“streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics
Street view imagery (SVI) is an increasingly important data source for urban analytics and environmental researchers studying the visual quality of the built environment. Compared to remote sensing imagery, SVI can provide a different plane of perspective at ground level and better determine the int...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | SoftwareX |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711024003510 |
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| author | Xiaohao Yang Mark Lindquist Derek Van Berkel |
| author_facet | Xiaohao Yang Mark Lindquist Derek Van Berkel |
| author_sort | Xiaohao Yang |
| collection | DOAJ |
| description | Street view imagery (SVI) is an increasingly important data source for urban analytics and environmental researchers studying the visual quality of the built environment. Compared to remote sensing imagery, SVI can provide a different plane of perspective at ground level and better determine the interplay between urban physical settings and socio-ecological factors that enhance well-being and sustainability. Mapillary, a platform for volunteered street view imagery, has emerged as a promising alternative to Google Street View, offering greater accessibility. Nonetheless, the utility of this open-source database can be limited by the current Mapillary Application Programming Interface (API), which only partially meets the needs of urban analytics research. To address this, we introduce ''streetscape,'' an R package designed to provide user-friendly functions for collecting and analyzing street view imagery data from Mapillary. In addition, the package supports the generation of surveys for the qualitative study of urban landscapes. |
| format | Article |
| id | doaj-art-c0ab1907355b4772a3ea57b5750ccb2c |
| institution | DOAJ |
| issn | 2352-7110 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj-art-c0ab1907355b4772a3ea57b5750ccb2c2025-08-20T03:11:33ZengElsevierSoftwareX2352-71102025-02-012910198110.1016/j.softx.2024.101981“streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analyticsXiaohao Yang0Mark Lindquist1Derek Van Berkel2Corresponding author.; School for Environment and Sustainability, University of Michigan, USASchool for Environment and Sustainability, University of Michigan, USASchool for Environment and Sustainability, University of Michigan, USAStreet view imagery (SVI) is an increasingly important data source for urban analytics and environmental researchers studying the visual quality of the built environment. Compared to remote sensing imagery, SVI can provide a different plane of perspective at ground level and better determine the interplay between urban physical settings and socio-ecological factors that enhance well-being and sustainability. Mapillary, a platform for volunteered street view imagery, has emerged as a promising alternative to Google Street View, offering greater accessibility. Nonetheless, the utility of this open-source database can be limited by the current Mapillary Application Programming Interface (API), which only partially meets the needs of urban analytics research. To address this, we introduce ''streetscape,'' an R package designed to provide user-friendly functions for collecting and analyzing street view imagery data from Mapillary. In addition, the package supports the generation of surveys for the qualitative study of urban landscapes.http://www.sciencedirect.com/science/article/pii/S2352711024003510Urban analyticsStreet-level imageryUrban greeneryUrban landscapeUrban perceptionR package |
| spellingShingle | Xiaohao Yang Mark Lindquist Derek Van Berkel “streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics SoftwareX Urban analytics Street-level imagery Urban greenery Urban landscape Urban perception R package |
| title | “streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics |
| title_full | “streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics |
| title_fullStr | “streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics |
| title_full_unstemmed | “streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics |
| title_short | “streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics |
| title_sort | streetscape package in r a reproducible method for analyzing open source street view datasets and facilitating research for urban analytics |
| topic | Urban analytics Street-level imagery Urban greenery Urban landscape Urban perception R package |
| url | http://www.sciencedirect.com/science/article/pii/S2352711024003510 |
| work_keys_str_mv | AT xiaohaoyang streetscapepackageinrareproduciblemethodforanalyzingopensourcestreetviewdatasetsandfacilitatingresearchforurbananalytics AT marklindquist streetscapepackageinrareproduciblemethodforanalyzingopensourcestreetviewdatasetsandfacilitatingresearchforurbananalytics AT derekvanberkel streetscapepackageinrareproduciblemethodforanalyzingopensourcestreetviewdatasetsandfacilitatingresearchforurbananalytics |