Search Results (80)

The landscapes of China’s multi-ethnic areas are rich in natural and cultural value, but they are threatened by homogenization and urbanization. This study aims to establish a method for identifying and classifying the landscape characters in China’s multi-ethnic areas to support the protection and sustainable development of the landscape in these areas. Taking the Miao Frontier Corridor as an example, the study optimized a parameterization method of landscape character assessment (LCA), integrated relevant cultural and natural elements, and used the K-means clustering algorithm to determine the landscape character types and regions of the Miao Frontier Corridor. The results show that (1) the natural conditions, ethnic exchanges, and historical institutions of the Miao Frontier Corridor have had a significant impact on its overall landscape; and (2) using ethnic group culture as a cultural element in LCA helps to reveal the unique cultural value of areas with different landscape characters. This study expands the LCA framework and applies it to multi-ethnic areas in China, thereby establishing a database that can serve as the basis for cross-regional landscape protection, management, and development planning in these areas. The research methods can be widely used in other multi-ethnic areas in China. Full article

Small towns in mountainous regions face significant challenges in formulating effective landscape zoning strategies due to pronounced landscape fragmentation, which is driven by both the dominance of large-scale forest resources and the lack of coordination between administrative planning departments. To tackle this problem, this study focused on Yuqian, a quintessential small mountainous town in Hangzhou, Zhejiang Province. The town’s layout was divided into a grid network measuring 70 m × 70 m. A two-step cluster process was employed using ArcGIS and SPSS software to analyze five landscape variables: altitude, slope, land use, heritage density, and visual visibility. Further, eCognition software’s semi-automated segmentation technique, complemented by manual adjustments, helped delineate landscape character types and areas. The overlay analysis integrated these areas with administrative village units, identifying four landscape character types across 35 character areas, which were recategorized into four planning and management zones: urban comprehensive service areas, agricultural and cultural tourism development areas, industrial development growth areas, and mountain forest ecological conservation areas. This result optimizes the current zoning types. These zones closely match governmental sustainable development zoning requirements. Based on these findings, we propose integrated landscape management and conservation strategies, including the cautious expansion of urban areas, leveraging agricultural and cultural tourism, ensuring industrial activities do not impact the natural and village environment adversely, and prioritizing ecological conservation in sensitive areas. This approach integrates spatial and administrative dimensions to enhance landscape connectivity and resource sustainability, providing key guidance for small town development in mountainous regions with unique environmental and cultural contexts. Full article

Mining activities in a quarry significantly interfere with the landscape, weaken its ecological functions, disrupt the continuity of habitats and change its natural character. The aim of this study is to present a robust, transparent, and participatory methodological framework centered on the Reclamation Quality Index, which enables a comprehensive and repeatable assessment of reclamation quality. At a time when the restoration of functional, ecologically stable and long-term sustainable landscapes is increasingly important, there is a need for reliable tools to assess the quality of restoration. This article presents an original methodology for the evaluation of quarry reclamation, which combines scientific precision with practical applicability. The proposed Reclamation Quality Index is built on multidisciplinary foundations and uses the Delphi methodology, through which expert knowledge and weighted preferences enter the evaluation process. A tool designed in this way makes it possible to quantify the quality of land restoration, identify the benefits of individual interventions, support effective planning, and strengthen the strategic management of post-mining transformation. At the same time, the Reclamation Quality Index creates space for the application of the principles of ecological stability and integration of the landscape as a living, dynamic system in the process of restoration. With its structure and philosophy, the methodology represents a prospective approach to the evaluation and planning of the post-extraction landscape. Its application goes beyond academia, as it can serve as a support for environmental policymaking, landscape planning, and assessing the quality of restoration in practice. Full article

Rural landscapes play a key role in preserving ecological processes, cultural identity, and socio-economic well-being, yet these areas often face challenges such as land degradation, water scarcity, and an inadequate road network. A sustainable approach to rural landscape and tourism planning is essential for enhancing both environmental resilience and socio-economic vitality in areas facing degradation and global change. This study aims to develop and validate an integrated methodological workflow that combines Landscape Character Assessment (LCA), ECOVAST guidelines, SWOT analysis, and open-source GIS techniques, complemented by a bottom-up approach of spontaneous fruition mapped through Wikiloc heatmaps. The framework was applied to a case study in Paternò, Eastern Sicily, Italy—a territory distinguished by its key local values such as Calanchi formations, proximity to Mount Etna, and cultural heritage. Through this application, eight distinct Landscape Units (LUs) were delineated, and key strengths, weaknesses, opportunities, and threats for sustainable development were identified. Using open-access data and a survey-free protocol, this approach facilitates detailed landscape assessment without extensive fieldwork. The methodology is readily transferable to other rural Italian and Mediterranean contexts, providing practical guidance for researchers, planners, and stakeholders engaged in sustainable tourism development and landscape management. Full article

The East–West Mountain Region (EWMR) of Wuhan is a vital natural and cultdural asset, characterized by its scenic nature landscapes and rich historical and cultural heritage. This study aims to address the problems of landscape character degradation and weakened public preferences caused by rapid urbanization and proposes a research framework integrating landscape character assessment and public preferences. Initially, we utilize K-means cluster analysis to identify landscape character types based on six landscape elements, resulting in a landscape character map with 20 types. Subsequently, we employ emotion analysis based on Natural Language Processing (NLP) techniques to analyze user-generated content (UGC) from Weibo check-in data to establish perception characteristic indicators reflecting public preferences. Finally, we quantitatively identify the environmental factors influencing public preferences through the SoIVES model and compare and integrate the landscape character map with the public emotion value map. The results show that (1) public preferences hotspots are concentrated in three types: (a) urban construction-driven types, including areas dominated by commercial service functions and those characterized by mixed-function residential areas; (b) natural terrain-dominated types with well-developed supporting facilities; and (c) hybrid transition types predominated by educational and scientific research land uses. These areas generally feature a high degree of functional diversity and good transportation accessibility. (2) Landscapes eliciting stronger emotional responses integrate moderate slopes, multifunctional spaces, and robust public services, whereas areas with weaker responses are characterized by single-function use or excessive urbanization. (3) The emotional variations within categories could be influenced by (a) functional hybridity through enhanced environmental exploration; (b) spatial usage frequency through place attachment formation; and (c) visual harmony through cognitive overload prevention. These findings provide critical insights for formulating zoning optimization plans aimed at the refined conservation and utilization of urban landscape resources, as well as offering guidance for improving landscape planning and management in the EWMR. Full article

This article seeks to demonstrate the value of landscape character assessment in addressing the unique needs of remote areas, located at national insular borders, with lower levels of development and economic activity. The paper assesses and presents the predominant landscape character of a remote agricultural area in the north part of the island of Crete in Greece, the specific assets of various landscape character types with the main productive economic sectors, leading to a proposal for tourism development sustainable strategies. To achieve this, a landscape character assessment methodology was applied in combination with a literature review and landscape evaluation per each economic sector. The goals of a landscape strategy for the area were formulated to preserve and enhance the landscape character and uniqueness, as natural and cultural heritage, for the benefit of the island inhabitants. At the end, landscape strategies for the planning, management and protection of the specific area were proposed for its sustainable development. Full article

Rural landscape character assessment (LCA) is significant for identifying and understanding rural landscapes and maintaining the cultural connotations of the rural vernacular. Taking the rural area of Songzi City as an example, this study identifies the landscape character (LC) and analyzes the coupling between the current state of its LC and a construction project based on the depth of rural landscape planning in the county and combining the ecology, arable land, and water body protection boundary as constraints. Thus, we obtain the “point, line, and surface” site selection suggestions for the construction activities of leisure agriculture, power grid, and energy facilities, and the zoning classification and layout control strategies for LC are subsequently proposed. The results show the following: (1) The county LC factor is a combination of natural and human factors used to obtain 165 LC areas in Songzi City. (2) The current state of rural LC is used to determine LCs from shallow to deep and to provide the basis for index selection and judgment for evaluation. (3) The coupling relationship between rural LC and construction projects varies and must be judged using subjective and objective methods, desktop research combined with field analyses, and multi-stakeholder participation. Based on the perspective of coupling and coordinating human and landscape, this study applies local-scale LCA to practice, strengthens the interface with rural construction planning, and provides research ideas and methodological references for the sustainable control of rural LC. Full article

Moving away from a static concept for the landscape that surrounds us, in this research article, we approach the visual landscape as a dynamic concept. Moreover, we attempt to provide an interconnection between the domains of landscape and cartography by designing maps that are particularly suitable for characterizing the visible landscape and are potentially meaningful for overall landscape evaluation. Thus, the present work mainly focuses on the consecutive computation of vistas along highways, incorporating actual landscape composition—as the landscape is perceived from an egocentric perspective by observers moving along highway routes in peri-urban landscapes. To this end, we developed an integrated method and a Python (version 2.7.16) tool, named “RouteLAND”, for implementing an algorithmic geoprocessing procedure; through this geoprocessing tool, sequences of composite dynamic geospatial analyses and geometric calculations are automatically implemented. The final outputs are interactive web maps, whereby the segments of highway routes are characterized according to the dominant element of the visible landscape by employing (spatial) aggregation techniques. The developed geoprocessing tool and the generated interactive map provide a cartographic exploratory tool for summarizing the landscape character of highways in any peri-urban landscape, while hypothetically moving in a vehicle. In addition, RouteLAND can potentially aid in the assessment of existing or future highways’ scenic level and in the sustainable design of new highways based on the minimization of intrusive artificial structures’ vistas; in this sense, RouteLAND can serve as a valuable tool for landscape evaluation and sustainable spatial planning and development. Full article

In recent years, rapid urbanization has transformed the man–land relationship in rural areas, highlighting issues such as the homogenization of vernacular landscapes. This study uses the Liuxi River in Guangzhou as a case and applies a hierarchical interpretation system for vernacular landscapes, utilizing methods from landscape character assessment (LCA) and Historic Landscape Characterization (HLC). Focusing on two scales, “basin” and “vernacular unit”, this study proposes a framework for identifying vernacular landscape patterns. This framework includes scale definition, pattern identification, feature description, and factor analysis. At the basin scale, the investigation concentrates on spatial configurations of vernacular landscapes in 1985, whereas the unit-scale analysis delineates temporal evolutionary trajectories spanning 1974–2020. The results indicate significant differences in landscape fragmentation, dominance, and diversity between upstream and downstream at the basin scale. At the unit scale, the landscape connectivity in the Shaxi River unit remains relatively stable, while landscape heterogeneity increases, resulting in greater diversity. This study provides valuable insights into the continuity and development of diversity in analogous vernacular landscape regions globally, particularly those comparable to the Liuxi River basin. Full article

The field of text summarization has evolved from basic extractive methods that identify key sentences to sophisticated abstractive techniques that generate contextually meaningful summaries. In today’s digital landscape, where an immense volume of textual data is produced every day, the need for concise and coherent summaries is more crucial than ever. However, summarizing short texts, particularly from platforms like Twitter, presents unique challenges due to character constraints, informal language, and noise from elements such as hashtags, mentions, and URLs. To overcome these challenges, this paper introduces a deep learning framework for automated short text summarization on Twitter. The proposed approach combines bidirectional encoder representations from transformers (BERT) with a transformer-based encoder–decoder architecture (TEDA), incorporating an attention mechanism to improve contextual understanding. Additionally, long short-term memory (LSTM) networks are integrated within BERT to effectively capture long-range dependencies in tweets and their summaries. This hybrid model ensures that generated summaries remain informative, concise, and contextually relevant while minimizing redundancy. The performance of the proposed framework was assessed using three benchmark Twitter datasets—Hagupit, SHShoot, and Hyderabad Blast—with ROUGE scores serving as the evaluation metric. Experimental results demonstrate that the model surpasses existing approaches in accurately capturing key information from tweets. These findings underscore the framework’s effectiveness in automated short text summarization, offering a robust solution for efficiently processing and summarizing large-scale social media content. Full article

This study examined the historical compatibility of urban furniture in Harput Sarahatun Mosque Square, Elazığ, Türkiye. It evaluated AI-generated modern and classical-style alternatives using the Semantic Differentiation Method. The research aimed to compare existing furniture with AI-assisted designs and identify key attributes influencing historical and spatial integration. The methodology consists of four stages: (1) defining adjective pairs to assess historical compatibility through expert opinions and literature review; (2) photographing existing urban furniture and generating AI-assisted modern and classical-style urban furniture (benches, trash cans, and lighting elements); (3) determination expert opinion using the survey; (4) statistical analysis of results through descriptive statistics and explanatory factor analysis (EFA). The study, which was conducted online in February 2025, involved 31 experts from the architecture and landscape architecture disciplines. The findings show that existing furniture is mainly judged by practicality and usability, with limited attention to historical integration. Modern AI-generated designs emphasize innovation, minimalism, and contemporary aesthetics. In contrast, classical-style AI-generated furniture is appreciated for its historical compatibility, cultural resonance, and aesthetic harmony. Experts favored classical alternatives for their alignment with traditional urban character. The results highlight the need for future designs to balance functionality, sustainability, and historical continuity, ensuring urban furniture contributes to cultural preservation and modern urban needs. Full article

Globalization has profoundly impacted architecture by promoting urban homogenization, where global styles and materials overshadow local character. This shift prioritizes standardized functionality and energy efficiency over cultural identity, erasing regional architectural distinctiveness. In historical urban centers, globalization-driven interventions—such as ventilated facades or external thermal insulation systems (ETISs)—often simplify original compositions and alter building materiality, texture, and color. The Ensanche of San Sebastián serves as a case study highlighting this issue. Despite its architectural richness, which includes neoclassical and modernist buildings primarily constructed with sandstone from the Igeldo quarry, unprotected buildings are at risk of unsympathetic renovations. Such changes can distort the identity of what is considered “everyday heritage”, encompassing the residential buildings and public spaces that shape the collective memory of cities. This study presents a replicable methodology for assessing the vulnerability of buildings to facade interventions. By utilizing tools like digital twins, point cloud modeling, and typological analysis, the research establishes criteria for interventions aimed at preserving architectural values. It emphasizes the importance of collaborative efforts with urban planning authorities and public awareness campaigns to safeguard heritage. Ultimately, protecting architectural identity requires balancing the goals of energy efficiency with cultural preservation. This approach ensures that urban landscapes maintain their historical and social significance amidst globalization pressures. Full article

Disaster-prone mountainous regions face complex human–environment conflicts resulting from the combined influences of natural disaster threats, ecosystem conservation, and resource development. This study takes Mentougou District as the research area, leveraging landscape character identification methods to develop a multidimensional evaluation framework integrating safety, ecology, and landscape aspects, providing a foundation for zoning and management decisions. Four characteristic elements—elevation, geomorphology, vegetation type, and land cover type—were extracted during the landscape character identification phase. Two-step clustering and eCognition multi-scale segmentation were used to identify 12 landscape character types (LCTs) and delineate Landscape Character Areas (LCAs). The MaxEnt model was applied during the evaluation phase to assess debris flow susceptibility. At the same time, AHP and ArcGIS spatial overlay methods were used to evaluate ecological resilience and landscape resource quality. The three-dimensional evaluation results for the 12 LCAs were clustered and manually interpreted, resulting in four levels of protection and development areas. Management strategies were proposed from three perspectives: debris flow disaster prevention, ecosystem conservation, and landscape resource development. This method provides a pathway to balance human–environment conflicts in disaster-prone mountainous regions, promoting scientific zoning management and sustainable development in vast mountainous areas. Full article

Grounded in the theoretical and methodological frameworks of landscape character identification from the European Landscape Map (LANMAP) and landscape character assessment (LCA), this study developed an AI-based tool for landscape character analysis to classify the Jianghan Plain’s landscape more effectively. The proposed method leveraged a deep learning model, the artificial intelligence-based landscape character (AI-LC) classifier, along with specific naming and coding rules for the unique landscape character of the Jianghan Plain. Experimental results showed a significant improvement in classification accuracy, reaching 89% and 86% compared to traditional methods. The classifier identified 10 macro-level and 18 meso-level landscape character types within the region, which were further categorized into four primary zones—a lake network river basin, a hillfront terrace, surrounding mountains, and a lake network island hill—based on natural and social features. These advancements contributed to the theoretical framework of landscape character assessment, offering practical insights for landscape planning and conservation while highlighting AI’s transformative potential in environmental research and management. Full article

In view of global climate and environmental challenges, exploring sustainable urban vegetation management and development is crucial. This study aims to investigate the design strategies of urban road green space plants under the guidance of the dual theories of carbon sequestration and cooling eco-efficiency and aesthetics. In this study, Yangling, a representative small- and medium-sized city, was selected as the study area, and road green space plants were identified as the research objects. The assimilation method was employed to ascertain the carbon sequestration and oxygen release, as well as the cooling and humidification capacities of the plants. The aesthetic quality of the plants was evaluated using the Scenic Beauty Estimation and Landscape Character Assessment. Finally, we propose design strategies for landscapes with higher aesthetic and carbon sequestration and cooling benefits. The results demonstrate a clear nonlinear positive correlation. The carbon sequestration and cooling benefits of plants and the aesthetic quality, with correlation coefficients of 0.864 and 0.922, respectively. Across the same sample points, the rankings of standardized values for carbon sequestration, cooling benefits, and aesthetic quality vary minimally. This indicates that eco-efficient plants with harmonious colors and elegant forms can boost the aesthetic appeal and ecological function in road green spaces. Furthermore, the Sophora japonica Linn., Ligustrum lucidum Ait., Koelreuteria paniculata Laxm., Prunus serrulata Lindl., Prunus cerasifera Ehrhar f., Ligustrum sinense Lour., Photinia × fraseri Dress, Ligustrum × vicaryi Rehder, Sabina chinensis (L.) Ant. cv. Kaizuca, and Ophiopogon japonicus (L. f.) Ker Gawl. are proved to be ecologically dominant plants. They can be employed as the principal selected species for plant design. This study summarizes applicable design strategies for three types of green spaces: avenue greenbelts, traffic separation zones, and roadside greenbelts. The nonlinear regression model developed here provides a reference for scientifically assessing and optimizing urban planting designs. Full article