Article
Ecology
Jiakun Liu, Dick Ettema, Marco Helbich
Summary: This study investigates the associations between street view (SV) environmental features and pedestrians' walking duration in Amsterdam. Results indicate that associations differ between weekdays and weekends, with factors such as individual standing walls and address density influencing weekday walking, while factors such as street greenery, car presence, address density, land-use diversity, and distance to train stations affecting weekend walking. These findings suggest that SV environmental features can complement traditional built environmental measures in explaining pedestrian mobility.
LANDSCAPE AND URBAN PLANNING
(2023)
Article
Environmental Sciences
Dongxin Wen, Maochou Liu, Zhaowu Yu
Summary: With the unprecedented urbanization processes, cities have become the main areas of political, cultural, and economic creation. However, they have also caused environmental degradation and public health issues. This study proposed a framework to quantify the quality of urban road landscape and explored its spatial heterogeneity. A case study in Xiamen Island showed that there were variations in streetscape quality, and vertical greening was suggested to improve street quality.
Article
Public, Environmental & Occupational Health
Xin Han, Lei Wang, Seong Hyeok Seo, Jie He, Taeyeol Jung
Summary: The urban built environment has a significant impact on the psychological stress of residents. This study proposes a rapid and large-scale method to measure the perceived psychological stress of urban residents using big data and deep learning technology. The empirical study conducted in Gangnam District, Seoul, shows that urban traffic arteries and riverine areas have lower psychological stress, while commercial and residential areas have higher psychological stress. Walls and buildings cause psychological stress, while sky, trees, and roads relieve it.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Computer Science, Interdisciplinary Applications
Tianhong Zhao, Xiucheng Liang, Wei Tu, Zhengdong Huang, Filip Biljecki
Summary: Based on machine learning, a new application of street view imagery is introduced to estimate large-area high-resolution urban soundscapes. This approach enables low-cost but accurate and detailed sensing of urban soundscapes, providing an alternative means to generate soundscape maps.
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
(2023)
Article
Energy & Fuels
Markus Rosenfelder, Moritz Wussow, Gunther Gust, Roger Cremades, Dirk Neumann
Summary: Reducing the electricity consumption of buildings through modeling based on aerial and street view images is an effective approach in predicting energy consumption and outperforms traditional models. The innovative method presented in the study is significant in addressing the lack of building electricity consumption data.
Article
Construction & Building Technology
Yuqi Han, Teng Zhong, Anthony G. O. Yeh, Xiuming Zhong, Min Chen, Guonian Lu
Summary: This study aims to quantitatively characterize seasonal differences in street greenery based on multi-temporal street-view images. The results revealed significant seasonal differences in street greenery in the Gulou District and classified four street greening patterns. The proposed framework could assist in future sustainable greening design and planning.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Transportation Science & Technology
Koichi Ito, Filip Biljecki
Summary: The study evaluates urban bikeability comprehensively using street view imagery and computer vision, developing a comprehensive index composed of 34 indicators. The results show that street view imagery and computer vision are effective in assessing urban bikeability and have the potential to replace traditional techniques. However, combining street view imagery and non-street view imagery approaches may be the best way forward for future development.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Environmental Sciences
Marcia P. Jimenez, Esra Suel, Sheryl L. Rifas-Shiman, Perry Hystad, Andrew Larkin, Steve Hankey, Allan C. Just, Susan Redline, Emily Oken, Peter James
Summary: The study found associations between street view imagery (SVI)-based greenspace in childhood and early adolescence sleep, particularly with sleep duration and time awake after sleep onset. Differences in greenspace-sleep associations were observed among racial and socioeconomic subgroups.
ENVIRONMENTAL RESEARCH
(2022)
Article
Environmental Studies
Huan Ning, Xinyue Ye, Zhihui Chen, Tao Liu, Tianzhi Cao
Summary: A reliable dataset of sidewalks is essential for enhancing multi-modal accessibility and social cohesion in urban environments. This paper proposes a new spatial procedure to extract sidewalks by integrating detected results from aerial and street view imagery, achieving a complete sidewalk network.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2022)
Article
Urban Studies
Shuting Chen, Filip Biljecki
Summary: Public open space (POS) is important for urban areas, but assessing them can be tedious. This research introduces a new approach of using Street View Imagery (SVI) and Computer Vision (CV) in conjunction with geospatial and remote sensing data to automate and extend POS assessment. Subjective and objective indicators are developed, and CV algorithms are used for visual feature retrieval. A case study in Hong Kong and Singapore shows that SVI can be used for POS assessment with high accuracy, reflecting different aspects compared to previous approaches.
Article
Economics
Sohee Kim, Ayoung Woo
Summary: This study investigates the impact of walkability on the survival of restaurant businesses, particularly in commercial areas. The study finds that streetscapes play a key role in increasing the survival rate of restaurants in commercial areas. This research provides valuable insights for policymakers to develop tailored approaches to revitalize the economies of local commercial areas.
JOURNAL OF TRANSPORT GEOGRAPHY
(2022)
Review
Ecology
Filip Biljecki, Koichi Ito
Summary: Street view imagery has become an integral component of urban analytics and GIScience, with applications ranging from analyzing vegetation and transportation to health and socio-economic studies. Most research currently relies on data from Google Street View. A notable trend is the use of crowdsourced street view imagery to enhance geographical coverage and temporal granularity in some cases.
LANDSCAPE AND URBAN PLANNING
(2021)
Article
Environmental Sciences
Teng Zhong, Cheng Ye, Zian Wang, Guoan Tang, Wei Zhang, Yu Ye
Summary: This study proposes a deep learning-based approach for mapping urban facade color, with a case study in Shenzhen demonstrating high accuracy in extracting urban facade color. Insights into mapping urban facade color from a humanistic perspective could improve urban space planning and design quality.
Article
Environmental Sciences
Chenbo Zhao, Yoshiki Ogawa, Shenglong Chen, Takuya Oki, Yoshihide Sekimoto
Summary: Estimating people flow trend is crucial for traffic and urban safety planning and management. Privacy concerns make it difficult to collect individual location data for statistical analysis, so an alternative approach is needed. This study proposes an end-to-end deep-learning approach that combines street view images and subjective scores to estimate and analyze people flow in different time and movement patterns. The study achieved 78% accuracy on the test set and provides insights into the relationship between streetscape, human subjective feeling, and people flow trend.
Article
Computer Science, Information Systems
Jing Huang, Teng Fei, Yuhao Kang, Jun Li, Ziyu Liu, Guofeng Wu
Summary: This paper proposes a data-driven approach for measuring road traffic noise using street view imagery. By capturing in-situ noise and utilizing a deep learning model, it is possible to quantitatively estimate the noise levels for different road segments. Additionally, a gradient-weighted Class Active Mapping approach is employed to interpret and visualize the results of the deep learning model.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
Editorial Material
Public, Environmental & Occupational Health
Linchuan Yang, Ruoyu Wang, Baojie He, Yu Ye, Yibin Ao
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Environmental Studies
Yuyang Wu, Yao Yao, Shuliang Ren, Shiyi Zhang, Qingfeng Guan
Summary: Social segregation hinders urban development and is a hot topic in urban research. This study used mobile phone datasets and housing price data to divide city dwellers into different socioeconomic levels, and analyzed the impact of urban service facilities on social segregation using geographically weighted regression. The results provide insights for city planners to address social segregation.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2023)
Article
Environmental Studies
Aynaz Lotfata, George Grekousis, Ruoyu Wang
Summary: This study examines the contribution of ten socioeconomic neighborhood factors to hypertension prevalence in Chicago. The results show that the importance of these factors varies across different neighborhoods. Understanding these variations can inform the development and implementation of localized health policies.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2023)
Article
Computer Science, Information Systems
Yao Yao, Siqi Lei, Zijin Guo, Yuanyuan Li, Shuliang Ren, Zhihang Liu, Qingfeng Guan, Peng Luo
Summary: Urban logistics plays a vital role in the development and operation of cities, and optimizing it can greatly benefit economic growth. The challenges of current logistics optimization include increasing customer needs and the complexity of urban systems. In this study, a hybrid sparrow search algorithm (SA-SSA) is proposed, which combines the sparrow search algorithm with fast computational speed and the simulated annealing algorithm with the ability to find the global optimum solution. Experiments conducted in Wuhan city show that SA-SSA can optimize large-scale urban logistics with guaranteed efficiency and solution quality.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
Article
Remote Sensing
Yao Yao, Jianfeng Zhou, Zhenhui Sun, Qingfeng Guan, Zhiqiang Guo, Yin Xu, Jinbao Zhang, Ye Hong, Yuyang Cai, Ruoyu Wang
Summary: This study examines China's progress in poverty reduction from 2016 to 2019 using time-series multi-source geospatial data and a deep learning model. The findings show a significant overall decrease in poverty rates throughout China during this period. The study also identifies an uneven geographical distribution of poverty rates between Southeast and Northwest China. The results suggest that future poverty reduction policies should focus on infrastructure development in poor areas and increasing population density.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Dongwei Liu, Yuxiao Jiang, Ruoyu Wang, Yi Lu
Summary: Trees in urban areas provide various ecological, social, and health benefits. However, most cities lack comprehensive street-tree inventories due to the laborious and expensive conventional field assessment. In this study, a cost-effective and novel method utilizing computer vision and street view images was developed to establish a city-wide tree inventory, providing information about individual trees such as species, height, crown diameter, and geographical coordinates.
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
(2023)
Article
Environmental Studies
Yiyi Chen, Colin A. Jones, Neil A. Dunse, Enquan Li, Ye Liu
Summary: This study examined the association between housing prices and green space characteristics, focusing on the impact of the shape pattern index. Using a hedonic price model, the research analyzed data from 16,222 housing transactions in the Metropolitan Area of Beijing. The results showed that an increase in the landscape shape index (LSI) can significantly raise housing prices, especially for residences near urban green spaces.
Article
Environmental Studies
Yiwei Bai, Yihang Bai, Ruoyu Wang, Tianren Yang, Xinyao Song, Bo Bai
Summary: The incorporation of cycling as a mode of transport has positive impacts on reducing traffic congestion, improving mental health outcomes, and contributing to sustainable cities. Bike-sharing systems have made cycling more accessible and convenient in urban areas. The connection between cycling behavior and the built environment, specifically urban greenways, was examined in this study using cycling trip data and street-view images. The results showed that the greenness and enclosure of greenways positively correlated with increased cycling, while the openness had differing effects on weekdays and weekends.
Article
Environmental Sciences
Ruoyu Wang, Wenjie Wu, Yao Yao, Wenxuan Tan
Summary: This study develops a new and systematic framework to assess potential disparities in quality and quantity aspects of visible green space provision around subway stations. The results show that there are disparities in visible green space provision around subway stations, but such disparities tend to fade with distance away from stations. Population density, land use mix, intersection density, and bus stop density are significantly associated with quantity and quality aspects of visible green space provision around subway stations.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Ecology
Ruoyu Wang, Matthew H. E. M. Browning, Frank Kee, Ruth F. Hunter
Summary: This study found that urban regeneration of urban green and blue spaces has a positive impact on residents' mental wellbeing along the Connswater Community Greenway in Belfast, Northern Ireland. The subjective perceptions of the environment and instoration indicators play a mediating role in linking UGBS proximity and mental wellbeing. The relationship between UGBS and mental wellbeing becomes more significant after the intervention.
LANDSCAPE AND URBAN PLANNING
(2023)
Article
Ecology
Wenjie Wu, Wenxuan Tan, Ruoyu Wang, Wendy Y. Chen
Summary: This study explores the effects of both the quantity and quality of neighborhood greenspaces on residents' life satisfaction in Beijing, and examines the differences in these effects across different social groups. The results demonstrate that greenspace quality has a more significant impact on life satisfaction, and both quantity and quality features contribute positively. The study enriches our understanding of the relationship between multi-dimensions of urban greenspaces and life satisfaction, and provides useful insights for improving population life satisfaction and narrowing inequalities.
LANDSCAPE AND URBAN PLANNING
(2023)
Article
Environmental Studies
Wenjie Wu, Yao Yao, Ruoyu Wang
Summary: This study investigates the association between green space exposure around subway stations and people's choice of subway as their primary commuting mode and travel satisfaction in Beijing. The results show that the quantity and quality of green space have differential effects on subway use and travel satisfaction in residential and workplace contexts. The findings highlight the complementary effects of green space and travel infrastructure in shaping travel behavior and wellbeing.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Geography
Yao Yao, Chenqi Feng, Jiteng Xie, Xiaoqin Yan, Qingfeng Guan, Jian Han, Jiaqi Zhang, Shuliang Ren, Yuyun Liang, Peng Luo
Summary: The world is facing more energy crises due to extreme weather and the rapidly growing demand for electricity. Siting new substations and optimizing the location of existing ones are necessary to address the energy crisis. The current site selection lacks consideration of spatial and temporal heterogeneity in urban power demand, which results in unreasonable energy transfer and waste, leading to power outages in some areas. A multi-scene micro-scale urban substation siting framework (UrbanPS) is proposed to maximize grid coverage and transformer utilization by estimating fine-scale power consumption, dividing power supply areas, and optimizing substation location using big data and machine learning models, region growing algorithms, and genetic algorithms. By applying this framework in Pingxiang City, Jiangxi Province, the optimization results showed close to 99% coverage and utilization rate under different power consumption scenarios, and potential energy savings through dynamic regulation of substation operation were identified.
TRANSACTIONS IN GIS
(2023)
Article
Environmental Studies
Zhuolin Pan, Ye Liu, Haining Wang, Yuqi Liu
Summary: Over the past two decades, house prices in Chinese large cities have risen quickly, making them unaffordable for most people. This study examines the impact of house prices on subjective wellbeing (SWB) in urban residents, as well as the mechanisms involved. The findings indicate that house prices negatively affect SWB, and this association is influenced by the number of residential properties. The study also reveals that subjective socioeconomic status and household consumption play a role in mediating the relationship between house prices and SWB.
JOURNAL OF HOUSING AND THE BUILT ENVIRONMENT
(2023)
Article
Computer Science, Information Systems
Wei Tu, Wei Gao, Mingxiao Li, Yao Yao, Biao He, Zhengdong Huang, Jie Zhang, Renzhong Guo
Summary: This study proposes a spatial cooperative simulation approach to capture the inter-wined influences among multiple features in urban development and forecast future development scenarios.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
