Landscape Character Assessment (LCA) in Historic Coal Mining Settings for Landscape Conservation: A Systematic Review

Abstract

Landscape character assessment (LCA) is a crucial tool for conserving an area’s unique character. However, in our literature review, we found no data linking LCA to historic coal mining settings. This systematic review explores the ways in which the landscape character assessment (LCA) methodology has been applied, as well as the factors that influence it, in the conservation of historic coal mine landscapes. It focuses on three areas: analyzing the ways in which LCA has been applied in landscape conservation, proposing recommendations for the application of LCA in historic coal mine setting landscapes, and summarizing the factors that influence LCA in landscape conservation in historic coal mine settings. Methods: This study used the Meta-Analyses (PRISMA) method to perform the systematic review. The whole review was selected from 2030 potential articles; a total of 21 articles were included. Results: This study demonstrates that the LCA approach can be operationalized in the conservation of environmental landscapes in historic coal mines by combining cluster analysis and multi-scale assessment and incorporating other theories. The quality of the results can be affected by factors such as the accuracy and completeness of the data and the complexity and tractability of the model. Conclusions: Future research should focus on improving the data capture technology, model complexity, and design of actionable models. Additionally, we recommend the strategies of enhancing stakeholder engagement and raising public awareness.

1. Introduction

As the most abundant and widely distributed fossil fuel on earth, coal is key to the global energy supply chain and underpins the advancement of global industrial development [1]. However, with the decline in coal resources and the transformation of urban industries, many mines have gradually ceased production, leading to the abandonment or demolition of a large number of sites [2]. In recent years, mining heritage has been regarded as an important form of cultural expression, which has been recognized by the international community and the heritage conservation community [3]. Historic coal mining settings are an important part of the industrialization journey and carry a wealth of historical, cultural, and social value. These sites not only witnessed the Industrial Revolution and socio-economic evolution but also served as strong evidence of the interaction between modern society and the natural environment [4,5]. However, research has consistently shown that historic coal mining settings face significant challenges in terms of conservation and management. Firstly, long-term coal mining activities have led to some areas suffering from severe environmental degradation, including ecological damage and landscape fragmentation. Protecting and restoring the landscape have become important tasks that aim to restore the ecological balance and enhance the sustainable use value of the land [6,7,8,9]. Secondly, the cultural and historical value of many historic coal mining settings may be forgotten or underestimated over time, and preserving this value requires systematic assessments and increased public awareness [10,11].

In this context, landscape character assessments (LCAs) provide a framework and methodology for identifying, assessing, and protecting the uniqueness and value of landscapes [12]. By systematically analyzing landscapes’ characteristics, historical evolution, and current conditions, LCAs can reveal the complex connections between natural and cultural elements in a landscape and provide a scientific basis for its conservation and sustainable management [13,14]. Historic coal mining settings are not only remnants of industrial activities but also a witness to regional history, culture, and social change [15,16]. In the conservation of historical coal mining settings, the application of LCA can help to identify the unique industrial landscape features of these areas and assess their natural and cultural value, as well as human perceptions of this value. This method provides important guidance for the development and implementation of conservation measures [15,17].

This study systematically reviews the literature on LCA-based conservation in historic coal mining settings and landscapes over the last five years, providing a comprehensive analytical framework. It fills the research gaps in the LCA field regarding systematic literature review methods and the application of LCA in historical coal mining settings. In this systematic literature review, we use Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) as the main methodology. According to the PRISMA guidelines, the review should include the following steps: defining the sources of the literature, determining the inclusion criteria, developing a search strategy, specifying the data management method, clarifying the screening process, designing the data collection procedure, identifying the data items, classifying and categorizing them, evaluating the risk of bias in individual studies, and analyzing and discussing the results [18]. This systematic literature review method not only helps to evaluate the current status and application methods of LCA in landscape conservation over the past five years but also provides a scientific basis for identifying and assessing landscape characteristics in historical coal mining environments. It aids in guiding the development of practical landscape conservation strategies and promotes sustainable landscape planning. To complete this systematic review, the following research questions were proposed:

RQ1. How is LCA applied in the context of historic coal mining settings?

RQ2. How does LCA effectively identify and evaluate landscape characteristics in historic coal mining settings?

RQ3. What are the factors that influence the development and implementation of landscape conservation strategies in historic coal mining settings?

2. Theoretical Background

To help with clarity, some important terms are defined in the context of this discussion. The two main terms are historic coal mining settings and landscape character assessment.

2.1. Historic Coal Mining Settings

Currently, there are no studies that provide a clear definition of “historic coal mining settings”. Historic coal mining settings are defined in this study as locations of historical significance connected to coal mining activities and practices. This definition is based on a review of the pertinent literature and a synthesis of the studies that cover the definitions and contents of mining heritage, heritage settings, and mining landscapes. Historic coal mining settings are defined as “places of historical significance associated with coal mining activities and practices”. They includes tangible physical features, such as secondary landscape buildings, sites, machinery, and equipment related to the coal mining industry, as well as intangible social and cultural features and people’s perceptions of the space, such as corporate systems, processes, behavioral norms, and cultural works [19,20,21].

Historical coal mining settings are often shaped by multiple factors, including natural, historical, and social influences, resulting in unique landscape characteristics. Specifically, coal mining activities have damaged natural mountain formations, such as through creating open-pit mines and underground shafts that alter the internal structure of the mountains. The extracted tailings accumulate on the surface, leading to soil and lake pollution, while the wastewater and exhaust gases emitted by smelting plants impact the region’s air quality and water environment. The continuous economic development has driven the expansion of mining areas and the evolution of mining technologies. The ensuing increase in demand has also prompted the construction of related infrastructure, including residential buildings, clubs, auditoriums, transportation facilities, sites, and equipment, as well as production and living cultures. These factors have collectively contributed to the enhancement of the value of historical coal mining settings [22].

To fully understand this phenomenon, it is important to recognize that historical coal mining settings are not merely spaces passively subjected to influences but are also dynamic systems that continue to develop, being impacted by industrial, spatial, political, and cultural activities. These activities include mining, processing, transportation, spatial planning, institutional arrangements, behavioral culture, institutional culture, and spiritual culture. Historical coal mining settings reflect the interconnections between different industries and their evolution over time, profoundly influencing human society, politics, culture, and ideology while embodying the integrality and dynamism of human coal mining activities [22].

2.2. Landscape Character Assessment

A landscape character assessment (LCA) is a method of understanding and expressing the uniqueness of a landscape in which the character and special qualities of a place are assessed and given some value by the integration of social and natural factors. It protects and preserves the unique character of a place and is an important tool in local sustainability, landscape conservation, and management [12]. It operates according to a two-stage process: “characterization” and “value assessment” [23].

As a comprehensive landscape assessment tool, landscape character assessment (LCA) is particularly useful for the conservation of historic coal mining settings. First, LCA can reveal the multi-dimensional characteristics of historic coal mining. These include geomorphological features, vegetation cover, water distribution, and various human-made structures and sites left behind by coal mining activities [24]. By recording and analyzing these features in detail, LCA helps us to understand the landscape patterns and environmental characteristics that are specific to coal mining areas, thus providing accurate baseline information for the development of landscape conservation and reuse strategies. Second, using LCA to assess the cultural and historical value of historic coal mining landscapes is crucial. Historic coal mining settings are not only the material remains of past industrial activities but also a concrete manifestation of regional socio-economic development and the impacts of human activities [5]. LCA helps us assess the cultural and historical value of historic coal mining landscapes by identifying the intangible elements related to these activities, such as mining technology, mining techniques, mining activities, and environmental characteristics. The cultural elements associated with coal mining activities, such as mining technology, miners’ stories, and religious beliefs, highlight the importance of preserving these values and provide an important perspective on landscape conservation [25]. Finally, LCA is an important aspect of guiding conservation and restoration efforts in historic coal mining landscapes. By comprehensively assessing the natural and cultural characteristics of a landscape, LCA provides comprehensive decision support for the development of conservation plans and helps conservationists to balance the needs of ecological restoration and cultural heritage protection [26]. In addition, LCA facilitates public participation and the raising of awareness, enhancing community support and involvement in historic coal mine conservation through public education and engagement activities [27].

To ensure the effective implementation of LCA, it is crucial to clarify its specific operational steps. These steps not only guarantee the systematic and scientific nature of the evaluation process but also provide a solid basis for the protection and management of historical coal mining landscapes. The application of LCA typically includes the following steps: first, clarifying the objectives and scope of the assessment; next, comprehensively collecting relevant data through a literature review, online resources, official data, field surveys, and historical archive research; then, identifying a list of key landscape features and defining the research boundaries; based on this, classifying the landscape characteristics, providing detailed descriptions, and drawing typological maps; finally, conducting a comprehensive assessment of the overall value of the historical coal mining setting landscape [28].

In summary, the application of LCA in the conservation of historic coal mining landscapes not only contributes to an in-depth understanding of the unique landscape characteristics and cultural value of these areas but also provides a scientific basis for conservation and management. It plays a significant and unique role in promoting the conservation and sustainable development of these important heritage sites. However, in reviewing the literature, no data were found regarding the association between historic coal mining settings and LCA.

3. Methodology

This study reviewed the literature on landscape character assessments in historic coal mining settings and landscape conservation over a five-year period (2019–2024) by conducting a systematic review. We explored landscape character assessment (LCA) methods over the past five years, evaluating the current status of its usage, the methods of its application, and the factors affecting the development and implementation of landscape conservation strategies in historic coal mining settings. Figure 1 illustrates the LCA process.

To make sure that future researchers could duplicate this study and carry out additional research, we employed the PRISMA model for our systematic literature review (SLR) [18,29]. In order to respond to the inquiries made in this study, the research team undertook a systematic research process, including a literature search, collation, and analysis.

3.1. Initial Literature Search

The initial literature search was conducted using two research databases: Scopus and the Web of Science Core Collection. The Scopus database was the main database used in this study due to its wide coverage and user-friendly interface. It covers more than 25,000 journals and more than 7000 publishers in a variety of subject areas, including technology, science, education, social sciences, and medicine, as well as the humanities and arts. The Web of Science Core Collection is a highly selective, high-quality scholarly database specializing in high-quality publications from high-impact journals in various disciplines across the globe that allow access to these publications [30]. The selected databases, therefore, cover a wide range of the global literature but still provide a level of quality assurance; they were, therefore, considered sufficient to support our initial literature search.

We used a list of search strings to conduct the initial searches in the selected databases. The purpose of this study was to summarize the scope, approach, and effects of LCA and to explore the factors that influence the development and implementation of landscape conservation strategies in historic coal mining settings. Based on the aims of the study, the team identified the key search strings as “landscape character assessment”, “historic coal mining settings”, and “landscape conservation”. In addition, we endeavored to identify the items contained in the key phrases, and this meticulous approach resulted in the precise search terms shown in

Table 1. Search terms for use in a literature search related to LCA and historic coal mining settings.

Keywords	Terms
Landscape character assessment	landscape character, landscape features, and LCA
Historic coal mining settings	heritage, mining, and landscape
Landscape conservation	assessment, evaluation, conservation, preservation, protection, management, sustainability, and strategy

.

These characters were combined according to the Boolean operators AND and OR. At the same time, based on our research experience, we opted to exclude “life cycle assessment” to avoid generating a large number of irrelevant documents, using NOT to connect them. In addition, when considering other terms similar to “strategy”, we decided to replace the use of strategy with “strateg*”. The final search string used for database retrieval is summarized below:

(“landscape character” OR ”landscape features” OR ”LCA”)

AND

(“heritage” OR ”mining” OR ”landscape”)

AND

(“assessment” OR ”evaluation” OR ”conservation” OR ”preservation” OR ”protection” OR ”management” OR ”sustainability” OR ”strateg*”)

NOT

(“life cycle assessment”)

During the initial search of the literature, the retrieved articles included only research articles published in the Web of Science core collection and Scopus; the articles also had to be written in English and published within the last five years, simultaneously being full-text-accessible literature. The selection criteria are shown in

Table 2. Selection criteria.

	Selection Criteria		N
	Inclusionary	Exclusionary
Initial literature search	Scopus and Web of Science Core Collection database English language Only including research articles Articles from the last five years Full-text-accessible literature	Duplicated papers	1467
Manual screening	Articles that take an LCA approach to the heritage or landscape conservation	Research on LCA that is unrelated to heritage or landscape conservation within the abstract, title, and keywords	123
	Articles that can support the authors in accomplishing their research objectives	Unrelated to the research questions and unable to support the authors in achieving their research objectives	23
	Peer-reviewed empirical studies	Empirical papers that are not peer reviewed	21

. The initial search, based on search strings for the relevant literature published up to April 9 2024, produced aggregated results of 2035 records. Then, 568 records that were duplicated in both databases were removed. Finally, 1467 records remained.

3.2. Manual Screening

During this stage, we manually screened the 1467 articles identified in the initial literature search against the main inclusion and exclusion criteria. Only articles that met the following criteria were included in the final pool: (1) articles that included an LCA approach to heritage or landscape conservation; (2) articles that were relevant to the research question and could support the authors in fulfilling their research objectives; and (3) peer-reviewed empirical studies. The peer-review process ensures the quality of the articles. Empirical studies include quantitative, qualitative, mixed-methods, and design-based studies, as well as surveys. If an article reports multiple experiments or cases, it is considered to be multiple independent empirical studies [30]. In addition, records with the full text missing were identified and removed. The selection criteria are shown in Table 2.

The manual screening process lasted approximately two months and involved two researchers. First, the literature that was unrelated to the research topic was filtered out based on titles, keywords, and abstracts, resulting in 123 articles being retained. Subsequently, a full-text reading of these articles was conducted, ultimately identifying 23 articles (21 empirical studies) that met all criteria, which were then included in the main database for further analysis. The entire PRISMA search and screening process is shown in Figure 2, which displays how many items were added and removed at each step, with the n in the box indicating the number of articles remaining after screening.

3.3. Data Analysis

After completing the search of the main library, we investigated the contents of the selected articles, using both quantitative and qualitative methods to analyze the final 21 publications. The studies were categorized according to the themes described below, with specific details including the following: article metadata, the scope and mode of the LCA application, the effectiveness of LCA implementation in landscape conservation in historic coal mining settings, landscape conservation strategies in historic coal mining settings, and factors influencing the development and implementation of landscape conservation strategies in historic coal mining settings. These themes or categories represent the breadth of coverage of topics related to landscape character assessment (LCA), historic coal mining settings, landscape conservation, and other topics relevant to this review. Thus, we were able to identify the application of LCA methods, techniques, effects, and influence on the development and implementation of conservation strategies in the landscape conservation process in historic coal mining settings.

4. Results and Discussion

This section is divided by subheadings. It provides a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. Specifically, it includes the application of LCA in the context of historic coal mining settings (covering a publication overview and research themes and areas); the role of LCA in effectively identifying and evaluating landscape characteristics (based on case studies and the exploration of application methods); and the key factors influencing the development and implementation of landscape conservation strategies (the overall framework is shown in Figure 3).

4.1. How Is LCA Applied in the Context of Historic Coal Mining Settings?

4.1.1. Publication Overview

As shown in Figure 4, there have been few publications related to the application of landscape character assessment (LCA) methods in the field of landscape conservation over the past five years, with only 21 publications, and the number of publications has fluctuated from year to year. This fluctuation may reflect developments and changes in the field of research. At the same time, this also indicates that there is still considerable room for development in this area of research. In addition, Figure 4 shows that the numbers of publications in 2020 and 2023 are significantly higher than the other years, with eight and six publications, respectively. In addition, the number of publications is somewhat distributed over the years, which suggests that the research may have received differing amounts of attention at different times. This may be a result of the evolution of the research field or topic. The majority of the research included in this study was conducted in China, with nine research articles. The countries and regions included in this study each produced only one research article; these areas include England, Australia, Greece, the United States, Italy, Serbia, and Jordan. Clearly, Chinese academics have paid more attention to evaluating the effectiveness of the LCA approach than researchers from other countries.

The limited number of publications chosen for this review could be attributed to three considerations. First, this study only considered the use of LCA in the field of landscape conservation in terms of the methodology and analysis of influencing factors, which limited it to a specific research area. Second, the databases used in this study were strictly limited to include only the Web of Science Core Collection and Scopus. Third, the research team only allowed papers that were written and published in English to be included.

4.1.2. Research Themes and Areas

Landscape studies from the review period covered a diverse range of objectives that were reflected in several prominent landscape-level research themes and scientific research areas. The findings are categorized into three main themes: analysis of technological dependence and data complexity, focus on cultural and historical characteristics, and exploration of the interactions between ecological and human activities. In more than 50% of the studies reviewed, LCA was related to the following themes: the assessment of landscape characteristics using Geographic Information System (GIS) techniques; working with local communities and stakeholders; targets for intervention and guidelines for conservation; the identification of landscape character types and the determination of landscape character areas; landscape classification and description; the assessment of ecological, cultural, and social value; natural and cultural/social factors; and multi-scale landscape conservation and management. Table 3 lists the main scientific research areas covered by the publications. These include natural, geological, and mountainous landscapes (33%), followed by historic and linear heritage landscapes (24%), rural and tropical landscapes (19%), and wetlands, watersheds, and agricultural landscapes (14%), as well as urban and peri-urban landscape studies (10%).

Our findings suggest that no one has applied LCA methods in the field of landscape conservation in historic coal mining settings in the last five years. However, LCA is a potentially important technique in the process of landscape conservation in historic coal mining settings. Firstly, LCA can be combined with a GIS or remote sensing technology to identify and analyze natural and cultural elements in a systematic and comprehensive way [31]. This can be used to help identify the landscape changes in coal mining areas and the natural features (topography, water bodies, vegetation, etc.) and cultural features (historical buildings, mine ruins, mining equipment, traditional crafts, etc.) in the remaining landscapes. Second, LCA emphasizes community participation and is used to collect preferences and evaluations of landscape features from local residents and stakeholders [32]. These data can reflect community perceptions of and ideas about the landscapes of historic coal mining settings. Furthermore, the successful application of LCA around the world demonstrates its high degree of operationalization and applicability [13]. This provides useful lessons for LCA in relation to landscape conservation in historic coal mining settings. Finally, LCA supports the sustainable development of landscapes and the development of scientifically sound conservation strategies through systematic assessment and management [33], thus contributing to the promotion of landscape conservation in historic coal mining settings. In summary, the application of LCA in historic coal mining settings not only provides a systematic tool for landscape analysis but also effectively promotes community engagement and sustainable development, reflecting its significance and potential in future conservation efforts.

Table 3. LCA research areas in landscape conservation.

Area of Research Related to Landscapes		Representative Studies	Research Focus
Technical dependency and data complexity analysis	Urban and peri-urban landscapes	Lu et al. (2022) X. Yang et al. (2023)	Urban and peri-urban landscape research involves the use of urban geographic data and machine learning techniques to build landscape character assessment systems for the urban built environment. This type of research emphasizes the multidimensionality, complexity, and accuracy of the data in the LCA process [34,35]. Despite technological advancements in data processing, researchers must still ensure data operability and carefully address biases and uncertainties. This balance reinforces existing knowledge and opens new avenues for future research.
	Nature, geology, and mountain landscapes	Koblet and Purves (2020) Y. Zhao et al. (2020) Pan et al. (2022) Koç and Yılmaz (2020) Gülçin and Yılmaz (2020) Nakarmi et al. (2023) D. Yang et al. (2020)	A focus on natural, geological, and mountainous landscapes in relation to the integration of LCA with Chinese landscape philosophy, cultural ecosystem services (CESs), and optimal land-use practices: First-person perceptions of the landscape, GIS mapping, and public participation are emphasized [25,33,36,37,38,39,40]. The integration of traditional philosophy with conventional tools enriches the depth of landscape studies but may lead to conflicts between theory and practice. The breadth and representativeness of public participation can influence the fairness and accuracy of the assessment results.
Focus on cultural and historical characteristics	Historic and linear heritage landscapes	Nevzati et al. (2023) Gkoltsiou and Paraskevopoulou (2021) Pihler et al. (2021) Gürbey and Irmeili (2023) S. Zhao et al. (2023)	Historic and linear heritage landscapes document the identification of landscape features and the assessment of landscape values. These studies highlight the identification of natural features, cultural features, and stakeholder engagement in LCAs [13,23,24,41,42]. However, subjectivity and the diversity of stakeholder opinions may limit the accuracy of the assessment. An over-reliance on existing data can overlook undocumented landscape elements, leading to incomplete evaluation results.
	Rural and tropical landscapes	Hong et al. (2024) Zakariya et al. (2020) Tara et al. (2024) Zulkifli et al. (2020)	This area of research focuses on a combination of subjective and objective approaches to the identification and protection of landscape features. It focuses on documenting natural, cultural, and social factors, as well as the distinctive features of major landscape routes, by conducting on-site observations [14,27,31,32]. This approach may face challenges in integrating perspectives and its tendency to simplify the interactions of complex factors. It is essential to balance subjectivity and objectivity during its application to ensure the comprehensiveness and accuracy of the assessment.
Exploration of ecological and human activity interactions	Wetlands, waters, and agricultural landscapes	Gülçin and Yalçınkaya (2024) Ding et al. (2020) Mazzeo et al. (2022)	This type of research involves analyzing the interactions between natural and human factors using LCA methods. It focuses on the diversity of landscapes, viewpoint analyses, and landscape type associations to support the sustainable conservation and management of landscapes [43,44,45]. However, this approach may underestimate certain micro-scale ecosystem dynamics or overlook the complexities of human activities’ long-term impacts on ecosystems.

Table 3. LCA research areas in landscape conservation.

Area of Research Related to Landscapes		Representative Studies	Research Focus
Technical dependency and data complexity analysis	Urban and peri-urban landscapes	Lu et al. (2022) X. Yang et al. (2023)	Urban and peri-urban landscape research involves the use of urban geographic data and machine learning techniques to build landscape character assessment systems for the urban built environment. This type of research emphasizes the multidimensionality, complexity, and accuracy of the data in the LCA process [34,35]. Despite technological advancements in data processing, researchers must still ensure data operability and carefully address biases and uncertainties. This balance reinforces existing knowledge and opens new avenues for future research.
	Nature, geology, and mountain landscapes	Koblet and Purves (2020) Y. Zhao et al. (2020) Pan et al. (2022) Koç and Yılmaz (2020) Gülçin and Yılmaz (2020) Nakarmi et al. (2023) D. Yang et al. (2020)	A focus on natural, geological, and mountainous landscapes in relation to the integration of LCA with Chinese landscape philosophy, cultural ecosystem services (CESs), and optimal land-use practices: First-person perceptions of the landscape, GIS mapping, and public participation are emphasized [25,33,36,37,38,39,40]. The integration of traditional philosophy with conventional tools enriches the depth of landscape studies but may lead to conflicts between theory and practice. The breadth and representativeness of public participation can influence the fairness and accuracy of the assessment results.
Focus on cultural and historical characteristics	Historic and linear heritage landscapes	Nevzati et al. (2023) Gkoltsiou and Paraskevopoulou (2021) Pihler et al. (2021) Gürbey and Irmeili (2023) S. Zhao et al. (2023)	Historic and linear heritage landscapes document the identification of landscape features and the assessment of landscape values. These studies highlight the identification of natural features, cultural features, and stakeholder engagement in LCAs [13,23,24,41,42]. However, subjectivity and the diversity of stakeholder opinions may limit the accuracy of the assessment. An over-reliance on existing data can overlook undocumented landscape elements, leading to incomplete evaluation results.
	Rural and tropical landscapes	Hong et al. (2024) Zakariya et al. (2020) Tara et al. (2024) Zulkifli et al. (2020)	This area of research focuses on a combination of subjective and objective approaches to the identification and protection of landscape features. It focuses on documenting natural, cultural, and social factors, as well as the distinctive features of major landscape routes, by conducting on-site observations [14,27,31,32]. This approach may face challenges in integrating perspectives and its tendency to simplify the interactions of complex factors. It is essential to balance subjectivity and objectivity during its application to ensure the comprehensiveness and accuracy of the assessment.
Exploration of ecological and human activity interactions	Wetlands, waters, and agricultural landscapes	Gülçin and Yalçınkaya (2024) Ding et al. (2020) Mazzeo et al. (2022)	This type of research involves analyzing the interactions between natural and human factors using LCA methods. It focuses on the diversity of landscapes, viewpoint analyses, and landscape type associations to support the sustainable conservation and management of landscapes [43,44,45]. However, this approach may underestimate certain micro-scale ecosystem dynamics or overlook the complexities of human activities’ long-term impacts on ecosystems.

4.2. How Does LCA Effectively Identify and Evaluate Landscape Characteristics in Historic Coal Mining Settings?

In order to explore how LCA can effectively identify and assess the landscape characteristics of historic coal mining environments, the research team selected several typical cases from the 21 screened articles to be analyzed and summarized. They were classified into two main categories: China and other countries.

4.2.1. Case Studies

• Li River Basin in Guilin, China

In the Guangxi Zhuang Autonomous Region, China, Hong et al. (2024) used a systematic LCA approach to provide a comprehensive framework for identifying and conserving the rural landscape heritage. The study authors collected and analyzed natural data (e.g., elevation, topographic relief, and land cover) and cultural data (e.g., cultural heritage sites, traditional villages, and intangible cultural heritage), using ArcGIS software and cluster analysis to identify natural feature areas; image segmentation software was employed to further refine the integrity of the areas. Combined with the cultural heritage site data, cultural characteristic zones were delineated, and, finally, comprehensive landscape character zones were formed through overlay analysis. Based on these character zones, the authors formulated targeted conservation and management strategies. The results showed that the LCA method provides a scientific, comprehensive, and objective means of landscape characteristic identification and conservation by combining natural and cultural data, which significantly improves the identification accuracy and supports systematic conservation and data-driven decision making. Practical cases verified its operability, effectiveness, and ability to maintain the diversity and uniqueness of the landscape [31]. Although this method has validated its operability and effectiveness in the Guangxi Zhuang Autonomous Region, it has not fully captured the dynamics and subtle cultural features of the landscape due to its reliance on existing data. Therefore, future research could integrate qualitative data to further enhance the assessment outcomes.

• National landscape heritage, China

Y. Zhao et al. (2020) developed a cross-cultural approach to landscape character assessment by combining Western LCA methods with Chinese landscape philosophy. Adopting a mixed research approach, the study identifies tangible and intangible natural and cultural elements through GIS mapping and the cultural interpretation of landscape paintings, providing an innovative and multi-dimensional approach to landscape heritage conservation. Specifically, the study is based on GIS technology, integrating local knowledge and values through a public consultation and participatory GIS (PPGIS), comprehensively describing, analyzing, and evaluating landscape features, and assessing visual impacts through visual domain analysis. The results show that the LCA approach enhances the comprehensiveness and sustainability of landscape management by integrating physical and human factors. The use of a GIS and visual domain analysis enhanced the understanding and conservation of landscape heritage, supported policy development and planning, and facilitated cross-cultural and interdisciplinary dialogues by incorporating Chinese landscape characterization methods [37]. However, reliance on the interpretation of landscape paintings may be overly subjective, affecting the scientific and objective nature of GIS mapping results. Integrating the aesthetic values of landscape paintings with modern ecological theories and developing new landscape evaluation indicators can help balance the relationship between subjective aesthetics and objective science.

• Lushan National Park and its fringes, China

In Mount Lushan, D. Yang et al. (2020) adopted a multi-scale approach, combining the parametric method and a holistic approach, to systematically identify and classify the landscape features of Mount Lushan National Park and its surroundings using GIS technology. The study provides a nested framework for integrating the spatial and administrative dimensions of the area to support regional conservation and planning. Through conducting quantitative analyses (principal component analysis, cluster analysis, etc.) and qualitative identification (manual delineation and a field survey), the study provides a scientific basis and decision support for landscape management. Specific applications include the identification of landscape features at broad, intermediate, and detailed scales, the combination of parametric methods and holistic approaches, the precise delineation of landscape character areas, and the provision of systematic perspectives and reference frameworks to support landscape conservation and planning. The results of this study show that the multi-scale approach achieves spatial and administrative integration, improves the efficiency and accuracy of landscape characteristic identification, demonstrates how protected areas and other landscapes can be integrated into a coherent framework, reduces the fragmentation of landscape conservation, and provides a “common language” through which government departments can develop policies [33]. While multi-scale approaches effectively integrate spatial and management dimensions, their complexity may lead to operational difficulties. Particularly in interdepartmental collaboration, inconsistencies in the understanding and use of data and methods among stakeholders can result in coordination challenges, inconsistent outcomes, or difficulties in policy implementation.

• The United States and Turkey

In the United States and Turkey, the LCA methodology has demonstrated significant results in identifying and classifying landscape features. In West Virginia, the USA, LCA has been successfully used to identify landscape features and define landscape units by comprehensively assessing elements such as landforms, vegetation, water bodies, and human activities, with GIS tools being used to process, analyze, and evaluate the data. Public participation was encouraged during the study to raise awareness of the landscape among local residents. This approach reveals the geographical, geological, historical, and cultural characteristics of the area, promotes community awareness, assigns value to local landscapes, and enhances the “sense of place attachment” and “sense of belonging,” thus contributing to the democratization and effectiveness of conservation and management [40]. Although public participation is widely advocated in landscape conservation, its depth and breadth in practical implementation are often limited, making it difficult to fully reflect the interests and opinions of different groups. Expanding and deepening public participation through digital tools and interactive technologies can enhance its practical impact in landscape conservation.

In Turkey, the application of LCA in the Aras Basin of Erzurum Province successfully defined and classified 71 different landscape types by analyzing data related to topography, geology, land use, vegetation cover, climatic conditions, and cultural elements using GIS technology. The study also encouraged public participation to enhance the awareness and involvement of local residents in the landscape. The results showed that LCA effectively identified and categorized landscape features, supported land-use planning and management, and promoted sustainable regional development. Specifically, LCA enhanced landscape management, balanced ecological conservation and economic development, enhanced decision-making science and public participation, and ensured the sustainable management and conservation of the landscape [38]. However, despite the encouragement of public participation, its actual depth and impact may be limited, and further exploration is needed to determine how to effectively integrate public opinions into decision making.

• Malaysia and Serbia

In Malaysia and Serbia, the LCA methodology had significant effects, optimizing rural tourism routes and improving spatial planning for special-use areas in cultural landscapes. In Pahang and Terengganu, Malaysia, the researchers performed detailed documentation and descriptive analyses of the landscape characteristics of major landscape routes using qualitative methods, as well as identified high-value landscape areas, proposed conservation measures, enhanced landscape management effectiveness, and strengthened the sense of identity and responsibility of local residents for landscape conservation through community participation. The results showed that the LCA developed sustainable landscape conservation policies and significantly enhanced landscape management and regional values [27]. Although qualitative methods are effective in recording and describing landscape features, they lack support from quantitative data. How to combine quantitative data with qualitative descriptions to enhance the scientific rigor and comprehensiveness of landscape assessments remains a topic worthy of further exploration.

In Serbia, a combination of GIS data and field visits were used to classify and assess the region; hierarchical clustering was used to define the landscape types and units, and maps were generated showing regional landscape characteristics. The study found that LCA effectively improved spatial planning documents, set landscape quality objectives such as the protection of agricultural land and the maintenance of ecological corridors, promoted sustainable development and the integration of spatial change, and significantly optimized spatial development [13]. Hierarchical clustering methods are effective in determining landscape types and units; however, their applicability is limited by data quality and the scope of analysis. When applied to different landscape features and regional scales, it is essential to evaluate their effectiveness and stability.

• Jordan

In Jordan, the LCA methodology was applied to urban tourism sites in Amman, producing significant results. The LCA methodology was used to analyze and assess, in detail, the landscape features of the Amman walkaway track, Adventure track, and the Hijaz railway track; it also identified and classified the natural and human landscape features using GIS techniques and field surveys and scored and publicly evaluated their value. The results show that LCA effectively promotes the conservation and management of high-value landscape features and areas, reduces inappropriate development, enhances public participation, and supports sustainable development and scientific decision making [24]. Although LCA has provided an in-depth analysis of urban tourism sites in Amman, the integration of GIS technology and field survey data still faces issues of consistency and accuracy. This integration may be influenced by public subjectivity, affecting the evaluation results. Therefore, future research should explore the combination of public participation and expert opinions, utilizing virtual reality (VR) or augmented reality (AR) technologies to help the public better understand landscape features and improve the accuracy of evaluations. Ensuring data compatibility and accuracy is key to effective analysis.

Specific insights into the ways in which LCA can be applied and its effects are drawn from several reviewed case studies that specifically advance the integration of LCA in the landscape conservation of historic coal mining settings. These insights are summarized in

Table 4. Summary of approaches and effects of integrating LCA in landscape conservation.

Way in Which LCA Was Applied in the Study and Its Effects	Representative Studies
a. Landscape features are successfully identified and classified using GIS technology to collect and analyze data on landforms, vegetation, water bodies, land use, climatic conditions, and cultural elements, and by incorporating public input and feedback. This process supports scientific planning and management, promotes sustainable development and ecological conservation, and enhances public participation in decision making [38,40]. Future research could explore the establishment of a dynamic interaction mechanism between technical analysis and public participation to reduce subjectivity bias.	Nakarmi et al. (2023) Koç and Yılmaz (2020)
b. A combination of GIS tools and digital elevation models (DEMs) are used to process and analyze landscape features, classify and assess areas, optimize the spatial planning of tourism routes and cultural landscapes, support the sustainable conservation and management of landscapes, and enhance community identities and public participation [13,27]. This combination improves classification accuracy but simplifies complex cultural landscape features. Therefore, cultural sensitivity indicators or multi-level classification systems should be introduced to better balance technical analysis with cultural characteristics.	Zakariya et al. (2020) Pihler et al. (2021)
c. Combining GIS technology and field surveys, natural and human landscape features are identified, categorized, scored, and evaluated by the public. This approach effectively promotes the conservation and management of high-value landscapes, enhances community identities, ensures sustainable development, and improves the quality of decision making [24]. However, the evaluation results may be influenced by public subjectivity. Therefore, future research should focus on integrating public participation with expert opinions to optimize the decision-making process.	Gürbey and Irmeili (2023)
d. Combining natural and cultural data, GISs and cluster analysis are used to identify landscape character areas and develop conservation and management strategies. This approach improves the accuracy and effectiveness of identification; scientifically, objectively, and comprehensively identifies and protects landscapes; supports systematic conservation and data-driven decision making; and helps to maintain the diversity and uniqueness of landscapes [31]. However, an over-reliance on data-driven decision making and clustering analysis may lead to an underestimation of cultural values. To enhance the evaluation outcomes, it is recommended to integrate qualitative data as a supplementary resource.	Hong et al. (2024)
e. A cross-cultural approach to landscape assessment is developed in conjunction with Chinese landscape philosophy. The study identifies natural and cultural elements through GIS mapping and the interpretation of landscape paintings. As a result, the sustainability and comprehensiveness of landscape management are enhanced, and the understanding and conservation of landscape heritage are enhanced. This approach not only supports policy development but also promotes cross-cultural dialogue [37]. However, an over-reliance on the interpretation of landscape paintings may appear subjective. Combining their aesthetic value with modern ecological theories and developing new landscape assessment metrics can help balance subjective aesthetics with objective science.	Y. Zhao et al. (2020)
f. A multi-scale approach, combined with parametric and holistic methods, is adopted to systematically identify and classify the landscape features of Mount Lushan National Park and its surrounding areas using high-resolution satellite images and GIS technology. The study achieves spatial and administrative integration by accurately delineating landscape character areas at multiple scales, reducing the fragmentation of landscape protection, improving the identification efficiency and accuracy, and promoting comprehensive landscape protection and planning [33]. However, the complexity of this method increases the operational difficulty, which may lead to the simplification or neglect of certain features.	D. Yang et al. (2020)

. They emphasize the value of LCA to landscape conservation.

In summary, this study shows that the LCA methodology has been applied in several countries and regions to effectively identify, protect, and enhance landscape features through scientific assessment and management, supporting sustainable development and regional planning, and significantly enhancing landscape management and regional values. These cases fully demonstrate the wide applications and remarkable effectiveness of the LCA methodology around the world, especially in China.

4.2.2. Exploring the Application Methods of LCA in Historic Coal Mining Settings

Based on this analysis of the last five years of LCA-applied research, we suggest that the following aspects can be studied when assessing the landscape characteristics of historic coal mining settings:

First, detailed historical and cultural studies of historic coal mining areas can be undertaken to understand the history of coal mining and mining activities and the evolution of communities. This will help to identify and protect relevant cultural heritage and historic landscape features. Spatial data collection and landscape character mapping using GIS technology can then be carried out to identify changes and legacy landscape features in the coal mining area by analyzing historical maps and satellite photographs and using modern remote sensing techniques. In addition, detailed fieldwork is required to record and photograph landscape features such as existing coal mine sites, industrial structures, pits, and waste ground. These features are an important part of the history of coal mining and are of high historical and cultural value. Based on the collected data, historic coal mining settings were classified into different landscape character types (LCTs) and spatially mapped using GIS tools to demonstrate their distribution and characteristics.

Next, public participation and expert assessments were organized to collect community and expert views and evaluations of the landscape features of the historic coal mining area. This enabled us to comprehensively understand the social and cultural values of the landscape features, enhanced the community’s sense of identity and responsibility towards the landscape, and allowed us to formulate corresponding conservation and management strategies. Finally, the landscape assessment framework of LCA was applied, combining natural factors (e.g., topography, water bodies, and vegetation) and cultural factors (e.g., historical sites and industrial sites) to carry out a comprehensive landscape assessment and to identify the features that need to be protected and restored. During this evaluation process, the historical coal mining settings can be analyzed in all directions through multi-scale evaluation, 3D modeling, and virtual reality (VR) technology, as well as employing other theoretical ideas, so as to improve the accuracy and scientificity of the evaluation. At the same time, the main tour routes can be identified, and the landscape features will be observed, recorded, and analyzed to provide valuable insights for future landscape conservation, with the aim of maintaining the visibility and experience of the landscape features. In addition, researchers can combine other theories, methods, or concepts to document and interpret tangible and intangible cultural value in order to enhance the understanding and conservation of landscape heritage.

4.3. What Are the Factors That Influence the Development and Implementation of Landscape Conservation Strategies in Historic Coal Mining Settings?

Previous studies have shown that the factors that may influence the effectiveness of LCA in historic coal mining settings are data accuracy and completeness, model complexity and operability, technical means and environmental factors, stakeholder engagement and public awareness, and cross-sectoral collaboration and policy support. The following are detailed descriptions of these factors:

• Accuracy and completeness of data

In the evaluation of the effectiveness of landscape character assessment (LCA), the accuracy and completeness of the data are crucial. LCA methods rely on accurate data to identify and assess landscape features. Inaccurate data may lead to incorrect assessment results, which may impact the effectiveness of landscape conservation and management strategies [43]. Detailed data collection is essential when conducting landscape character assessments. These data should be collected and validated using a variety of methods, such as archival records, historical documents, geographic information systems (GISs), field surveys, and community interviews [31,42]. A systematic and multi-source data collection and validation process can significantly improve the accuracy of landscape feature identification and enhance the science and effectiveness of landscape management decisions.

Data integrity is equally critical. Complete data can provide comprehensive landscape characterization information to support systematic conservation and data-driven decision making. Data integrity is particularly important in the identification of natural and cultural features. For example, when identifying cultural character areas (CCAs), if heritage data are incomplete, important cultural features may be missed; this affects the delineation of cultural core areas and cultural buffer zones [14]. This lack of data can directly affect the development and implementation of landscape conservation strategies. Therefore, ensuring data integrity is crucial for the successful application of LCA. In summary, the accuracy and completeness of data play a decisive role in LCA; they not only improve the reliability of the assessment results but also provide a solid scientific basis for landscape conservation and management.

2.

Model complexity and tractability

In the application of the LCA methodology, model complexity and operability are key factors in ensuring that the identification and conservation effects achieve the desired goals. For example, in the Li River Basin study in Guilin, natural feature types were identified using cluster analysis, and the spatial extent of the heritage was determined using the minimum cumulative resistance model (MCRM). These complex models and methods have improved the scientific validity and accuracy of the research results [31]. However, complex models also pose challenges in practice due to their high technical requirements and associated operational skills.

In order to improve the operability of LCA methods, studies usually emphasize systematic data selection and comprehensive analysis. For example, in the case studies of Pahang and Terengganu in Malaysia, rural landscape features of coastal routes were integrated to enhance visitor experiences and promote the sustainable management of the landscape. The study used only qualitative methods to propose conservation strategies through the on-site observation, documentation, and assessment of landscape features. These detailed descriptions demonstrate the unique landscape characteristics and cultural influence of each area, providing valuable insights for future development [14]. In addition, communities are often invited to participate in the landscape assessment and management process in LCA approaches, and this type of data collection not only increases the community’s sense of identity with the landscape but also ensures that the assessment and management process is actionable [13].

3.

Technical and environmental factors

The effectiveness of the LCA methodology is significantly influenced by technical and environmental factors, and it relies on a variety of advanced data collection and analysis techniques such as geographic information systems (GISs), remote sensing, 3D modeling, virtual reality (VR), etc. GIS technology integrates spatial and attribute data for the analysis of typologies and spatial information, while remote sensing technology obtains information about changes in the landscape environment through satellite imagery and aerial photographs, thus improving the accuracy and scientific validity of the assessment [14]. In addition, advanced landscape assessment techniques, such as 3D modeling and virtual reality (VR), further enhance our ability to capture and display landscape features, providing a scientific basis for landscape management and conservation [31].

Environmental factors also play an essential role in LCA applications. The conservation of natural features requires the development of targeted conservation measures based on different types of natural feature areas [14]. By identifying and assessing different landscape character types, strategies for protecting forests, restoring agricultural cultivation, enhancing the relevant experiential education, and restoring historic buildings and iconic landscapes can be developed. Such targeted conservation strategies can significantly enhance the natural and cultural value of landscapes [24].

4.

Stakeholder participation and public awareness

Stakeholder participation and public awareness in the use of LCA can enhance the community’s sense of identity and responsibility for the landscape, thereby optimizing landscape conservation and management [31]. Stakeholder perception surveys can help researchers to understand the perceptions and needs of local residents, historians, environmental protection organizations, etc., in relation to landscape conservation and to reach a consensus on conservation and management through collaboration and dialogue [42]. This broad level of participation helps to ensure that LCA implementation programs are inclusive and feasible. During this process, systematically recording and evaluating landscape features can raise the public’s and policymakers’ awareness of landscape conservation, promoting sustainable management and protection of landscapes [14]. Additionally, LCA increases public awareness of landscape conservation through education and outreach activities, thereby increasing societal support for landscape conservation [13]. These factors work together to determine the effectiveness of LCA in different contexts.

5.

Policy support and cross-sectoral cooperation

Policy support and cross-sectoral cooperation are key measures to ensure that LCA is successfully implemented and effective. Landscape conservation and management require multi-sectoral collaboration, and LCA develops an integrated spatial planning program by integrating landscape objectives into the agendas of different sectors (e.g., environmental protection, tourism development, water resource management, and heritage conservation) [42]. Effective cross-sectoral cooperation and communication can promote dialogue between different sectors, ensure the consistency and effectiveness of landscape conservation measures, and reduce the problems of fragmentation and one-sidedness in landscape conservation [13,31]. This cooperative mechanism ensures the effective implementation of landscape conservation measures and promotes the sustainable development of landscapes.

Policy support provides institutional and legal safeguards for the implementation of LCA and helps coordinate the participation of various sectors and stakeholders to ensure the effective implementation of landscape conservation measures [31]. In the case of Pahang and Terengganu in Malaysia, policy support enabled the coordination of landscape character conservation and tourism development through the alignment of policy and planning documents [14]. Furthermore, in the spatial planning process of the Sremski Karlovci cultural landscape, policy support provided the basis for landscape goal setting and the integration of cross-sectoral measures, facilitating the systematic identification and conservation of landscape features [13].

In summary, future studies ought to further focus on the improvement of data collection methods and data capture techniques. This will involve not only optimizing existing techniques but also exploring new methods of improving data accuracy and completeness. The design of model complexity and operational modes is a key focus of research, and model performance and applicability should be enhanced by introducing new theories and optimization techniques. In addition, stakeholder engagement is critical to the success of the study, and consideration should be given to ways to enhance cooperation and ensure stakeholders’ active participation during all stages of the study. Raising public awareness is equally important; enhancing the public’s understanding of the relevant fields through education and publicity can increase social support and the acceptance of the research results.

5. Conclusions

The main goal of this literature review was to analyze the applications and methods of land character assessment (LCA); we further sought to explore the ways in which LCA has been applied and the factors that influence it in the conservation of historic coal mining landscapes. The research team searched two databases using the PRISMA method and screened a total of 21 articles for analysis. Two methods were used to analyze the literature. The first part involved a quantitative descriptive analysis, focusing on the country and the year of publication. The next part comprised a qualitative analysis, emphasizing the following two aspects: analyzing the specific application methods of LCA in landscape conservation and suggesting the application of LCA in landscape conservation in historic coal mining settings. Finally, we discussed the factors influencing the application of LCA in landscape conservation in historical coal mining settings.

The review provides a comprehensive analysis of the application methods and specific cases of LCA, discussing the factors influencing the use of LCA in historic coal mining settings for landscape conservation. The specific application methods of LCA include the use of techniques such as historical maps, remote sensing data, field surveys, and GISs to design browsing routes, collect and identify natural and cultural features, and identify and classify landscape features. At the same time, using systematic assessments, management, and public participation, scientific and reasonable conservation strategies are formulated to promote regional economic development and cultural heritage conservation. Other theoretical ideas can be incorporated into this process to develop cross-cultural landscape assessment methods. We offer the following recommendations regarding LCA’s application to landscape conservation in historic coal mining settings: understanding the history of coal mining and the evolution of mining activities and communities, organizing public and expert participation, and designing itineraries and evaluating them in conjunction with, for example, multi-scalar or other theories. Factors affecting the application of LCA to landscape conservation in historic coal mining settings include data accuracy and completeness, modeling complexity and operability, technical tools and environmental considerations, stakeholder participation and public awareness, and issues of policy support and cross-sectoral cooperation.

The research team provides a comprehensive analysis of the scope and methodology of LCA, considering the ways in which LCA can be applied and the factors that influence it in the conservation of historical coal mining landscapes. This study not only contributes to the general literature on LCA but also has implications for future research in fields related to historic coal mining settings. Although this study makes some contributions to the field of LCA and historic coal mining settings, we must acknowledge that it has some limitations. First, only two databases—the Web of Science Core Collection and Scopus—were searched. Second, the scope of the study was rather narrow, the choice of keywords was not sufficiently inclusive, and the methods of applying LCA in landscape conservation were the sole focus of the empirical research. The selection criteria were limited to research papers, and, after systematic screening, only 21 articles finally met the review criteria, which may have caused the exclusion of some potentially valuable information. In addition, this study was limited to papers written and published in English and may have ignored valuable articles published in other languages. Despite this study’s shortcomings, it summarizes the ways in which LCA can be applied, makes recommendations for its application in historic coal mine environmental protection, as well as the factors that influence it, and promotes the cause of historic coal mine environmental landscape conservation. Given these limitations, it is recommended that other researchers continue to track the use of LCA in historic coal mining settings. Future research could delve deeper into the ways in which the public and experts are involved in LCA, enhance data accuracy, and improve methods for assessing the actionability of landscape features, among other issues.