{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:27:58Z","timestamp":1781108878720,"version":"3.54.1"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jiangsu Province Industry-University-Research Cooperation Program","award":["BY20221316"],"award-info":[{"award-number":["BY20221316"]}]},{"name":"Jiangsu Province Industry-University-Research Cooperation Program","award":["42471488"],"award-info":[{"award-number":["42471488"]}]},{"name":"Jiangsu Province Industry-University-Research Cooperation Program","award":["2021YFE0112300"],"award-info":[{"award-number":["2021YFE0112300"]}]},{"name":"National Natural Science Foundation of China","award":["BY20221316"],"award-info":[{"award-number":["BY20221316"]}]},{"name":"National Natural Science Foundation of China","award":["42471488"],"award-info":[{"award-number":["42471488"]}]},{"name":"National Natural Science Foundation of China","award":["2021YFE0112300"],"award-info":[{"award-number":["2021YFE0112300"]}]},{"name":"National Key R&amp;D Program of China","award":["BY20221316"],"award-info":[{"award-number":["BY20221316"]}]},{"name":"National Key R&amp;D Program of China","award":["42471488"],"award-info":[{"award-number":["42471488"]}]},{"name":"National Key R&amp;D Program of China","award":["2021YFE0112300"],"award-info":[{"award-number":["2021YFE0112300"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Street view imagery has become a vital tool for assessing urban street greenery, with the Green View Index (GVI) serving as the predominant metric. However, while GVI effectively quantifies overall greenery, it fails to capture the nuanced, human-scale experience of urban greenery. This study introduces the Front-Facing Green View Index (FFGVI), a metric designed to reflect the perspective of pedestrians traversing urban streets. The FFGVI computation involves three key steps: (1) calculating azimuths for road points, (2) retrieving front-facing street view images, and (3) applying semantic segmentation to identify green pixels in street view imagery. Building on this, this study proposes the Street Canyon Green View Index (SCGVI), a novel approach for identifying boulevards that evoke perceptions of comfort, spaciousness, and aesthetic quality akin to room-like streetscapes. Applying these indices to a case study in Nanjing, China, this study shows that (1) FFGVI exhibited a strong correlation with GVI (R = 0.88), whereas the association between SCGVI and GVI was marginally weaker (R = 0.78). GVI tends to overestimate perceived greenery due to the influence of lateral views dominated by side-facing vegetation; (2) FFGVI provides a more human-centered perspective, mitigating biases introduced by sampling point locations and obstructions such as large vehicles; and (3) SCGVI effectively identifies prominent boulevards that contribute to a positive urban experience. These findings suggest that FFGVI and SCGVI are valuable metrics for informing urban planning, enhancing urban tourism, and supporting greening strategies at the street level.<\/jats:p>","DOI":"10.3390\/ijgi14080287","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T14:11:44Z","timestamp":1753366304000},"page":"287","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Evaluating Urban Greenery Through the Front-Facing Street View Imagery: Insights from a Nanjing Case Study"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1143-1730","authenticated-orcid":false,"given":"Jin","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China"},{"name":"Suzhou Key Laboratory of Spatial Information Intelligent Technology and Application, Suzhou 215009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8772-1403","authenticated-orcid":false,"given":"Yingjing","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100091, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyue","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9802-4606","authenticated-orcid":false,"given":"Yuan","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinglong","family":"Du","sequence":"additional","affiliation":[{"name":"School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China"},{"name":"Suzhou Key Laboratory of Spatial Information Intelligent Technology and Application, Suzhou 215009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"ref_1","first-page":"396","article-title":"Business District Streetscapes, Trees, and Consumer Response","volume":"103","author":"Wolf","year":"2005","journal-title":"J. For."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Houlden, V., Weich, S., Porto de Albuquerque, J., Jarvis, S., and Rees, K. (2018). The Relationship between Greenspace and the Mental Wellbeing of Adults: A Systematic Review. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0203000"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"103920","DOI":"10.1016\/j.landurbplan.2020.103920","article-title":"Analyzing the Effects of Green View Index of Neighborhood Streets on Walking Time Using Google Street View and Deep Learning","volume":"205","author":"Ki","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.envint.2019.02.013","article-title":"Using Deep Learning to Examine Street View Green and Blue Spaces and Their Associations with Geriatric Depression in Beijing, China","volume":"126","author":"Helbich","year":"2019","journal-title":"Environ. Int."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/01426399108706344","article-title":"Evaluation Methods for Landscapes with Greenery","volume":"16","author":"Aoki","year":"1991","journal-title":"Landsc. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1037\/0022-3514.71.2.230","article-title":"Automaticity of Social Behavior: Direct Effects of Trait Construct and Stereotype Activation on Action","volume":"71","author":"Bargh","year":"1996","journal-title":"J. Personal. Soc. Psychol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.landurbplan.2017.05.010","article-title":"Green Streets \u2212 Quantifying and Mapping Urban Trees with Street-Level Imagery and Computer Vision","volume":"165","author":"Seiferling","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_8","first-page":"103385","article-title":"Sensitivity of Measuring the Urban Form and Greenery Using Street-Level Imagery: A Comparative Study of Approaches and Visual Perspectives","volume":"122","author":"Biljecki","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"101626","DOI":"10.1016\/j.compenvurbsys.2021.101626","article-title":"Decoding Urban Landscapes: Google Street View and Measurement Sensitivity","volume":"88","author":"Kim","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"103434","DOI":"10.1016\/j.landurbplan.2018.08.028","article-title":"Measuring Daily Accessed Street Greenery: A Human-Scale Approach for Informing Better Urban Planning Practices","volume":"191","author":"Ye","year":"2019","journal-title":"Landsc. Urban Plan."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1080\/13658816.2018.1555832","article-title":"Street-Frontage-Net: Urban Image Classification Using Deep Convolutional Neural Networks","volume":"34","author":"Law","year":"2020","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"104498","DOI":"10.1016\/j.scs.2023.104498","article-title":"Mapping Seasonal Changes of Street Greenery Using Multi-Temporal Street-View Images","volume":"92","author":"Han","year":"2023","journal-title":"Sustain. Cities Soc."},{"key":"ref_13","first-page":"2010","article-title":"Analyzing Green View Index and Green View Index Best Path Using Google Street View and Deep Learning","volume":"9","author":"Zhang","year":"2022","journal-title":"J. Comput. Des. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"110756","DOI":"10.1016\/j.ecolind.2023.110756","article-title":"Understanding the Nonlinear Effects of the Street Canyon Characteristics on Human Perceptions with Street View Images","volume":"154","author":"Xu","year":"2023","journal-title":"Ecol. Indic."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhu, J., Gong, Y., Liu, C., Du, J., Song, C., Chen, J., and Pei, T. (2023). Assessing the Effects of Subjective and Objective Measures on Housing Prices with Street View Imagery: A Case Study of Suzhou. Land, 12.","DOI":"10.3390\/land12122095"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1209","DOI":"10.1080\/2150704X.2024.2407557","article-title":"An Assessment of How Street View Imagery and Remote-Sensing Data of Green and Blue Spaces Can Explain Variations in Housing Prices: A Case Study in Suzhou, China","volume":"15","author":"Zhu","year":"2024","journal-title":"Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.landurbplan.2008.12.004","article-title":"Can You See Green? Assessing the Visibility of Urban Forests in Cities","volume":"91","author":"Yang","year":"2009","journal-title":"Landsc. Urban Plan."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1080\/13574800802451155","article-title":"Measuring the Unmeasurable: Urban Design Qualities Related to Walkability","volume":"14","author":"Ewing","year":"2009","journal-title":"J. Urban Des."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"104217","DOI":"10.1016\/j.landurbplan.2021.104217","article-title":"Street View Imagery in Urban Analytics and GIS: A Review","volume":"215","author":"Biljecki","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e2220417120","DOI":"10.1073\/pnas.2220417120","article-title":"Urban Visual Intelligence: Uncovering Hidden City Profiles with Street View Images","volume":"120","author":"Fan","year":"2023","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"106048","DOI":"10.1016\/j.landusepol.2022.106048","article-title":"Does Visual Contact with Green Space Impact Housing Prices\u0294 An Integrated Approach of Machine Learning and Hedonic Modeling Based on the Perception of Green Space","volume":"115","author":"Wu","year":"2022","journal-title":"Land Use Policy"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.healthplace.2018.07.001","article-title":"Systematic Review of the Use of Google Street View in Health Research: Major Themes, Strengths, Weaknesses and Possibilities for Future Research","volume":"52","author":"Rzotkiewicz","year":"2018","journal-title":"Health Place"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/j.ufug.2015.06.006","article-title":"Assessing Street-Level Urban Greenery Using Google Street View and a Modified Green View Index","volume":"14","author":"Li","year":"2015","journal-title":"Urban For. Urban Green."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"126995","DOI":"10.1016\/j.ufug.2021.126995","article-title":"Development of a System for Assessing the Quality of Urban Street-Level Greenery Using Street View Images and Deep Learning","volume":"59","author":"Xia","year":"2021","journal-title":"Urban For. Urban Green."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kumakoshi, Y., Chan, S.Y., Koizumi, H., Li, X., and Yoshimura, Y. (2020). Standardized Green View Index and Quantification of Different Metrics of Urban Green Vegetation. Sustainability, 12.","DOI":"10.3390\/su12187434"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"104472","DOI":"10.1016\/j.cities.2023.104472","article-title":"Measuring Streetscape Perceptions from Driveways and Sidewalks to Inform Pedestrian-Oriented Street Renewal in D\u00fcsseldorf","volume":"141","author":"Rui","year":"2023","journal-title":"Cities"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.buildenv.2018.02.042","article-title":"Mapping Sky, Tree, and Building View Factors of Street Canyons in a High-Density Urban Environment","volume":"134","author":"Gong","year":"2018","journal-title":"Build. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1007\/978-3-030-01234-2_49","article-title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation","volume":"Volume 11211","author":"Ferrari","year":"2018","journal-title":"Computer Vision\u2013ECCV 2018"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, H., Li, F., Xu, H., Huang, S., Liu, S., Ni, L.M., and Zhang, L. (2023). MP-Former: Mask-Piloted Transformer for Image Segmentation. arXiv.","DOI":"10.1109\/CVPR52729.2023.01733"},{"key":"ref_30","first-page":"104058","article-title":"Measuring Solar Radiation and Spatio-Temporal Distribution in Different Street Network Direction through Solar Trajectories and Street View Images","volume":"132","author":"Wang","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Cheng, B., Misra, I., Schwing, A.G., Kirillov, A., and Girdhar, R. (2022). Masked-Attention Mask Transformer for Universal Image Segmentation. arXiv.","DOI":"10.1109\/CVPR52688.2022.00135"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., Franke, U., Roth, S., and Schiele, B. (2016, January 27\u201330). The Cityscapes Dataset for Semantic Urban Scene Understanding. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"106424","DOI":"10.1016\/j.buildenv.2019.106424","article-title":"Classification and Mapping of Urban Canyon Geometry Using Google Street View Images and Deep Multitask Learning","volume":"167","author":"Hu","year":"2020","journal-title":"Build. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wu, Y., Sun, Q., Hu, C., Liu, H., Chen, C., and Xiao, P. (2023). Tree Failure Assessment of London Plane (Platanus acerifolia (Aiton) Willd.) Street Trees in Nanjing City. Forests, 14.","DOI":"10.3390\/f14091696"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.trc.2019.07.013","article-title":"A Novel Method for Predicting and Mapping the Occurrence of Sun Glare Using Google Street View","volume":"106","author":"Li","year":"2019","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"103387","DOI":"10.1016\/j.landurbplan.2018.07.011","article-title":"Mapping the Spatio-Temporal Distribution of Solar Radiation within Street Canyons of Boston Using Google Street View Panoramas and Building Height Model","volume":"191","author":"Li","year":"2019","journal-title":"Landsc. Urban Plan."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"103289","DOI":"10.1016\/j.scs.2021.103289","article-title":"Street-Level Solar Radiation Mapping and Patterns Profiling Using Baidu Street View Images","volume":"75","author":"Deng","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"127845","DOI":"10.1016\/j.ufug.2023.127845","article-title":"Comparing Conventional Manual Measurement of the Green View Index with Modern Automatic Methods Using Google Street View and Semantic Segmentation","volume":"80","author":"Aikoh","year":"2023","journal-title":"Urban For. Urban Green."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"105262","DOI":"10.1016\/j.scs.2024.105262","article-title":"Accessing Eye-Level Greenness Visibility from Open-Source Street View Images: A Methodological Development and Implementation in Multi-City and Multi-Country Contexts","volume":"103","author":"Labib","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"104896","DOI":"10.1016\/j.scs.2023.104896","article-title":"A Novel Walkability Index Using Google Street View and Deep Learning","volume":"99","author":"Ki","year":"2023","journal-title":"Sustain. Cities Soc."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"103630","DOI":"10.1016\/j.scs.2021.103630","article-title":"CitySurfaces: City-Scale Semantic Segmentation of Sidewalk Materials","volume":"79","author":"Hosseini","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1080\/15481603.2017.1338389","article-title":"Building Block Level Urban Land-Use Information Retrieval Based on Google Street View Images","volume":"54","author":"Li","year":"2017","journal-title":"GIScience Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Novack, T., Vorbeck, L., Lorei, H., and Zipf, A. (2020). Towards Detecting Building Facades with Graffiti Artwork Based on Street View Images. IJGI, 9.","DOI":"10.3390\/ijgi9020098"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.isprsjprs.2024.06.023","article-title":"Global Streetscapes\u2014A Comprehensive Dataset of 10 Million Street-Level Images across 688 Cities for Urban Science and Analytics","volume":"215","author":"Hou","year":"2024","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"104873","DOI":"10.1016\/j.landurbplan.2023.104873","article-title":"Bridging the Gap between Pedestrian and Street Views for Human-Centric Environment Measurement: A GIS-Based 3D Virtual Environment","volume":"240","author":"Ki","year":"2023","journal-title":"Landsc. Urban Plan."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/8\/287\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:15:30Z","timestamp":1760033730000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/8\/287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"references-count":45,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["ijgi14080287"],"URL":"https:\/\/doi.org\/10.3390\/ijgi14080287","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,24]]}}}