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ZenSVI

An open-source software for the integrated acquisition, processing and analysis of street view imagery towards scalable urban science

Dados Bibliográficos

ID7150565
AutoresKoichi Ito (0000-0002-1470-3677, National University of Singapore), Yihan Zhu (0000-0003-0164-6973, National University of Singapore), Mahmoud Abdelrahman (0000-0002-4733-4046, National University of Singapore), Xiucheng Liang (0000-0003-0898-7543, National University of Singapore), Zicheng Fan (0000-0001-7463-8865, National University of Singapore), Yujun Hou (0000-0002-3581-0180, National University of Singapore), Tianhong Zhao (0000-0002-9290-2049, Shenzhen Technology University), Rui Ma (0000-0002-3367-674X, National University of Singapore), Kunihiko Fujiwara (0000-0002-8044-8838, National University of Singapore), Jiani Ouyang (0000-0002-8258-4147, National University of Singapore), Matias Quintana (0000-0002-0486-221X, CREATe Centre), Filip Biljecki (0000-0002-6229-7749, National University of Singapore, autor correspondente)
Ano2025
Volume119
Páginas102283
Data de publicação2025-07-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoComputers Environment and Urban Systems (JOURNAL)
Identificadores do periódicoISSN: 0198-9715 • E-ISSN: 1873-7587
EditoraElsevier BV (PUBLISHER)
DOI10.1016/j.compenvurbsys.2025.102283
OpenAlexW4408597752
IdiomaEN
Citações recebidas22
Referências citadas120

Cartography · Data science · Database · Geography · Open source · Open source software · Scalability · Automated Road and Building Extraction · Computer Science · Impact of Light on Environment and Health · Remote Sensing and LiDAR Applications · Software

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  • What Makes Some Historic Streets Cooler? Field-Measured Utci, Functional Morphology, and Leakage-Safe Spatial Validation across Three Chinese Districts

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  • A Spatial Analysis of Urban Space Albedo According to Urban Surfaces Color

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  • Safe or Unsafe? A Street-Level Analysis of the (Mis)Match Between Perceived and Objective Safety in Chaoyang District, Beijing

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  • A hierarchical network approach for analyzing scale-dependent coupling among policy-relevant dimensions of disaster governance

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  • It is not always greener on the other side

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  • Assessing and mapping public visual perception across urban public space typologies based on geotagged social media images

    Open Access•Chenghao Yang, Ye Zhang•Applied Geography•2026

  • Tracking urban built environment longitudinal changes using text mining and historical street view imagery

    Open Access•Quang Hoai Le, Thi Hong Na Le et al.•Applied Geography•2026

  • Perceived traffic safety’s impact on cycling route choice with street-level images

    Open Access•Koichi Ito, Roos Terra et al.•Transportation•2026

  • Linking Streetscape Atmosphere with Social Vulnerability and Community Resilience

    Zhang Chen, Hanlin Zhou et al.•Annals of the American…•2026

  • Incorporating urban thermal comfort into transit-oriented development (TOD) planning

    Open Access•Mushu Zhao, Shuyu Lei et al.•Sustainable Cities and Society•2026

  • A utility-based spatial analysis of residential street-level conditions a case study of Rotterdam

    Open Access•Sander Van Cranenburgh, Francisco Garrido-Valenzuela•Cities•2026

  • Does weather matter? Examining measurement bias in street view image-based urban perception assessments

    Open Access•Donghwan Ki, Dongwon Ki et al.•Computers Environment and Urban…•2026

  • Mapping vitality–safety tensions with streetscape scores in Zagreb

    Open Access•Anastasiia Galaktionova, Aura-Luciana Istrate et al.•Journal of Urban Design•2026

  • Fine-timestamped street view imagery reveals patterns of pedestrian dynamics associated with urban functional characteristics

    Open Access•Cheng‐han Yang, Chenghan Yang et al.•Cities•2025

  • Exploring the impact of urbanization intensity on human perception through street view imagery

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  • VoxCity

    Open Access•Kunihiko Fujiwara, Ryuta Tsurumi et al.•Computers Environment and Urban…•2026

  • Assessing bikeability with street view imagery and computer vision

    Open Access•Koichi Ito, Filip Biljecki•Transportation Research Part C:…•2021

  • Densely Connected Convolutional Networks

    Gao Huang, Zhuang Liu et al.•2017 IEEE Conference on Computer…•2017

  • A Computational Approach to Edge Detection

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  • Perceptions of built environment and health outcomes for older Chinese in Beijing

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  • Measuring human perceptions of a large-scale urban region using machine learning

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  • Can you see green? Assessing the visibility of urban forests in cities

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  • A review of urban physical environment sensing using street view imagery in public health studies

    Open Access•Yuhao Kang, Fan Zhang et al.•Annals of GIS•2020

  • Impacts of Street-Visible Greenery on Housing Prices

    Open Access•Yonglin Zhang, Rencai Dong•ISPRS International Journal of…•2018

  • Quantifying the shade provision of street trees in urban landscape

    Open Access•Xiaojiang Li, Carlo Ratti et al.•Landscape and Urban Planning•2018

  • Measuring visual enclosure for street walkability

    Open Access•Li Yin, Zhenxin Wang•Applied Geography•2016

  • Places

    Open Access•Bolei Zhou, Agata Lapedriza et al.•IEEE Transactions on Pattern…•2018

  • ImageNet classification with deep convolutional neural networks

    Open Access•Alex Krizhevsky, Ilya Sutskever et al.•Communications of the ACM•2017

  • OSMnx

    Open Access•Geoff Boeing•Computers Environment and Urban…•2017

  • Using Google Street View to investigate the association between street greenery and physical activity

    Open Access•Yi Lü•Landscape and Urban Planning•2019

  • Building instance classification using street view images

    Open Access•Jian Kang, Mirjam Körner et al.•ISPRS Journal of Photogrammetry…•2018

  • Applications of 3D City Models

    Open Access•Filip Biljecki, Jantien Stoter et al.•ISPRS International Journal of…•2015

  • Assessing street-level urban greenery using Google Street View and a modified green view index

    Open Access•Xiaojiang Li, Chuanrong Zhang et al.•Urban Forestry & Urban Greening•2015

  • Matplotlib

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  • Assessing Street Space Quality Using Street View Imagery and Function-Driven Method

    Open Access•Moyang Wang, Yijun He et al.•ISPRS International Journal of…•2022

  • Diagnosis and Planning Strategies for Quality of Urban Street Space Based on Street View Images

    Open Access•Jiwu Wang, Yali Hu et al.•ISPRS International Journal of…•2023

  • Quantifying the Characteristics of the Local Urban Environment through Geotagged Flickr Photographs and Image Recognition

    Open Access•Meixu Chen, Daniel Arribas-Bel et al.•ISPRS International Journal of…•2020

  • Crowdsourcing Street View Imagery

    Open Access•Raghunath Mahabir, Ross J Schuchard et al.•ISPRS International Journal of…•2020

  • Method for Applying Crowdsourced Street-Level Imagery Data to Evaluate Street-Level Greenness

    Open Access•Xinrui Zheng, Mamoru Amemiya•ISPRS International Journal of…•2023

  • Sensing urban soundscapes from street view imagery

    Open Access•Tianhong Zhao, Xiucheng Liang et al.•Computers Environment and Urban…•2023

  • Free and open source urbanism

    Open Access•Winston Yap, Patrick Janssen et al.•Computers Environment and Urban…•2022

  • From hearing to seeing

    Open Access•Yonggai Zhuang, Yuhao Kang et al.•Computers Environment and Urban…•2024

  • Trackintel

    Open Access•Henry Martin, Ye Hong et al.•Computers Environment and Urban…•2023

  • Places for play

    Open Access•J Kruse, Yuhao Kang et al.•Computers Environment and Urban…•2021

  • Sensing urban poverty

    Open Access•Yuan Meng, Hanfa Xing et al.•Computers Environment and Urban…•2020

  • Streets of London

    Open Access•Azam Raha Bahrehdar, Benjamin Adams et al.•Computers Environment and Urban…•2020

  • Converting street view images to land cover maps for metric mapping

    Open Access•Huan Ning, Zhenlong Li et al.•Computers Environment and Urban…•2022

  • Measuring heterogeneous perception of urban space with massive data and machine learning

    Open Access•Tomás Ramírez, Tomas Eduardo Ramirez et al.•Landscape and Urban Planning•2021

  • Assessing differences in safety perceptions using GeoAI and survey across neighbourhoods in Stockholm, Sweden

    Open Access•Yuhao Kang, Jonatan Abraham et al.•Landscape and Urban Planning•2023

  • Street view imagery in urban analytics and GIS

    Open Access•Filip Biljecki, Koichi Ito•Landscape and Urban Planning•2021

  • Revealing spatio-temporal evolution of urban visual environments with street view imagery

    Open Access•Xiucheng Liang, Tianhong Zhao et al.•Landscape and Urban Planning•2023

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

    Open Access•Bon Woo Koo, Subhrajit Guhathakurta et al.•Environment and Behavior•2022

  • Associations between the quality of street space and the attributes of the built environment using large volumes of street view pictures

    Open Access•Shuangjin Li, Shuang Ma et al.•Environment and Planning B Urban…•2022

  • The visual quality of streets

    Open Access•Yu Ye, Ye Yu et al.•Environment and Planning B Urban…•2019

  • Nighttime Street View Imagery

    Open Access•Zicheng Fan, Filip Biljecki•Sustainable Cities and Society•2024

  • Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning

    Open Access•Yunqin Li, Nobuyoshi Yabuki et al.•Sustainable Cities and Society•2022

  • Accessing eye-level greenness visibility from open-source street view images

    Open Access•Ilse Abril Vázquez Sánchez, S M Labib•Sustainable Cities and Society•2024

  • Social inequalities in neighborhood visual walkability

    Open Access•Hao Zhou, Shenjing He et al.•Sustainable Cities and Society•2019

  • Street pavement classification based on navigation through street view imagery

    Open Access•Rafael G de Mesquita, Tsang Ing Ren et al.•AI & Society•2024

  • Systematic review of the use of Google Street View in health research

    Open Access•Amanda Rzotkiewicz, Amber L Pearson et al.•Health & Place•2018

  • Understanding urban perception with visual data

    Open Access•Koichi Ito, Yuhao Kang et al.•Cities•2024

  • Understanding the user perspective on urban public spaces

    Open Access•Yihan Zhu, Ye Zhang et al.•Cities•2025

  • Understanding cities with machine eyes

    Open Access•Mohamed R Ibrahim, James Haworth et al.•Cities•2020

  • Urban infrastructure audit

    Xiao Li, Huan Ning et al.•Cartography and Geographic…•2021

  • To use or not to use proprietary street view images in (health and place) research? That is the question

    Open Access•Marco Helbich, Matthew Danish et al.•Health & Place•2024

  • Measuring human perceptions of streetscapes to better inform urban renewal

    Open Access•Xiangyuan Ma, Chenyan Ma et al.•Cities•2021

  • Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery

    Open Access•Zeyu Wang, Koichi Ito et al.•Cities•2024

  • Automatic assessment of public open spaces using street view imagery

    Open Access•Shuting Chen, Filip Biljecki•Cities•2023

  • Investigating the potential of crowdsourced street-level imagery in understanding the spatiotemporal dynamics of cities

    Open Access•Meihui Wang, James Haworth et al.•Cities•2024

  • Understanding architecture age and style through deep learning

    Open Access•Maoran Sun, Fan Zhang et al.•Cities•2022

  • Spatial accessibility and transport inequity in Finland

    Open Access•Matti Pönkänen, Henrikki Tenkanen et al.•Computers Environment and Urban…•2025

  • A citizen science toolkit to collect human perceptions of urban environments using open street view images

    Open Access•Matthew Danish, M Labib et al.•Computers Environment and Urban…•2025

Obras citantes distintas22
Citações por ano22
Intervalo de citações2025 - 2026 (2)
Velocidade de citaçãocurrent
Altamente citadoNão
Tipos de citaçãoNeutras: 19
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae