This research investigated the impact of social-networking service posts on the formation of image structure of cities,focusing on the spatial distribution of images and their content similarity.It aimed to delineate the image structure of cities created by numerous users,moving beyond traditional qualitative methods towards a more quantitative and objective approach with big data.Taking central Tokyo as an example,this study extracted geotagged image data of 33 major railway station areas from Flickr’s API(Application Programming Interface).Four coverage types of viewpoint distribution,namely planar,intersecting linear,linear,and nodal,were identified,reflecting the unique urban structures respectively.Further investigation of the image contents,primarily consisting of“urban landscape”and“landscape/street trees,”showed that such contents significantly influenced the formationof the image structure of cities.The study concluded that asthe number of photo posts increased and the representativeviewpoints concentrated,the digital information received by usersbecame more homogeneous,leading to strongly stereotypedimages of urban landscapes.These findings highlight the role ofsocial networking services in shaping perceptions of the urbanenvironment and provide insights into the image structure of citiesas formed by digital information.
