09:20 〜 09:40
[E1-02] The Generation Process and Data Characteristics of Volunteered Street View Imagery for Streetscape Monitoring: A Case Study in Tokyo
キーワード：Crowdsourcing, Volunteered Street View Imagery (VSVI), Mapillary, Contribution behavior, Data quality
Street View Imagery (SVI) has become an essential data source for streetscape audit studies. However, traditional professionally provided SVI (e.g., Google Street View (GSV)) has limitations in spatial and temporal resolution, as well as data usage, which pose challenges for accurate and dynamic streetscape monitoring. The emergence of the Web 2.0 era has enabled individuals to contribute to Volunteered Street View Imagery (VSVI), which has the potential to provide more open and comprehensive geographic information, but is subject to several criteria (e.g., data completeness and quality). In order to better understand the value of VSVI in streetscape monitoring studies, this study aims to analyze the generation process and examine the relevant characteristics in Tokyo using Mapillary. The generation process of Mapillary from 2014 is analyzed in terms of spatial expansion and revisit behavior. For data characteristics, we analyzed data completeness and quality in terms of temporal (update frequency and seasonal diversity) and spatial resolution (spatial density, viewing angle completeness, and perspective diversity) using GSV as a benchmark.