Search Results (146)

Urban green spaces (UGSs) and forests play a vital role in shaping sustainable and livable cities, offering not only ecological benefits but also spaces that are essential for human well-being, social interactions, and everyday life. Understanding the landscape features that resonate most with public preferences is essential for enhancing the appeal, accessibility, and functionality of these environments. However, traditional approaches—such as surveys or single-data analyses—often lack the nuance needed to capture the complex and multisensory nature of human responses to green spaces. This study explores a cross-modal methodology that integrates natural language processing (NLP) and deep learning techniques to analyze text and image data collected from public reviews of 19 urban parks in Nanjing. By capturing both subjective emotional expressions and objective visual impressions, this study reveals a consistent public preference for natural landscapes, particularly those featuring evergreen trees, shrubs, and floral elements. Text-based data reflect users’ lived experiences and nuanced perceptions, while image data offers insights into visual appeal and spatial composition. By bridging human-centered insights with data-driven analysis, this research provides a robust framework for evaluating landscape preferences. It also underscores the importance of designing green spaces that are not only ecologically sound but also emotionally resonant and socially inclusive. The findings offer valuable guidance for the planning, design, and adaptive management of urban green infrastructure in ways that support healthier, more responsive, and smarter urban environments. Full article

Understanding how people perceive urban streetscapes is essential for enhancing the visual quality of the urban environment and optimizing street space design. While perceptions are shaped by the interplay of multiple visual elements, existing studies often isolate single semantic features, overlooking their combinations. This study proposes a Landscape Element Combination Extraction Method (SLECEM), which integrates the UniSal saliency detection model and semantic segmentation to identify landscape combinations that play a dominant role in human perceptions of streetscapes. Using street view images (SVIs) from the central area of Futian District, Shenzhen, China, we further construct a multi-dimensional feature–perception coupling analysis framework. The key findings are as follows: 1. Both low-level visual features (e.g., color, contrast, fractal dimension) and high-level semantic features (e.g., tree, sky, and building proportions) significantly influence streetscape perceptions, with strong nonlinear effects from the latter. 2. K-Means clustering of salient landscape element combinations reveals six distinct streetscape types and perception patterns. 3. Combinations of landscape features better reflect holistic human perception than single variables. 4. Tailored urban design strategies are proposed for different streetscape perception goals (e.g., beauty, safety, and liveliness). Overall, this study deepens the understanding of streetscape perception mechanisms and proposes a highly operational quantitative framework, offering systematic theoretical guidance and methodological tools to enhance the responsiveness and sustainability of urban streetscapes. Full article

In the context of cultural tourism integration, tourists’ spatial perception intention is an important carrier of spatial evaluation. In historic cultural districts represented by Jinan Mingfu City, tourists’ perceptual depth remains underexplored, leading to a misalignment between cultural tourism development and spatial quality needs. Taking Jinan Mingfu City as a representative case of a historic cultural district, while the living heritage model has revitalized local economies, the absence of a tourist perspective has resulted in misalignment between cultural tourism development and spatial quality requirements. This study establishes a technical framework encompassing “data crawling-factor aggregation-human-machine collaborative optimization”. It integrates Python web crawlers, SnowNLP sentiment analysis, and TF-IDF text mining technologies to extract physical elements; constructs a three-dimensional evaluation framework of “visual perception-spatial comfort-cultural experience” through SPSS principal component analysis; and quantifies physical element indicators such as green vision rate and signboard clutter index through street view semantic segmentation (OneFormer framework). A synergistic mechanism of machine scoring and manual double-blind scoring is adopted for correlation analysis to determine the impact degree of indicators and optimization strategies. This study identified that indicators such as green vision rate, shading facility coverage, and street enclosure ratio significantly influence tourist evaluations, with a severe deficiency in cultural spaces. Accordingly, it proposes targeted strategies, including visual landscape optimization, facility layout adjustment, and cultural scenario implementation. By breaking away from traditional qualitative evaluation paradigms, this study provides data-based support for the spatial quality enhancement of historic districts, thereby enabling the transformation of these areas from experience-oriented protection to data-driven intelligent renewal and promoting the sustainable development of cultural tourism. Full article

Rural landscape perception is of great significance in understanding the emotional connection between people and rural local environments. Seeking to rectify the problem of incomplete or biased results owing to the separation of objective and subjective landscape perception in previous studies, this study took the village of Chongming District in Shanghai, China, as an example and built an evaluation model that integrated four dimensions and 20 indicators of objective and subjective landscape perception, and used machine learning technology to analyze street view images. Subjective perception has been influenced by landscape color, style, and element perception. Notable spatial disparities have been observed in the distribution of rural landscape indicators across Chongming. This study refines key subjective and objective factors affecting rural landscape perception, and the model provides a new method for the perception evaluation of complex landscapes, providing a theoretical basis and practical reference for rural landscape planning. Full article

Traditional park designs no longer meet the diverse needs of young users amid rising visitor numbers and environmental challenges. Exploring the impact of mountain city parks on youth is crucial, yet localised studies on their spatial perceptions in such unique environments are lacking. Landscape design based on spatial perception evaluation offers a promising approach for renewing mountain parks to address these complex needs. Therefore, a pilot study was conducted in Chongqing’s Pipa Mountain and Eling Parks, involving questionnaire surveys and on-site spatial data collection. Using principal component analysis to select the visual and auditory indicators most related to environmental satisfaction in the overall park and various types of gathering spaces, the results showed that the first principal component of the visual environment in the entrance platform and key nodes (r = 0.41, r = 0.45), as well as the first principal component of the auditory environment in the entrance platform, path platform, and elevated points (r = 0.67, r = 0.85, r = 0.68), all showed significant positive correlations with environmental satisfaction (p < 0.01). Moreover, naturalness and aesthetics were identified as the main factors influencing environmental satisfaction. A random forest model analysed nonlinear relationships, ranking spatial factors by importance. Simultaneously, SHAP analysis highlighted the effects of key factors like elevation changes, green view index, colour diversity, and natural elements. Elevation changes were positively correlated with satisfaction at elevated points but showed a negative correlation in the overall park environment and other gathering spaces. This study explored space-perception dynamics in mountain city parks, proposing strategies to improve environmental quality in various gathering spaces and the park. These findings support creating liveable mountainous environments and guide “human-centred health,” quality enhancement, and sustainable development in renewing mountain city parks. Full article

Urban historic parks face the dual challenge of achieving the living preservation of historic buildings while enhancing contemporary visitor satisfaction. In the context of accelerating urbanization and growing demand for immersive cultural experiences, it is increasingly important to conserve historical and cultural values while maintaining relevance and emotional engagement. This study adopts a mixed-methods approach to develop a predictive model for visitor satisfaction within the framework of living preservation, using Yingzhou West Lake in Fuyang City, Anhui Province, as a representative case. Qualitative methods were employed to identify key landscape narrative dimensions, while quantitative data from structured questionnaires highlighted critical experiential elements such as environmental restoration perception, flow experience, and cultural identity. Three machine-learning algorithms—random forest, Support Vector Machine (SVM), and XGBoost—were applied, with the most accurate model used to analyze the relative contribution of each component to visitor satisfaction. The findings revealed that immersive experiential elements play a central role in shaping satisfaction, while physical and cultural elements, particularly historic buildings and their contextual integration, provide essential structural and emotional support. This study offers data-driven insights for the adaptive reuse and interpretive activation of historic architecture, proposing practical strategies to harmonize cultural continuity with visitor engagement in the sustainable management of urban historic parks. 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 study investigated tourists’ visual perception, aesthetic experience, and behavioral intentions across four types of landscapes. A total of 353 questionnaires were distributed on-site, and the SOR model was used to examine the visual stimuli and aesthetic responses perceived by tourists, followed by laboratory eye-tracking to observe tourists’ points of attention on the Longji Terraced Fields landscape Key findings reveal that different residences and revisiting conditions affect tourists’ visual attention, with the most attention given at the intersections of landscape elements. Furthermore, although landscape visual stimuli do not significantly affect the intention response, eye movement parameters are positively correlated with aesthetic experience. The study contributes to understanding tourist aesthetic perception in terraced rice field landscapes and provides Chinese cases for the aesthetic appreciation of the terrace landscape. Full article

This study aimed to check whether physical signs of children’s presence in the urban space have an impact on sense of safety and preferences. We based the study on an intra- and inter-group design, whereby respondents assessed two types of space: housing estates and green areas. The photos were manipulated to create three scenarios: control (without elements related to children), denotation (spaces supplemented with children’s playgrounds), and connotation (spaces containing elements associated with children). Each scenario was assessed by a separate group of respondents, who were further split between men and women. Analyses have shown that in residential districts, spaces with child-related connotations foster a feeling of safety and enhance the general appeal of the place, especially among women. In turn, direct signs of the presence of children (denotation) have a lesser impact on the positive assessment of the space. In green areas, adding child-related details did not affect women’s feelings but lowered men’s evaluations of safety and preference. The findings suggest that elements associated with children should be used selectively, taking into account the type of space and differences in perception between the sexes. These observations can support the creation of sustainable urban environments: safe and inclusive housing estate and park designs, especially in the context of building cities that foster social integration without exclusions. This is a preliminary study that paves the way for further exploration of the topic. In order to be able to analyse adults’ preferences and safety in more depth, it seems interesting to investigate the shared perception of landscape by children and adults and the possibilities of participatory design of public spaces. Full article

Urbanization has amplified the critical role of urban green spaces in enhancing public health and well-being. While natural landscape elements are known to influence physiological and psychological states through visual perception, their mechanistic pathways remain underexplored, and existing studies often focus on singular environments. This study examines how specific landscape elements affect public health and proposes optimization strategies for urban green space planning. Focusing on five green space types in Kunming (forests, wetlands, urban parks, street green spaces, and residential green spaces), this study employed PSPNet-based semantic segmentation to quantify landscape elements and conducted human–subject experiments using paired visual stimuli. Physiological metrics and psychological questionnaires were analysed to assess health outcomes. Key findings reveal that forests and urban parks, rich in natural elements (Plant and Earth and Mountain Elements), outperformed artificial-dominated spaces (residential/street green spaces) in physiological and psychological restoration. Artificially designed green spaces achieved benefits comparable to natural counterparts when mimicking natural element composition. Notably, aggregated indices (naturalness, artificiality, and enclosure) showed negligible correlations with health outcomes, underscoring the primacy of specific elements. The Plant and Earth and Mountain Elements mediated physiological recovery, while minimizing the Building and Artificial Element and enhancing the Sky Element exposure improved attention coherence. Excessive Water Element perception impaired heart rate stabilization, while psychological restoration mechanisms were multifaceted but were consistently linked to higher natural element proportions. These results provide actionable guidelines for optimizing visual proportions of natural elements in urban green space planning and management. Full article

Emerging evidence underscores the beneficial effects of campus green spaces (CGSs) on student well-being and recovery. Previous research has predominantly examined the independent roles of landscape characteristics and preferences in mental restoration. However, limited studies have explored the complex interrelationships among restorative effects, landscape characteristics, preferences, and place-bonding factors, particularly within the context of CGSs. To address this gap, this study developed a validated campus landscape perception scale comprising three dimensions (perception of natural characteristics, perception of artificial characteristics, spatial perception) and 20 related indicators. In the second phase, the scale was used to investigate the influence mechanism of perceived campus landscape characteristics on mental restoration. A total of 36 CGSs across six higher education institutions in Nanjing were selected, representing diverse spatial types. The restoration experiences of 759 participants were measured using psychological indicators when viewing these landscapes. With the help of deep learning techniques, landscape elements were integrated with perceptual factors for partial least squares (PLS)-based statistical analysis. Our findings indicate that the natural and spatial dimensions significantly influence mental restoration, whereas the artificial dimension does not directly impact psychological health. Nevertheless, all dimensions indirectly enhance mental restoration through landscape preference and perceived restorativeness. The study also revealed the moderating effect of objective landscape elements on the relationship between the perception of landscape characteristics and landscape preference. This study confirms the positive role of perceived campus landscape characteristics in fostering mental restoration among students and elucidates the intricate pathway of influence, namely “perception of landscape characteristics → landscape preference → perceived restorativeness → mental restoration”. These findings offer new insights into the complex processes of environmental restoration, where psychological and physical factors are intertwined. Finally, theoretical and managerial implications for improving landscape planning in restoration research are proposed. Full article

This study explores the design characteristics of approach spaces in architect Yoshiji Takehara’s independent residential works, focusing on their spatial arrangement, sinuosity, and experiential qualities. Through the analysis of Takehara’s projects and interviews with the architect, the research identifies key patterns in approach configurations, including entrance positioning, path complexity, and site-specific adaptations. The findings reveal that Takehara’s designs emphasize winding paths and deliberate spatial sequences, contrasting the simpler approaches of contemporaneous residential designs. The study categorizes approach configurations into distinct typologies, influenced by the site dimensions and entrance placement, and highlights a shift from physical obstructions to subtler, psychologically guided design elements over time. Takehara’s design method translates the concept of “Ma” from traditional tea gardens into the language of modern pathways, integrating traditional Japanese spatial ambiguity into contemporary residential design. This offers strategies to enhance spatial perception and experiential richness. Particularly in compact urban settings, the research provides valuable insights for contemporary residential design, emphasizing the importance of landscape-oriented approaches and spatial sequencing in creating meaningful entry experiences. Full article

The advent of generative artificial intelligence (GAI) technologies has significantly influenced the educational landscape. However, public perceptions and the underlying emotions toward artificial intelligence-generated content (AIGC) applications in education remain complex issues. To address this issue, this study employs LDA network public opinion topic mining and SnowNLP sentiment analysis to comprehensively analyze over 40,000 comments collected from multiple social media platforms in China. Through a detailed analysis of the data, this study examines the distribution of positive and negative emotions and identifies six topics. The study further utilizes visual tools such as word clouds and heatmaps to present the research findings. The results indicate that the emotional polarity across all topics is characterized by a predominance of positive emotions over negative ones. Moreover, an analysis of the keywords across the six topics reveals that each has its own emphasis, yet there are overlaps between them. Therefore, this study, through quantitative methods, also reflects the complex interconnections among the elements within the educational ecosystem. Additionally, this study integrates the six identified topics with the Technology–Organization–Environment (TOE) framework to explore the broad impact of AIGC on education from the perspectives of technology, organization, and environment. This research provides a novel perspective on the emotional attitudes and key concerns of the Chinese public regarding the use of AIGC in education. Full article

This study focuses on the visual attention of residents and tourists to elements of urban landscapes from above. It screens out elements that attract viewers’ attention, assesses their aesthetics, and explores how these aesthetic evaluations affect the psychology of place identity. We tracked data from 30 participants, collected responses from 237 participants, and observed differences in visual behaviors and emotional connections to place identity. The results show that while residents and tourists exhibit similar visual behaviors when viewing the same landscape, they have large differences in their perceptual behaviors for different visual elements and have very different familiarity levels in the place identity dimension. Landmark buildings attract strong visual attention despite their low proportion in the overall landscape. Aesthetic factors such as the color vividness of elements like water, mountains, and landmark buildings significantly affect place identity. This study shows that combining eye-tracking and psychometric analysis can effectively evaluate urban landscape perception and provide valuable insights for visual planning and preservation efforts in historic neighborhoods. Full article

As official terms included in the International Council on Monuments and Sites (ICOMOS) documents, archaeological site parks have gradually emphasized the establishment of sustainable management frameworks for archaeological sites open to the public and enhancing public experiences. The management frameworks should be closely related to the goals of the United Nations and other international conventions on sustainable development. However, they lack implementation strategies to promote archaeological site protection and provide responsible tourism. This research adopts a multi-case study approach to analyze the management of representative archaeological site parks in the United States, Japan, and China to develop a framework for the sustainable management of archaeological site parks. Various values, heritage tourism activities, and public perceptions of each park are examined based on cross-case analysis, which identifies principal elements and strategies for the sustainable management of archaeological parks. The principal elements reflect the archaeological parks’ intrinsic value, utility value, and other values. The strategies are closely related to the design of heritage tourism activities and are in alignment with the UN’s sustainable development goals. The theoretical and practical contributions of this research include the reflection and explanation of the sustainable management practices of archaeological site parks in different national and cultural contexts, considering public perceptions. The proposed framework and strategy integrate management guidelines, theoretical knowledge, and practical experience of public archaeological site parks. The outcomes of this research provide a reference for the study of archaeological parks and the management of heritage landscapes. Full article