Abstract
It is important for understanding the visitor movement patterns to develop planning for tourist destination. This study clarified visitor movement patterns in the context of CCS use in Kawagoe city, Saitama prefecture, Japan, which was based on surveys using GPS loggers and questionnaires. Raster computation of two types of kernel density based on GPS logs with high or low speed revealed the difference of time and space which visitors walk or use CCS. Cluster analysis of six behavioral indicators classified visitor movement patterns to three clusters. In addition, results revealed that CCS users tended to visit more tourist attractions than non-CCS users and to stop by attractions in a short time.
