4.7 Review

A review on street view observations in support of the sustainable development goals

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Article Environmental Studies

How are Neighborhood and Street-Level Walkability Factors Associated with Walking Behaviors? A Big Data Approach Using Street View Images

Bon Woo Koo et al.

Summary: This paper explores the correlation between street-level factors and neighborhood-level factors in relation to walkability by using computer vision techniques to analyze street view images in Atlanta, Georgia. The results suggest that street-level factors can significantly impact walking mode choices and may serve as proxies for macroscale factors, providing a different perspective on pedestrian experiences.

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Article Environmental Sciences

Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City

Eun-Hye Yoo et al.

Summary: This study found significant associations between green space exposure (both proximity and visibility) and total ER visits for mental disorders in neighborhoods with high social vulnerability, but no significant associations in neighborhoods with low social vulnerability. Specific neighborhoods with particularly high utilization of ER visits for mental disorders were also identified.

ENVIRONMENTAL RESEARCH (2022)

Article Public, Environmental & Occupational Health

Understanding the role of urban social and physical environment in opioid overdose events using found geospatial data

Yuchen Li et al.

Summary: Opioid use disorder is a serious public health crisis in the United States, and social and economic conditions are major factors contributing to the variations in opioid overdose events (OOEs). This study explores the use of non-traditional geospatial data, such as Google Street View images and non-emergency service requests, as indicators of social and physical conditions in community neighborhoods. The findings reveal positive associations between community disorder indicators and OOEs, while perceived safety, wealth, and liveliness measures from street view imagery are negatively associated with the risk of OOEs. The results suggest that social inequality and distress contribute to the opioid epidemic crisis.

HEALTH & PLACE (2022)

Article Urban Studies

Urban greenery mitigates the negative effect of urban density on older adults' life satisfaction: Evidence from Shanghai, China

Dongsheng He et al.

Summary: The influence of high-density environment on urban residents is controversial, but urban greenery may mitigate the detrimental effects of crowded environments on quality of life. This study examined the complex relationship between urban density, urban greenery, and older people's life satisfaction, using survey data collected from 1,594 older adults in 129 neighborhoods in Shanghai, China. The results showed that higher urban density was related to lower life satisfaction, and a reduced sense of community was a significant pathway between higher urban density and lower life satisfaction. Furthermore, eye-level greenery cushioned the negative effect of urban density on life satisfaction.

CITIES (2022)

Article Environmental Studies

How does street space influence crash frequency? An analysis using segmented street view imagery

Jonathan Stiles et al.

Summary: Preventing road crashes in metropolitan areas is challenging due to the complex interactions between drivers and other system users in built environments. Recent research suggests that the features of the built environment can influence unsafe driving by shaping users' expectations and behaviors.

ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE (2022)

Article Development Studies

Sustainable built environment for facilitating public health of older adults: Evidence from Hong Kong

Shuangzhou Chen et al.

Summary: This study investigates the non-linear relationships between the built environment and older adults' functional capability and discovers that specific factors in the built environment have a positive impact on the functional capability of older adults. This is valuable for relevant stakeholders and policymakers in developing age-friendly urban planning.

SUSTAINABLE DEVELOPMENT (2022)

Article Remote Sensing

Impacts of perceived safety and beauty of park environments on time spent in parks: Examining the potential of street view imagery and phone-based GPS data

Hanlin Zhou et al.

Summary: Research shows that urban parks have positive effects on human health. By utilizing Google Street View imagery and cellphone GPS data, researchers can measure perceptions of park environments and the time people spend in parks. The research reveals a positive association between perceived safety and beauty of park environments and increased time spent in parks, with the addition of perception variables improving the model performance. This is important for urban planners to design better park environments and enhance park usage.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2022)

Article Remote Sensing

Mapping individual abandoned houses across cities by integrating VHR remote sensing and street view imagery

Shengyuan Zou et al.

Summary: This study aims to map individual-level abandoned houses in urban areas using high-resolution remote sensing and Google Street View (GSV) images. The proposed method involves four steps, including validating the feasibility of three relevant remote sensing data, extracting discriminative features, applying decision-level fusion, and using a geographical random forests (GRF) model for improved predictions on GSV images. The results demonstrate the effectiveness and potential of this method in tackling the challenges of housing abandonment in shrinking cities.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2022)

Article Environmental Studies

Quantifying physical and psychological perceptions of urban scenes using deep learning

Yonglin Zhang et al.

Summary: This study explores the impact of urban landscapes on public perceptions by quantifying psychological and physical perceptions. The research finds that natural landscapes in Beijing's built-up area have a positive influence on psychological perceptions, while industrial landscapes exhibit negative feelings. The framework in the paper has the potential to assist urban planning and land-use management, improving residents' perceptions of urban scenes.

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Article Environmental Sciences

Modelling and mapping eye-level greenness visibility exposure using multi-source data at high spatial resolutions

S. M. Labib et al.

Summary: A new method was developed to model and map eye-level greenness visibility exposure for ground observers, using viewshed analysis and distance decay model to compute a novel VGVI.

SCIENCE OF THE TOTAL ENVIRONMENT (2021)

Article Environmental Sciences

A human-centred assessment framework to prioritise heat mitigation efforts for active travel at city scale

Qian (Chayn) Sun et al.

Summary: This study presents a new method for comprehensive assessment of urban heat environment, community vulnerability to heat effects, and implementation of heat mitigation interventions, using data-driven research with multiple spatial data sources, providing value for urban planning and community improvement.

SCIENCE OF THE TOTAL ENVIRONMENT (2021)

Article Construction & Building Technology

Modeling pedestrian emotion in high-density cities using visual exposure and machine learning: Tracking real-time physiology and psychology in Hong Kong

Luyao Xiang et al.

Summary: This study used machine learning to model pedestrian emotions in high-density urban areas of Hong Kong, finding that exposure to more trees, visual volume, and drift magnitude can lead to positive emotions, while views containing sign symbols, object proportion, min-radial, and occlusivity can lead to negative emotions. The predictive model explained 79% of the spatial variance of pedestrian emotion, providing opportunities for data-driven approaches in urban planning research.

BUILDING AND ENVIRONMENT (2021)

Article Engineering, Environmental

Spatiotemporal Characteristics and Driving Factors of Black Carbon in Augsburg, Germany: Combination of Mobile Monitoring and Street View Images

Xiansheng Liu et al.

Summary: The study investigated the spatial pattern of black carbon (BC) in Augsburg, Germany, showing significant spatial heterogeneity and diurnal variations related to traffic density. Meteorological factors and street microenvironments have influences on BC concentration. Models based on street view images and meteorological data provide good explanations for the variability of BC concentrations, particularly for UVPM and eBC.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2021)

Article Geography, Physical

Exploring Google Street View with deep learning for crop type mapping

Yulin Yan et al.

Summary: In this study, a convolutional neural network (CNN) model was applied to investigate the effectiveness of automatic ground truthing using Google Street View (GSV) images in two distinct farming regions: Illinois and the Central Valley in California. The study demonstrated the feasibility and reliability of this new ground referencing technique, showing high classification accuracy for crop mapping at the state level. These results suggest that GSV images with deep learning models offer an efficient and cost-effective alternative method for ground referencing in various regions worldwide.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2021)

Article Environmental Sciences

Are greenspace quantity and quality associated with mental health through different mechanisms in Guangzhou, China: A comparison study using street view data

Ruoyu Wang et al.

Summary: This study found that the quality of greenspace may be more important for mental health than the quantity, with quality influencing mental health through restoring and building capacities, while quantity influences mental health through reducing harm from pollution. The mechanisms through which greenspace exposure influences mental health may vary across different exposure assessment strategies.

ENVIRONMENTAL POLLUTION (2021)

Article Ecology

Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning

Donghwan Ki et al.

Summary: Previous research has shown limitations in traditional methods of measuring urban greenery, and found a closer association between GVI and walking time. Additionally, low-income residents tend to live in neighborhoods with low GVI, but walking time is more sensitive to GVI.

LANDSCAPE AND URBAN PLANNING (2021)

Article Public, Environmental & Occupational Health

Leveraging 31 Million Google Street View Images to Characterize Built Environments and Examine County Health Outcomes

Quynh C. Nguyen et al.

Summary: This study utilized big data sources and computer vision technology to analyze the associations between built environment features and health outcomes in 2916 US counties. The findings showed that counties with more crosswalks were associated with lower adult obesity, physical inactivity, and poor self-rated health, highlighting the importance of pedestrian-friendly built environments in promoting better public health.

PUBLIC HEALTH REPORTS (2021)

Article Geography, Physical

Automatic large scale detection of red palm weevil infestation using street view images

Dima Kagan et al.

Summary: A novel method for surveillance of Red Palm Weevil infested palm trees using deep learning algorithms and aerial/street-level imagery has been proposed, demonstrating efficiency in detecting infested trees in urban and open environments through large-scale testing.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2021)

Article Environmental Sciences

Assessing the Impact of Street-View Greenery on Fear of Neighborhood Crime in Guangzhou, China

Fengrui Jing et al.

Summary: The study found that increasing street-view greenery can reduce fear of crime in the neighborhood, a relationship that is mediated by perceived physical incivilities. Therefore, social factors should be taken into consideration when designing ameliorative programs.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2021)

Article Construction & Building Technology

Machine learning-based regional scale intelligent modeling of building information for natural hazard risk management

Chaofeng Wang et al.

Summary: This paper presents a framework for regional scale building information generation or gathering to support regional hazard analysis. Different types of data are acquired from multiple sources and fused to semantically profile each building in a city. The framework utilizes deep learning techniques and a data mining tool to overcome data scarcity issues and quantify uncertainty to create building inventories for disaster and risk management planning.

AUTOMATION IN CONSTRUCTION (2021)

Article Ecology

Predicting perceptions of the built environment using GIS, satellite and street view image approaches

Andrew Larkin et al.

Summary: This study examined built environment factors associated with safety, lively, and beauty perceptions, finding significant differences in factors such as population density, impervious surface area, major roads, and more between high and low perception locations. Visible street level features explained about 18% of the variation in perceptions, while GIS/remote sensing variables explained 3-10%.

LANDSCAPE AND URBAN PLANNING (2021)

Article Ecology

Dynamic greenspace exposure and residents' mental health in Guangzhou, China: From over-head to eye-level perspective, from quantity to quality

Ruoyu Wang et al.

Summary: The study found that eye-level greenspace quality is closely related to residents' mental health, emphasizing the importance for policymakers and planners to consider in urban planning and development.

LANDSCAPE AND URBAN PLANNING (2021)

Article Engineering, Environmental

Using Street View Imagery to Predict Street-Level Particulate Air Pollution

Meng Qi et al.

Summary: By leveraging Google Street View imagery and deep learning models, we developed LUR models for predicting street-level particulate air pollution, achieving higher spatial resolution and better performance compared to traditional LUR models.

ENVIRONMENTAL SCIENCE & TECHNOLOGY (2021)

Article Ecology

Perception bias: Deciphering a mismatch between urban crime and perception of safety

Fan Zhang et al.

Summary: This study quantitatively examines the relationship between the perception of safety and crime rates in urban areas by inferring safety scores from Google Street View images. The results suggest a paradoxical association between characteristics of urban space and perception bias over crime, with neighborhoods experiencing daytime and nighttime visitors showing different safety perceptions. The findings contribute to our understanding of the built environment's impact on crime and highlight the importance of considering perception bias in urban management strategies.

LANDSCAPE AND URBAN PLANNING (2021)

Article Environmental Sciences

Google Street View-Derived Neighborhood Characteristics in California Associated with Coronary Heart Disease, Hypertension, Diabetes

Thu T. Nguyen et al.

Summary: The characteristics of the neighborhood built environment have an impact on health outcomes and behaviors. Research has shown that communities with higher levels of greenery have lower prevalence of coronary artery disease, hypertension, and diabetes, while visible utility wires and dilapidated buildings are associated with higher rates of these chronic diseases. Google Street View images and computer vision models can provide insights into contextual factors influencing patient health outcomes.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2021)

Article Urban Studies

Human settlement value assessment from a place perspective: Considering human dynamics and perceptions in house price modeling

Yuhao Kang et al.

Summary: The value of house settlement is influenced by spatial settings, cultures, human dynamics, human perceptions, and social interactions. Introducing a place-oriented hedonic pricing model that incorporates human dynamics and perceptions can provide better insights into human settlement values. The impact of place-related variables on house prices is stable across space, as shown by geographically weighted regression analysis and Monte Carlo test.

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Article Environmental Sciences

Street view greenness is associated with lower risk of obesity in adults: Findings from the 33 Chinese community health study

Xiang Xiao et al.

Summary: This study found beneficial associations between community-level street view greenness and lower body weight in Chinese adults, with greater effects observed in women. Air pollution may partially mediate this association.

ENVIRONMENTAL RESEARCH (2021)

Article Ecology

Discovering the homogeneous geographic domain of human perceptions from street view images

Yao Yao et al.

Summary: This study uses street view images to analyze human perceptions of urban areas and proposes a novel method to discover homogeneous geographic domains of human perception. By constructing perception network models and using the Infomap community detection algorithm, the study successfully identifies homogeneous perception communities.

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Article Plant Sciences

Perceived influence of street-level visible greenness exposure in the work and residential environment on life satisfaction: Evidence from Beijing, China

Wenjie Wu et al.

Summary: The study found that street-level visible greenness exposure is positively associated with life satisfaction, but the effect decreases after considering greenness exposure at work locations. Stratified analysis revealed that different demographic and socioeconomic groups benefit differently from SVG exposure.

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Residential greenness, air pollution and psychological well-being among urban residents in Guangzhou, China

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Street-Frontage-Net: urban image classification using deep convolutional neural networks

Stephen Law et al.

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