. Land 2022, 11, 1362. [Google Scholar] [CrossRef]
  61. Gu, D.; Li, T.; Wang, X.; Yang, X.; Yu, Z. Visualizing the intellectual structure and evolution of electronic health and telemedicine research. Int. J. Med. Inform. 2019, 130, 103947. [Google Scholar] [CrossRef] [PubMed]
  62. Aung, T.T.; Nyunt, T.T.S. Community detection in scientific co-authorship networks using neo4j. In Proceedings of the 2020 IEEE Conference on Computer Applications (ICCA), Yangon, Myanmar, 27–28 February 2020; pp. 1–6. [Google Scholar]
  63. Bindu, N.; Sankar, C.P.; Kumar, K.S. Research collaboration and knowledge sharing in e-governance: Temporal analysis of co-author network. Transform. Gov. People Process Policy 2019, 13, 2–33. [Google Scholar] [CrossRef]
  64. Gazni, A.; Sugimoto, C.R.; Didegah, F. Mapping world scientific collaboration: Authors, institutions, and countries. J. Am. Soc. Inf. Sci. Technol. 2012, 63, 323–335. [Google Scholar] [CrossRef]
  65. Abbasi, A.; Hossain, L.; Uddin, S.; Rasmussen, K.J. Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis. Scientometrics 2011, 89, 687–710. [Google Scholar] [CrossRef]
  66. Sonnenwald, D.H. Scientific collaboration. Annu. Rev. Inf. Sci. Technol. 2007, 41, 643–681. [Google Scholar] [CrossRef]
  67. Jacob, M.; Meek, V.L. Scientific mobility and international research networks: Trends and policy tools for promoting research excellence and capacity building. Stud. High. Educ. 2013, 38, 331–344. [Google Scholar] [CrossRef]
  68. Jeong, Y.K.; Song, M.; Ding, Y. Content-based author co-citation analysis. J. Informetr. 2014, 8, 197–211. [Google Scholar] [CrossRef]
  69. Wang, F.; Tan, B.; Chen, Y.; Fang, X.; Jia, G.; Wang, H.; Cheng, G.; Shao, Z. A visual knowledge map analysis of mine fire research based on CiteSpace. Environ. Sci. Pollut. Res. 2022, 29, 77609–77624. [Google Scholar] [CrossRef]
  70. Zou, X.; Yue, W.L.; Le Vu, H. Visualization and analysis of mapping knowledge domain of road safety studies. Accid. Anal. Prev. 2018, 118, 131–145. [Google Scholar] [CrossRef]
  71. Didegah, F.; Thelwall, M. Co-saved, co-tweeted, and co-cited networks. J. Assoc. Inf. Sci. Technol. 2018, 69, 959–973. [Google Scholar] [CrossRef]
  72. Rauchfleisch, A.; Schäfer, M.S. Structure and development of science communication research. Co-citation analysis of a developing field. JCOM J. Sci. Commun. 2018, 17, 1–21. [Google Scholar] [CrossRef]
  73. Bollen, J.; Van de Sompel, H.; Smith, J.A.; Luce, R. Toward alternative metrics of journal impact: A comparison of download and citation data. Inf. Process. Manag. 2005, 41, 1419–1440. [Google Scholar] [CrossRef]
  74. Leydesdorff, L.; Rafols, I.; Chen, C. Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations. J. Am. Soc. Inf. Sci. Technol. 2013, 64, 2573–2586. [Google Scholar] [CrossRef]
  75. García-Lillo, F.; Claver-Cortés, E.; Marco-Lajara, B.; Úbeda-García, M. Identifying the ‘knowledge base’or ‘intellectual structure’of research on international business, 2000–2015: A citation/co-citation analysis of JIBS. Int. Bus. Rev. 2019, 28, 713–726. [Google Scholar] [CrossRef]
  76. Réale, D.; Khelfaoui, M.; Montiglio, P.-O.; Gingras, Y. Mapping the dynamics of research networks in ecology and evolution using co-citation analysis (1975–2014). Scientometrics 2020, 122, 1361–1385. [Google Scholar] [CrossRef]
  77. Nakano, Y.; Shimizu, T.; Yoshikawa, M. A visualization of relationships among papers using citation and co-citation information. In Proceedings of the Digital Libraries: Knowledge, Information, and Data in an Open Access Society, 18th International Conference on Asia-Pacific Digital Libraries, ICADL 2016, Tsukuba, Japan, 7–9 December 2016; Proceedings 18. pp. 157–163. [Google Scholar]
  78. Lei, H.; Zhou, Y. Conducting heritage tourism-Led urban renewal in Chinese historical and cultural urban spaces: A case study of Datong. Land 2022, 11, 2122. [Google Scholar] [CrossRef]
  79. Trujillo, C.M.; Long, T.M. Document co-citation analysis to enhance transdisciplinary research. Sci. Adv. 2018, 4, e1701130. [Google Scholar] [CrossRef]
  80. Khasseh, A.A.; Soheili, F.; Mousavi Chelak, A. An author co-citation analysis of 37 years of iMetrics. Electron. Libr. 2018, 36, 319–337. [Google Scholar] [CrossRef]
  81. Uddin, S.; Hossain, L.; Rasmussen, K. Network effects on scientific collaborations. PLoS ONE 2013, 8, e57546. [Google Scholar] [CrossRef]
  82. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K. Detecting emerging research fronts based on topological measures in citation networks of scientific publications. Technovation 2008, 28, 758–775. [Google Scholar] [CrossRef]
  83. Jiang, D.; Tang, C.; Zhang, A. Cluster analysis for gene expression data: A survey. IEEE Trans. Knowl. Data Eng. 2004, 16, 1370–1386. [Google Scholar] [CrossRef]
  84. Brown, M.F. Heritage trouble: Recent work on the protection of intangible cultural property. Int. J. Cult. Prop. 2005, 12, 40–61. [Google Scholar] [CrossRef]
  85. Zhang, Q.; Rong, G.; Meng, Q.; Yu, M.; Xie, Q.; Fang, J. Outlining the keyword co-occurrence trends in Shuanghuanglian injection research: A bibliometric study using CiteSpace III. J. Tradit. Chin. Med. Sci. 2020, 7, 189–198. [Google Scholar] [CrossRef]
  86. Wu, M.; Yu, K.; Zhao, Z.; Zhu, B. Knowledge structure and global trends of machine learning in stroke over the past decade: A scientometric analysis. Heliyon 2024, 10, e24230. [Google Scholar] [CrossRef] [PubMed]
  87. Galati, F.; Bigliardi, B. Industry 4.0: Emerging themes and future research avenues using a text mining approach. Comput. Ind. 2019, 109, 100–113. [Google Scholar] [CrossRef]
  88. Leskovec, J.; Chakrabarti, D.; Kleinberg, J.; Faloutsos, C.; Ghahramani, Z. Kronecker graphs: An approach to modeling networks. J. Mach. Learn. Res. 2010, 11, 985–1042. Available online: https://www.jmlr.org/papers/volume11/leskovec10a/leskovec10a.pdf (accessed on 23 March 2024).
  89. Zaidan, E.; Abulibdeh, A.O. The new cultural turn in urban development for the gulf state: Creativity, place promotion, and identity: Doha as a case study. Political Econ. Soc. Issues 2019, 227, 258. [Google Scholar]
  90. Jiao, L.; Wu, Y.; Fang, K.; Liu, X. Typo-Morphological Approaches for Maintaining the Sustainability of Local Traditional Culture: A Case Study of the Damazhan and Xiaomazhan Historical Area in Guangzhou. Buildings 2023, 13, 2351. [Google Scholar] [CrossRef]
  91. Knapp, R.G. Chinese Houses: The Architectural Heritage of a Nation; Tuttle Publishing: Singapore, 2012. [Google Scholar]
  92. Gülersoy, N.Z.; Gürler, E. Conceptual challenges on urban transformation. A|Z ITU J. Fac. Archit. 2011, 8, 10–24. [Google Scholar]
  93. Capolongo, S.; Sdino, L.; Dell’Ovo, M.; Moioli, R.; Della Torre, S. How to assess urban regeneration proposals by considering conflicting values. Sustainability 2019, 11, 3877. [Google Scholar] [CrossRef]
  94. Akbar, N.; Abubakar, I.R.; Bouregh, A.S. Fostering urban sustainability through the ecological wisdom of traditional settlements. Sustainability 2020, 12, 10033. [Google Scholar] [CrossRef]
  95. Radosavljević, U.; Đorđević, A.; Lalović, K.; Živković, J.; Đukanović, Z. Nodes and networks: The generative role of cultural heritage for urban revival in Kikinda. Sustainability 2019, 11, 2509. [Google Scholar] [CrossRef]
  96. Xiao, W.; Mills, J.; Guidi, G.; Rodríguez-Gonzálvez, P.; Barsanti, S.G.; González-Aguilera, D. Geoinformatics for the conservation and promotion of cultural heritage in support of the UN Sustainable Development Goals. ISPRS J. Photogramm. Remote Sens. 2018, 142, 389–406. [Google Scholar] [CrossRef]
  97. Al-hagla, K.S. Sustainable urban development in historical areas using the tourist trail approach: A case study of the Cultural Heritage and Urban Development (CHUD) project in Saida, Lebanon. Cities 2010, 27, 234–248. [Google Scholar] [CrossRef]
  98. Colapinto, C.; Jayaraman, R.; Ben Abdelaziz, F.; La Torre, D. Environmental sustainability and multifaceted development: Multi-criteria decision models with applications. Ann. Oper. Res. 2020, 293, 405–432. [Google Scholar] [CrossRef]
  99. Labadi, S.; Giliberto, F.; Rosetti, I.; Shetabi, L.; Yildirim, E. Heritage and the sustainable development goals: Policy guidance for heritage and development actors. Int. J. Herit. Stud. 2021, 29. Available online: https://openarchive.icomos.org/id/eprint/2453/ (accessed on 20 March 2024).
  100. Lu, Y.; Ahmad, Y. Heritage protection perspective of sustainable development of traditional villages in Guangxi, China. Sustainability 2023, 15, 3387. [Google Scholar] [CrossRef]
  101. Moscatelli, M.; Raffa, A.; Ulusoy Shipstone, A. Revitalisation of urban spaces by women architects: Enhancing cultural heritage in the gulf region. Archnet IJAR Int. J. Archit. Res. 2023. [Google Scholar] [CrossRef]
  102. Trovato, M.G.; Ali, D.; Nicolas, J.; El Halabi, A.; Meouche, S. Landscape risk assessment model and decision support system for the protection of the natural and cultural heritage in the Eastern Mediterranean Area. Land 2017, 6, 76. [Google Scholar] [CrossRef]
  103. Martínez-Molina, A.; Tort-Ausina, I.; Cho, S.; Vivancos, J.-L. Energy efficiency and thermal comfort in historic buildings: A review. Renew. Sustain. Energy Rev. 2016, 61, 70–85. [Google Scholar] [CrossRef]
  104. De Fino, M.; Galantucci, R.A.; Fatiguso, F. Condition assessment of heritage buildings via photogrammetry: A scoping review from the perspective of decision makers. Heritage 2023, 6, 7031–7066. [Google Scholar] [CrossRef]
  105. Moirano, R.; Sánchez, M.A.; Štěpánek, L. Creative interdisciplinary collaboration: A systematic literature review. Think. Ski. Creat. 2020, 35, 100626. [Google Scholar] [CrossRef]
  106. Zhang, J. Upgrade the Global Partnership Network and Build the New Type of International Relations. In China’s Major Country Diplomacy: Chinese Characteristics, Connotations, and Paths; World Scientific: Singapore, 2021; pp. 93–110. [Google Scholar]
  107. Dahan, N.M.; Doh, J.P.; Oetzel, J.; Yaziji, M. Corporate-NGO collaboration: Co-creating new business models for developing markets. Long Range Plan. 2010, 43, 326–342. [Google Scholar] [CrossRef]
  108. Ranga, M.; Etzkowitz, H. Triple Helix systems: An analytical framework for innovation policy and practice in the Knowledge Society. Entrep. Knowl. Exch. 2015, 117–158, 128. [Google Scholar] [CrossRef]
  109. García-Lillo, F.; Seva-Larrosa, P.; Sánchez-García, E. What is going on in entrepreneurship research? A bibliometric and SNA analysis. J. Bus. Res. 2023, 158, 113624. [Google Scholar] [CrossRef]
  110. Yigitcanlar, T.; Lee, S.H. Korean ubiquitous-eco-city: A smart-sustainable urban form or a branding hoax? Technol. Forecast. Soc. Chang. 2014, 89, 100–114. [Google Scholar] [CrossRef]
  111. Walker, C.; Jackson, M.; Rosenstein, C. Culture and Commerce: Traditional Arts in Economic Development; The Fund for Folk Culture: Santa Fe, NM, USA, 2003. [Google Scholar]
  112. Naheed, S.; Shooshtarian, S. The role of cultural heritage in promoting urban sustainability: A brief review. Land 2022, 11, 1508. [Google Scholar] [CrossRef]
  113. Malik, U.; Tissen, L.N.; Vermeeren, A. 3D reproductions of cultural heritage artifacts: Evaluation of significance and experience. Stud. Digit. Herit. 2021, 5, 1–29. [Google Scholar] [CrossRef]
Buildings 14 01362 g001
Figure 1. Data filtering flow chart.
Figure 1. Data filtering flow chart.
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Figure 2. Author collaboration network.
Figure 2. Author collaboration network.
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Figure 3. Institutional collaboration network.
Figure 3. Institutional collaboration network.
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Figure 4. National collaboration network.
Figure 4. National collaboration network.
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Figure 5. Journal co-citation analysis.
Figure 5. Journal co-citation analysis.
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Figure 6. Co-citation analysis of references.
Figure 6. Co-citation analysis of references.
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Figure 7. Co-citation analysis of authors.
Figure 7. Co-citation analysis of authors.
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Figure 8. Co-occurrence analysis of keywords.
Figure 8. Co-occurrence analysis of keywords.
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Figure 9. Keyword emergence analysis diagram.
Figure 9. Keyword emergence analysis diagram.
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Table 1. Search keywords.
Table 1. Search keywords.
TopicSearch Terms
Urban renewalurban renewal OR urban regeneration OR urban revitalization OR urban reconstruction OR urban revival OR urban renovation OR urban transformation OR urban innovation OR urban improvement OR urban renaissance OR city renewal OR city regeneration OR city revitalization OR city reconstruction OR city revival OR city renovation OR city transformation OR city innovation OR city improvement OR city renaissance
Traditional
village		traditional village OR historic village OR cultural village OR ancient village OR folk village OR old village OR historic site OR cultural heritage OR old architecture OR old scenery OR folk art OR folk custom OR rural village OR old dwelling OR old street
Cultural heritagecultural heritage OR cultural relic OR cultural site OR cultural object OR cultural remains OR cultural wealth OR cultural resource OR cultural asset OR historical relic OR historical site OR historical object OR historical remains OR cultural inheritance OR cultural essence OR cultural treasure OR historical mark OR historical witness OR historical landmark OR historical footprint OR historical work OR historical masterpiece OR historical imprint OR historical fragment
Protectionconservation OR maintenance OR preservation OR protection OR retention
Table 2. Statistical chart of national cooperation relations.
Table 2. Statistical chart of national cooperation relations.
RankCountriesCountsBetweenness CentralityStart YearEnd Year
1Peoples R China1300.137620062023
2Italy850.142620092023
3Spain350.119120052023
4England320.133319992023
5USA220.044520022023
6Turkey170.001220062023
7Poland140.005920152023
8Australia130.004320112023
9Singapore100.003120102023
10Japan70.016120062023
11Germany70.016920162023
12South Korea60.006820152023
13Greece60.000020152023
14France60.008720102022
15Lithuania50.000020132022
16Croatia50.036420102022
17Portugal50.000020192023
18Belgium40.000020092022
19Israel40.000020052018
20New Zealand40.000020132020
21Russia40.000020152021
22Serbia40.000020152022
23Iran40.067120202023
24Romania40.012220202023
25Netherlands30.000020162021
26Jordan30.000020102023
27Brazil30.000020122018
28Switzerland30.024720162023
29India30.000020092020
30Malaysia30.000020132020
31Canada30.000020132023
32Qatar30.000020192023
33Norway30.000020132021
34Austria30.000020202021
35Herceg20.000020202022
36Cyprus20.000020192023
37Indonesia20.000020162020
38Slovakia20.000020162022
39UArab Emirates20.000020102019
40Egypt20.000020112019
41Mexico20.072020212021
42Kazakhstan20.053120222022
43Montenegro20.018520202022
44Chile10.000020222022
45South Africa10.000020192019
46Latvia10.000020142014
47Iraq10.000020202020
48Colombia10.000020212021
49Bolivia10.000020212021
50Peru10.000020212021
51Ecuador10.000020212021
52Hungary10.000020212021
53Nepal10.000020232023
54Denmark10.000020212021
55Finland10.000020232023
56Liberia10.000020232023
57Cuba10.000020162016
58Nigeria10.000020232023
59Estonia10.000020182018
60Macedonia10.000020182018
61Saudi Arabia10.000020222022
62Palestine10.000020212021
63Slovenia10.000020212021
64Kyrgyzstan10.000020222022
65Uzbekistan10.000020222022
66Kenya10.000020222022
67Pakistan10.000020232023
68Lebanon10.000020192019
69Malta10.000020142014
Table 3. Keyword co-occurrence statistics table.
Table 3. Keyword co-occurrence statistics table.
RankKeywordWeightCountWeight per CountStart YearEnd YearCentralityCluster
Label
1cultural heritage278545.15200420230.2818
2conservation96204.80200520230.0920
3sustainable development93185.17201320230.067
4sustainability89175.24201420230.0519
5urban regeneration86194.53201120230.064
6heritage74154.93199920220.056
7adaptive reuse67135.15201420230.0315
8heritage conservation57124.75201720230.0420
9industrial heritage50114.55200920230.036
10urban renewal48114.36201420230.023
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Xia, J.; Gu, X.; Fu, T.; Ren, Y.; Sun, Y. Trends and Future Directions in Research on the Protection of Traditional Village Cultural Heritage in Urban Renewal. Buildings 2024, 14, 1362. https://doi.org/10.3390/buildings14051362

AMA Style

Xia J, Gu X, Fu T, Ren Y, Sun Y. Trends and Future Directions in Research on the Protection of Traditional Village Cultural Heritage in Urban Renewal. Buildings. 2024; 14(5):1362. https://doi.org/10.3390/buildings14051362

Chicago/Turabian Style

Xia, Jun, Xuefei Gu, Tianru Fu, Yangzhi Ren, and Yazhen Sun. 2024. "Trends and Future Directions in Research on the Protection of Traditional Village Cultural Heritage in Urban Renewal" Buildings 14, no. 5: 1362. https://doi.org/10.3390/buildings14051362

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