Search Results (24)

Historical and cultural districts are the outcome of cultural sedimentation brought about by urban development, and they embody distinctive urban historical and cultural connotations. Ignoring the protection of the historical and cultural value contained in streetscapes will not only decrease the life quality of residents but will also diminish distinctive local urban features. This study focused on the Fangcheng historical and cultural district in Shenyang. The scenic beauty estimation method was employed to evaluate urban style and features’ visual quality, while the semantic differential method was used to obtain the subjective perceptual features of samples. The study also systematically explored the dynamic relationship between urban style and features’ quality and subjective perception in historical and cultural districts. The results show that color richness, coherence, iconic status, and continuum all exert significant positive predictive effects on visual preferences regarding urban style and features. Color richness was the primary determinant of urban style and features’ visual quality. Continuum interfaces, a unified spatial texture, and coordinated dimensions contributed significantly to improving urban style and features’ visual quality in historic and cultural districts. The distinctiveness and cultural iconic status of historical and cultural districts enhanced the residents’ identity and place memory. Moreover, the coherence and continuum of style between the old and new elements promoted an integrated aesthetic experience. The evaluation results revealed that the overall visual quality of urban style and features of most streets was medium. However, streets with a higher visual quality cluster among historical streets and commercial streets. The residential streets demonstrated a significantly lower visual quality. Establishing a comprehensive evaluation system that integrates urban style and features, subjective perception, and the style of historical and cultural districts can contribute to covering the shortage in the traditional urban style and features’ research and also provide a basis for urban regeneration at the micro scale. Full article

Wind turbines can affect perceived landscape quality, particularly in open rural settings where their scale and distinctive form make them a strong visual dominant. This article presents model-based research on how turbine setback distance from residential buildings influences the visual perception of rural landscapes in Poland. A modified Scenic Beauty Estimation (SBE) method was applied, using standardized computer-generated visualizations instead of real-world photographs of seven rural landscape types. For each type, four variants were assessed: a reference view and three scenarios with turbines located 500, 750, and 1000 m from residential buildings. Shorter setback distances significantly reduced visual ratings (ANOVA, p < 0.001). The lowest ratings occurred at 500 m, particularly in the large-scale arable farming landscape (Z = −0.886), while the highest ratings were recorded for reference variants, especially in the mountain agricultural landscape (Z = 1.20). Landscape type was also significant, with open areas proving more sensitive to turbine presence than structurally complex landscapes. Linear trend analysis confirmed that increasing setback distance is associated with higher visual ratings (F(1, 2140) = 31.60; p < 0.001; R² = 0.01). These findings indicate that perceptual landscape assessment supports wind turbine siting and, when combined with geographic information systems (GIS) and Landscape and Visual Impact Assessment (LVIA), enables a more comprehensive evaluation of project-related environmental effects. Full article

National urban wetland parks serve as key platforms for ecological conservation and recreation, yet the synergistic mechanisms between plant color dynamics and public aesthetic perception remain underexplored. Understanding these mechanisms is crucial for evidence-based, climate-resilient landscape design. This study quantifies statistical associations between seasonal color and aesthetic patterns in two national wetland parks (South Dian Lake and Laoyu Lake, Kunming) using Hue–Saturation–Brightness (HSB) color metrics and Scenic Beauty Estimation (SBE) based on year-round monitoring at 24 sample sites. Regression analysis revealed that overall SBE values ranged from −1.027 to 0.756, indicating medium aesthetic quality, with South Dian Lake outperforming Laoyu Lake, particularly in aquatic plant communities. Seasonal trends showed the highest aesthetic preference in winter (orange–yellow dominant, 0.110) and the lowest in early spring (−0.167, yellow dominant), followed by relatively stable values from late spring to mid-autumn (0.007–0.020) and a secondary peak in late autumn (0.029). Higher SBE scores were associated with a dominant hue ratio of 70–75%, balancing color unity and diversity. We identify an operational plant color configuration—70–75% dominant hue, 20% evergreen foliage and 5–7 color types—that corresponds to higher SBE scores. By translating aesthetic responses into quantitative color targets, this study provides guidance for climate-adaptive planting design and seasonal management in subtropical wetland landscapes under global warming. Full article

Landscape quality and the productivity of $\mathit{Rhododendron\; simsii}$ are directly related to the maintenance of ecological functions in the alpine region. The specific relationship between the spatial pattern of colour patches and the visual quality of R. simsii landscape recreational forests has been insufficiently explored. In this study, we constructed a model of the relationship between landscape colour patches and the aesthetic value of such a forest, analysing the key factors driving changes in its landscape quality. A total of 1549 participants were asked to assess 16 groups of landscape photographs. The results showed that variations in perceived aesthetic quality were stimulated by colour patch dynamics and spatial heterogeneity. Utilising structural equation modelling (SEM), we identified key indicators synergistically influencing aesthetic quality, including the area percentage, shape, and distribution of colour patches, which demonstrated strong explanatory power ($R^2$ = 0.83). The SEM also revealed that the red patch area, mean perimeter area ratio, and separation index are critical latent variables with standardised coefficients of 0.54, 0.65, and 0.62, respectively. These findings provide actionable design strategies: (1) optimising chromatic contrast through high-saturation patches, (2) controlling geometric complexity, and (3) improving spatial coherence. These results advance the theoretical framework for landscape aesthetic evaluation and offer practical guidance for landscape recreational forest management. Full article

Urban parks are an important component of public urban spaces, which directly impact the living experiences of residents and the urban image. High-quality urban parks are crucial for enhancing the well-being of residents. This study selected Fukuoka, Japan, as the study site. Five urban parks were chosen to evaluate landscape visual quality by using the Scenic Beauty Estimation (SBE) method. The Semantic Differential (SD) method was used to get sample subjective landscape features. Meanwhile, sample objective landscape features were obtained by using semantic segmentation techniques in deep learning and combined with spatial analysis to understand their distribution. A regression model was established, which used the SBE values as the dependent variable and subjective landscape features as the independent variables to analyze the relationship between urban park landscape visual quality and subjective landscape features. The regression analysis revealed that sense of layering, harmony, interestingness, sense of order, and vitality were the core factors influencing visual quality. All five features had a significant positive impact on landscape visual quality. The sense of order was the most influential factor, which would be the key to enhancing the landscape perception experience. Moreover, the XGBoost model and SHAP value from machine learning were used to reveal the nonlinear relationships and significant threshold effects between urban park visual quality and five objective landscape features: openness, greenness, enclosure, vegetation diversity, and Shannon–Wiener diversity index. This study showed that when openness exceeded 0.27, the positive effect was significant. The optimal threshold for the greenness was 0.38. Vegetation diversity and enclosure had to be below 0.82 and 0.58, respectively, to have a positive impact. Meanwhile, the positive influence of the Shannon–Wiener diversity index reached its maximum at a value of 1.37. This study not only establishes a systematic method for diagnosing landscape problems and evaluating landscape visual quality but also provides both theoretical support and practical guidance for urban park landscape optimization. Full article

Flowering street trees are important carriers of urban landscapes and ecological functions, as well as a significant boost to the construction of “Shanghai Flower City”. Most existing studies focus on the ornamental value or single ecological benefits, and there are insufficient systematic evaluations of the landscape–ecology synergistic effect, especially as there are few quantitative studies on the landscape value during the flowering period and long-term ecological benefits. Scientific assessment of multiple benefits is of great significance for optimizing tree species allocation and enhancing the sustainability of road landscapes. Taking flowering street trees in Shanghai’s central urban area as a case study, this paper verifies the feasibility of using digital technology to evaluate their landscape and ecological benefits and explores ways to enhance these aspects. Landscape, ecological, and comprehensive benefits were quantitatively assessed using digital images, the i-Tree model, and the entropy-weighted method. Influencing factors for each aspect were also analyzed. The results showed the following: (1) Eleven species or cultivars of flowering street trees from six families and ten genera were identified, with the majority flowering in spring, fewer in summer and autumn, and none in winter. (2) The landscape benefits model was: Scenic Beauty Estimation (SBE) = −0.99 + 0.133 × Flowering branches+ 0.183 × Degree of flower display + 0.064 × Plant growth + 0.032 × Artistic conception + 0.091 × Visual harmony with surrounding elements. Melia azedarach L., Prunus × yedoensis ‘Somei-yoshino’, and Paulownia tomentosa (Thunb.) Steud. ranked highest in landscape benefits. (3) Catalpa bungei C. A. Mey., Koelreuteria bipinnata Franch., and Koelreuteria bipinnata ‘integrifoliola’ (Merr.) T.Chen had the highest plant height, diameter at breast height (DBH), and crown width among the studied trees, and ranked top in ecological benefits. (4) Koelreuteria bipinnata, Catalpa bungei, and Melia azedarach showed the best overall performance. The comprehensive benefits model was: Comprehensive Benefits = 0.6889 × Ecological benefits + 0.3111 × Landscape benefits. This study constructs a digital evaluation framework for flowering street trees, quantifies their landscape and ecological benefits, and provides optimization strategies for the selection and application of flowering trees in urban streets. Full article

The landscape visual sensitivity (LVS) assessment is recognized as a critical tool for identifying areas most sensitive to landscape changes and for informing multi-resource optimization and allocation strategies. However, conventional large-scale LVS assessment criteria and methodologies developed for natural landscapes do not satisfy the precision-oriented assessment requirements of streetscape visual sensitivity (SVS) in historic districts, nor do they facilitate the operational linkage between assessment outcomes and planning applications. This study proposes an innovative SVS–PAP assessment methodology, which is a systematic integration of the SVS assessment and public esthetic perception (PAP) evaluation. The SVS assessment criteria framework was first improved through the integration of enriched multi-modal datasets. Subjective weights were obtained via the analytic hierarchy process (AHP), incorporating expert and public judgments, while objective weights were derived through the entropy weight method (EWM) based on data information entropy. The integration of both approaches enhances the methodological rigor and scientific validity of SVS weight determination. An SVS–PAP analytical matrix was subsequently constructed through integration of SVS assessments and PAP-based scenic beauty estimation (SBE), enabling the derivation of planning strategies. An empirical validation conducted in Anshandao Historic District yielded four key findings: (1) The SVS–PAP methodology, which integrates subjective–objective evaluation factors and incorporates broad public participation, demonstrates strong scientific validity and reliability, establishing a novel paradigm for SVS assessment and strategic planning; (2) The technical framework—leveraging multi-modal data and GIS spatial analysis techniques—improves assessment precision, operability, and replicability; (3) The planning and management strategies formulated by the SVS–PAP analytical matrix were verified as reasonable, demonstrating effective planning-transition capability; (4) Notably, historical and cultural influences showed significantly higher weighting coefficients across assessment criteria compared to non-historic streetscape assessments. Overall, these research results address the persistent undervaluation of the esthetic and spiritual values of historic landscapes in multi-resource value trade-off and decision-making processes, demonstrating both theoretical and practical significance through a systematic methodological advancement. Full article

Three-dimensional architectural greening (TAG) enables the integration of ecological, economic, and social advantages via the effective use of multidimensional space in a variety of forms, making it a significant method for enhancing spatial quality in densely populated cities. TAG technology has expanded the scope and capabilities of urban greening. It has the ability to provide green space, improve urban ecology and aesthetics, and alleviate the conflict between limited land resources and rising demand for greening throughout the urbanization process. Currently, there is a lack of a systematic assessment approach that focuses on the public’s visual perception of TAG. It is critical to focus on advances in visual perception approaches and create a “people-oriented perception driven” evaluation system that serves as a scientific foundation for urban three-dimensional greening initiatives. First, this study created a database of 300 TAG cases and selected classic cases using screening, classification, and sampling. Second, three experiments were set up for the study, including the use of the semantic differential (SD) method, and scenic beauty estimation (SBE) for subjective evaluation, and the eye-tracking experiment for objective evaluation. Finally, this study compared subjective and objective evaluations and demonstrated that both two approaches had a certain amount of accuracy. It also investigated the relationship between spatial features and public visual perceptions using methods such as factor and correlation analysis. The three effective methods for evaluating the quality of TAG based on visual perception that are presented in this study—two subjective and one objective—use standardized images, are quick and simple to use, and make up for the drawbacks of conventional strategies like indirectness, inefficiency, and time-consuming data collection. They also form a solid foundation for the real-world application of categorization prediction. In addition to being adaptable to a wide range of application settings, these two assessment paths—subjective evaluation and objective evaluation—can be integrated to complement one another and provide scientific references for future TAG designs and spatial decision making. Full article

Check dams play a pivotal role in soil and water conservation engineering as they mitigate debris flow and decelerate the slope of the river channel by intercepting sediments, thereby preventing disasters. However, as ecological conservation and landscape integration have become significant, functions, safety, harmony, and aesthetics with the surroundings must be considered in the design of check dams. In this study, a questionnaire survey was conducted based on scenic beauty estimation (SBE) and image segmentation using artificial intelligence to evaluate the landscape quality of soil and water conservation projects. Data were collected from the photos which were segmented into vegetation, structure, sky, land, and water. The proportion of each segment was calculated to explore the relationship with the scenic beauty of the landscapes. Regions with prevalent vegetation and water received favorable evaluations, whereas areas with a higher proportion of land were less preferred. Even when vegetation was present in high quantities, an unorganized arrangement was less desirable. Identified key factors influencing the scenic beauty of the landscape can be considered in the design of soil and water conservation engineering projects. Full article

Traditional villages, as repositories of cultural heritage and natural landscapes, have gained increasing prominence in the tourism industry. However, balancing authenticity preservation with visitor satisfaction remains a critical challenge. This study employs a combined Analytic Hierarchy Process (AHP)–Scenic Beauty Estimation (SBE) approach under the theoretical framework of 4E theory (Entertainment, Education, Aesthetics, and Escapism) to comprehensively evaluate visitor satisfaction in traditional village tourism landscapes. Eight nationally designated tourism-oriented traditional villages in Anhua County, China were selected as case studies. Findings from the AHP analysis reveal that aesthetic and escapism experiences are the most influential dimensions in shaping visitor satisfaction, while entertainment and educational experiences, though secondary, remain integral to a well-rounded tourism framework. The SBE evaluation corroborates these results, highlighting that seasonal characteristics, stress relief, and cultural landscape diversity significantly enhance visitor experiences. Conversely, deficiencies were observed in social interactivity, satisfaction with educational experiences, and fulfillment of aesthetic needs, indicating areas for improvement. A strong positive correlation between AHP and SBE scores (Pearson correlation coefficient = 0.867, p < 0.01) underscores the alignment between expert-driven evaluations and visitor perceptions. These insights suggest that integrating expert-based hierarchical analysis with empirical visitor assessments provides a more robust and multidimensional framework for sustainable tourism management. Recommendations include enhancing social interactivity, optimizing educational components, enriching aesthetic experiences, and ensuring the preservation of vernacular landscapes to foster sustainable, experience-driven rural tourism development. Full article

Pocket parks are small green spaces that significantly enhance urban livability, particularly in densely populated cities. To leverage this advantage, Chongqing has committed to establishing 100 pocket parks by 2024. This study assesses the landscape quality of six pocket parks in Chongqing’s Dadukou District, employing Scenic Beauty Estimation (SBE) and Analytic Hierarchy Process (AHP). The results of the SBE method identify four main factors—spatial hierarchy, plant diversity, landscape harmony, and color richness—that show a strong correlation with scenic beauty (R = 0.947, R² = 0.897). AHP analysis reveals that landscape function is the dominant criterion, accounting for 66.86% of the total weight, with ecological function and service function contributing 21.44% and 8.82%, respectively. Notably, plant color richness emerges as the most significant factor, with a comprehensive weight of 0.1509, emphasizing its critical role in enhancing visual appeal. Based on these findings, this study recommends increasing plant diversity, optimizing color design to improve visual appeal, and implementing sustainable, low-maintenance strategies. This research integrates both quantitative and qualitative approaches, offering strategies to refine pocket park designs and establish a framework to enhance green spaces in densely populated urban areas, not only in China but potentially globally, promoting environmental sustainability and user satisfaction. 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

This investigation delves into the waterfront plant landscapes of traditional villages in Western Hunan, China, aiming to bolster sustainable ecological resource management, amplify ecological culture, and ameliorate environmental standards. Furthermore, it endeavors to furnish a theoretical scaffold for the meticulous construction and assessment of these landscapes. This study has illustrated the waterfront botanical landscapes of 32 traditional hamlets within the Xiangxi region, integrating prior research on the waterfront botanical regression model based on the Scenic Beauty Estimation (SBE) method. It established and investigated fifteen landscape factors pivotal to the aesthetic valorization of these village waterfronts. The study concocted a beauty quality evaluation model, unearthing a significant correlation (p < 0.01) across evaluations by students majoring in landscape architecture, expert landscape architects, and laypersons, thus underscoring a consensus in aesthetic judgments. A noteworthy correlation between the beauty value (Z-value) and the entropy weight value was elucidated through the equation EWM = −0.106 + 0.425ZSBE, showcasing the landscape quality’s variance among the studied villages. The formulated evaluation model accentuates the significance of seasonal variation, scale affinity, and a rich hierarchical structure. Full article

Walking exercise is a prevalent physical activity in urban areas, with streetscapes playing a significant role in shaping preferences. Understanding this influence is essential for creating urban environments conducive to walking exercise and improving residents’ quality of life. In this study, we utilize scenic beauty estimation and deep learning methods, leveraging street view images and walking exercise trajectories to analyze this influence from a human-centric perspective. We begin by generating sampling points along streets covered by trajectories and acquiring street view images. Subsequently, we apply a deep learning model to segment the images, yielding six visual indicators. Additionally, we use scenic beauty estimation to derive the seventh visual indicator. Finally, we match these indicators with trajectory data to implement preference analysis. The main findings are: (1) preferences for walking and running exercises differ on multiple indicators; (2) there are gender distinctions, with males preferring openness and females prioritizing enclosed spaces; (3) age plays a role, with those aged 30–40 preferring openness and those aged 40–50 preferring enclosed spaces; (4) preferences for different indicators vary over time and across different locations. These insights can inform policymakers in tailoring urban planning and design to specific population segments and promoting sustainable residential landscapes. Full article

Contemporary landscape architecture studies have paid close attention to the interactions between public aesthetic preferences and the landscape environment. Scenic beauty has become an important evaluation indicator of landscape quality. The quality of the plant color landscape is an important factor affecting scenic beauty. Exploring the relationship between the composition rules and internal properties of autumn plant color landscapes in urban parks and public aesthetic preferences can provide new ideas for the evaluation and design of plant community color landscapes. Taking 12 parks in Changsha City, Hunan Province, China, as the study area and 85 plant communities as the sample plots, scenic beauty estimation (SBE) was used to evaluate the autumn plant color landscape of urban parks. ColorImpact software was used to extract the color values of each plant community. Fifteen original color element indicators were determined, and the data were statistically analyzed by principal component analysis (PCA), one-way ANOVA, multiple comparison analysis and systematic cluster analysis. Four principal components were extracted to construct the characteristic indices and a comprehensive model of the color landscape quality of autumn plant communities. The four characteristic indices showed significant or extremely significant differences among the five SBE grades. From the overall trend, the SBE grades showed a positive correlation with PC1 (primary and adjunctive color index), PC2 (color structure and property index) and PC3 (autumn-color-leafed index) and a negative correlation with PC4 (intersperse color index). R_PH (ratio of primary hue), R_P (ratio of primary color), R_C (color-leafed index), R_WC (ratio of warm and cool colors), and N_C (number of colors) were the key factors affecting the SBE grade. Overall, R_PH, R_P, R_C, and R_WC positively influenced the SBE values, while N_C negatively influenced the SBE values, and five to seven colors were more moderate. The quality of the color landscape can be improved by creating plant communities with three types of color composition: warm-toned dominant type, warm- and cold-toned contrast type, and multicolor harmonic type. The results provide a reference for the evaluation, design and construction of autumn plant color landscapes in urban parks. Full article