Spatial Patterns and Multi-Dimensional Impact Analysis of Urban Street Quality Perception under Multi-Source Data: A Case Study of Wuchang District in Wuhan, China

Li, Tianyue; Xu, Hong; Sun, Haozun

doi:10.3390/app132111740

Cited by 3 publications

(2 citation statements)

References 55 publications

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“…The street furniture and public activity space in the scene play a decorative role, corresponding to the environmental facility elements. The street business feature elements constitute the diverse functional connotations of the scene [32,46,48,56].…”

Section: Methodsmentioning

confidence: 99%

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A Study on Identifying the Spatial Characteristic Factors of Traditional Streets Based on Visitor Perception: Yuanjia Village, Shaanxi Province

Liu,

Li,

Tian

et al. 2024

Buildings

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The street spaces in tourist-oriented traditional villages served both the daily lives of villagers and the leisure activities of tourists. However, due to insufficient understanding of the spatial characteristics and under-exploration of spatial genes, these spaces often suffered from homogenization during tourism development. Thus, identifying the characteristics and connotations of such streets, understanding the relationship between tourists’ perceptions and built environment elements, and developing optimization strategies for these rural street spaces were urgent issues. Many studies have evaluated street space characteristics from tourists’ behavior, but few have focused on rural areas. Especially, research combining new technologies like artificial intelligence to study the psychological perceptions of tourists is still in its infancy. This study used a typical traditional village as a case study and applied the YOLOv5 deep-learning model to build a perception evaluation system based on three dimensions: tourists’ aggregation degree, stay time, and facial expressions. The study conducted a multivariate regression analysis on 21 factors across 4 aspects: street scale morphology, environmental facilities, ground-floor interface, and street business types. Results indicated that the functional business type of the scene had the greatest impact on tourists’ perception of the street space environment, followed by ground-floor features and environmental facilities. The regression coefficient for business in situ values and spatial perception was 0.47, highlighting it as a key factor influencing characteristic perception. Landscape water systems, flat ground-floor façades, and business diversity also positively affected tourists’ perception. This study utilized advanced techniques like the YOLOv5 model, known for its speed and accuracy, to scientifically analyze tourists’ behavior and perceptions, serving as feedback and evaluation for the village’s built environment. Empirical analysis of Yuanjia Village validated the effectiveness of the multidimensional approach and spatial gene theory. Ultimately, this method identified 12 street characteristic factors significantly affecting tourists’ perceptions. The uniqueness of this study lies in its comprehensive approach, combining empirical research, spatial gene theory, and advanced object detection technology, providing new insights for village spatial planning and construction.

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Section: Methodsmentioning

confidence: 99%

“…They collected different perception scores of streets and lanes. They analyzed the spatial patterns of spatial quality perception of urban streets through global Moran's I and GIS hotspot analysis [46]. Fang Zhiguo et al conducted an association study of Shanghai streets using crowd visual perception [47].…”

Section: Measures Of Pedestrian Perceptionmentioning

confidence: 99%

A Study on Identifying the Spatial Characteristic Factors of Traditional Streets Based on Visitor Perception: Yuanjia Village, Shaanxi Province

Liu,

Li,

Tian

et al. 2024

Buildings

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Transformation of Modern Urban Park Based on User’s Spatial Perceived Preferences: A Case Study of Kowloon Walled City Park in Hong Kong

Di,

Chen,

Ren

et al. 2024

Forests

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Urban parks enhance residents’ quality of life and health by fostering a harmonious relationship between people and nature, so effective park design needs to prioritize ecological protection, sustainable landscapes, and practical spatial structures to achieve these benefits. This study takes the typical case of urban park renovation and reconstruction—Kowloon Walled City Park—as an example to conduct research and divides the interior of the park into four types of areas: contemporary built-up area; historical relic area; natural–folk custom area; and ecological conservation area. Based on 405 valid questionnaire data for respondents, this study conducts empirical research using a combination of the Semantic Differential (SD) method, Importance Performance Analysis (IPA) model, and unordered multivariate logit choice model, comprehensively describes and analyzes individual spatial perception and preferences, and further discusses the potential factors affecting individual perception preferences. The results show that there are differences in many characteristics between different areas in Kowloon Walled City Park. At the same time, people generally prefer park areas that integrate modern and traditional elements, natural and cultural environments, and pay attention to the balance between naturalness and sociality in park design. These results provide useful information for planners, developers, and others, as well as data for designing urban park construction with higher practical value and natural benefits.

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Advanced Integration of Urban Street Greenery and Pedestrian Flow: A Multidimensional Analysis in Chengdu’s Central Urban District

Ma,

Zhang,

2024

IJGI

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As urbanization accelerates, urban greenery, particularly street greenery, emerges as a vital strategy for enhancing residents’ quality of life, demanding attention for its alignment with pedestrian flows to foster sustainable urban development and ensure urban dwellers’ wellbeing. The advent of diverse urban data has significantly advanced this area of study. Focusing on Chengdu’s central urban district, this research assesses street greening metrics against pedestrian flow indicators, employing spatial autocorrelation techniques to investigate the interplay between street greenery and pedestrian flow over time and space. Our findings reveal a prevalent negative spatial autocorrelation between street greenery and pedestrian flow within the area, underscored by temporal disparities in greenery demands across various urban functions during weekdays versus weekends. This study innovatively incorporates mobile phone signal-based population heat maps into the mismatch analysis of street greenery for the first time, moving beyond the conventional static approach of space syntax topology in assessing pedestrian flow. By leveraging dynamic pedestrian flow data, it enriches our understanding of the disconnect between street greening plans and pedestrian circulation, highlighting the concept of urban flow and delving into the intricate nexus among time, space, and human activity. Moreover, this study meticulously examines multiple street usage scenarios, reflecting diverse behavior patterns, with the objective of providing nuanced and actionable strategies for urban renewal initiatives aimed at creating more inviting and sustainable urban habitats.

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Spatial Patterns and Multi-Dimensional Impact Analysis of Urban Street Quality Perception under Multi-Source Data: A Case Study of Wuchang District in Wuhan, China

Cited by 3 publications

References 55 publications

A Study on Identifying the Spatial Characteristic Factors of Traditional Streets Based on Visitor Perception: Yuanjia Village, Shaanxi Province

A Study on Identifying the Spatial Characteristic Factors of Traditional Streets Based on Visitor Perception: Yuanjia Village, Shaanxi Province

Transformation of Modern Urban Park Based on User’s Spatial Perceived Preferences: A Case Study of Kowloon Walled City Park in Hong Kong

Advanced Integration of Urban Street Greenery and Pedestrian Flow: A Multidimensional Analysis in Chengdu’s Central Urban District

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