Mechanisms contributing to road network growth in volunteered street view imagery data

Abstract. This study focuses on the growth of road networks in volunteered street view imagery (VSVI) data, using data from the Mapillary platform in Tokyo as a case study. The results demonstrate that VSVI data extends outward from the city center and is governed by two fundamental spatial processes, densification and exploration, as observed for OpenStreetMap in previous studies. Among these, densification becomes more dominant as dataset grows, rising from 76.8% to 91.4% of total contributions. Furthermore, bivariate regression analyses indicated relationships between the number of image contributions and road coverage, as well as the growth rate of road networks for various road types. Specifically, the growth in coverage for National Expressways follows a logarithmic model, whereas other road types are better represented by linear models with higher-grade roads exhibiting greater growth rates. This study represents the first attempt to explore the links between the number of contributions and spatial distribution in VSVI, thereby providing new insights into its dynamic growth patterns and future development trends.