Landscape Character Assessment (LCA) in Historic Coal Mining Settings for Landscape Conservation: A Systematic Review
Abstract
:1. Introduction
2. Theoretical Background
2.1. Historic Coal Mining Settings
2.2. Landscape Character Assessment
3. Methodology
3.1. Initial Literature Search
3.2. Manual Screening
3.3. Data Analysis
4. Results and Discussion
4.1. How Is LCA Applied in the Context of Historic Coal Mining Settings?
4.1.1. Publication Overview
4.1.2. Research Themes and Areas
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?
4.2.1. Case Studies
- Li River Basin in Guilin, China
- National landscape heritage, China
- Lushan National Park and its fringes, China
- The United States and Turkey
- Malaysia and Serbia
- Jordan
4.2.2. Exploring the Application Methods of LCA in Historic Coal Mining Settings
4.3. What Are the Factors That Influence the Development and Implementation of Landscape Conservation Strategies in Historic Coal Mining Settings?
- Accuracy and completeness of data
- 2.
- Model complexity and tractability
- 3.
- Technical and environmental factors
- 4.
- Stakeholder participation and public awareness
- 5.
- Policy support and cross-sectoral cooperation
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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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 |
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 |
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) |
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Liu, Q.; Zainal Abidin, N.A.; Maliki, N.Z.; Zhang, K.; Li, Z.; Liu, S. Landscape Character Assessment (LCA) in Historic Coal Mining Settings for Landscape Conservation: A Systematic Review. Land 2024, 13, 1396. https://doi.org/10.3390/land13091396
Liu Q, Zainal Abidin NA, Maliki NZ, Zhang K, Li Z, Liu S. Landscape Character Assessment (LCA) in Historic Coal Mining Settings for Landscape Conservation: A Systematic Review. Land. 2024; 13(9):1396. https://doi.org/10.3390/land13091396
Chicago/Turabian StyleLiu, Qi, Nor Arbina Zainal Abidin, Nor Zarifah Maliki, Kailai Zhang, Zhi Li, and Sha Liu. 2024. "Landscape Character Assessment (LCA) in Historic Coal Mining Settings for Landscape Conservation: A Systematic Review" Land 13, no. 9: 1396. https://doi.org/10.3390/land13091396