“streetscape” package in R: A reproducible method for analyzing open-source street view datasets and facilitating research for urban analytics

• The "streetscape" package allows users to access and analyze mapillary's SVI datasets through geographic-based searches, segmentation, and green view index calculations, enabling detailed urban environmental studies. • The package supports complex geospatial queries, including integration with openstreetmap road networks, and facilitates large-scale data collection and visualization without requiring image inputs. • The package includes functions to create street view-embedded surveys for Qualtrics, simplifying the process of collecting public opinions on urban landscapes and enhancing research on human-centered urban studies. 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.