Measuring the perceptual features of coastal streets: a case study in Qingdao, China

Lyu, Mei; Meng, Yumeng; Gao, Weijun; Yu, Yang; Ji, Xiang; Li, Qingyu; Huang, Gonghu; Sun, Dong

doi:10.1088/2515-7620/ac9515

Cited by 9 publications

(7 citation statements)

References 82 publications

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“…In other words, women believe that new towns with high street openness are more imageable, while men believe the opposite. Lower openness of the sky generally leads to higher enclosure scores [89,93], and our findings support it more specifically. The effect of the sky on women's enclosure is significantly higher than other features, and it has a negative impact combined with the results in Sections 4.2 and 4.3.…”

Section: Gender Differences Of Influence Factors In New Townssupporting

confidence: 81%

Walkability Perceptions and Gender Differences in Urban Fringe New Towns: A Case Study of Shanghai

Wenjing

Huang

White

et al. 2023

Land

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Urban fringe areas, characterized by relatively larger community sizes and lower population densities compared to central areas, may lead to variations in walkability as well as gender differences, such as safety perception. While objective measurements have received considerable attention, further research is needed to comprehensively assess subjective perceptions of walking in the urban periphery. As a case study, we evaluated survey responses of community perceptions of “Imageability”, “Enclosure”, “Human scale”, “Complexity” and “Safety” of Shanghai’s five new towns, comparing these with responses from the central area in terms of gender difference, and analyzed influencing factors and prediction performance of machine learning (ML) models. We developed a TrueSkill-based rating system to dynamically collect audits of street view images (SVIs) from professional students and used the result to integrate with Geographic Information Systems (GIS), Computer Vision (CV), Clustering analysis, and ML algorithm for further investigation. Results show that most of the new towns’ communities are perceived as moderately walkable or higher, with the city center’s community exhibiting the best walkability perceptions in general. Male and female perceptions of the “Human scale” and the factors that affect it differ little, but there are significant disparities in the other four perceptions. The best-performing ML models were effective at variable explanations and generalizations, with Random Forest Regression (RFR) performing better on more perception predictions. Responses also suggest that certain street design factors, such as street openness, can positively influence walkability perceptions of women and could be prioritized in new town development and urban renewal for more inclusive and walkable cities.

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Section: Gender Differences Of Influence Factors In New Townssupporting

confidence: 81%

Walkability Perceptions and Gender Differences in Urban Fringe New Towns: A Case Study of Shanghai

Wenjing

Huang

White

et al. 2023

Land

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“…The SD method, also known as the semantic differential method, was proposed by Osgood in 1957 (Osgood et al 1957). The SD method has been widely used in environment evaluation studies due to its better applicability (Sun et al 2021, Lyu et al 2022. The evaluation process of SD method usually involoves 20 to 50 observers who need a certain amount of professional knowledge.…”

Section: The Evaluation Of Viwpmentioning

confidence: 99%

Using google street view panoramas to investigate the influence of urban coastal street environment on visual walkability

Huang

Lyu

et al. 2023

Environ. Res. Commun.

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Urban street walkability can effectively promote public health and the construction of livable cities. In addition, the coastal streets play a positive role in showing urban vitality and image. Due to the growing leisure needs of residents, measuring the visual walkability perception (VIWP) in urban streets and exploring the influence mechanisms of urban coastal street environments on VIWP have theoretical and practical significance. However, the methods of the previous walkability studies have limitations in terms of cost, time and measurement scale. Based on Google Street View Panoramic (GSVP) image data, this study used the semantic difference (SD) method with virtual reality (VR) technology to evaluate the VIWP of Fukuoka coastal streets. Meanwhile, the proportion of streetscape elements was extracted from GSVP images by semantic segmentation. The correlation and regression analyses were performed between the VIWP evaluation values and streetscape elements. Then, the regression model of the VIWP and the streetscape elements was established. The results showed that the natural features had a positive influence on VIWP in coastal streets. Correspondingly, trees were the strongest contribution rate for the VIWP, followed by shrubs, grasses and water, however, buildings and cars had a negative influence on VIWP. The method extends previous studies for measuring walkability, and optimization strategies were proposed to improve the visual quality of the coastal streets. It can be applied in the construction and management of walkable coastal street environments.

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“…In housing research, it is crucial to explore the relationship between socioeconomic environments and human settlement. Bin et al (2020), Chen et al (2020), Fu et al (2019), Kang, Stice-Lawrence, and Wong (2021), Law et al (2019), Li et al (2021), Lyu et al (2022), Wang (2023), Wu et al (2022), Xu et al (2022), Yao et al (2018) and Ye et al (2019) utilised street views to estimate housing prices and proposed a neural networks-based methodology to address the issues that the economists had to manually categorise each view in the past and providing new insights into the assessment of human settlement values. Meanwhile, Johnson et al (2020), Kostic and Jevremovic (2020) and Qiu et al (2022) found that houses with better street or property design come at a price premium, meaning that proposed methods can efficiently describe visible characteristics.…”

Section: Review and Applicationsmentioning

confidence: 99%

Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences

Wang

2023

Social Science Computer Review

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Street views, satellite imageries and remote sensing data have been integrated into a wide spectrum of topics in the social sciences. Computer vision methods not only help analysts and policymakers make better decisions and produce more effective solutions but they also enable models to achieve more precise predictions and greater interpretability. In this paper, we review the growing literature applying such methods to economic issues and the social sciences, in which social scientists employ deep learning approaches to utilise image data to retrieve additional information. Typically, image data produce better results than traditional approaches and can provide detailed results and helpful insights to improve society and people’s well-being.

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Measuring the perceptual features of coastal streets: a case study in Qingdao, China

Cited by 9 publications

References 82 publications

Walkability Perceptions and Gender Differences in Urban Fringe New Towns: A Case Study of Shanghai

Walkability Perceptions and Gender Differences in Urban Fringe New Towns: A Case Study of Shanghai

Using google street view panoramas to investigate the influence of urban coastal street environment on visual walkability

Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences

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