Abstract
‘Collective intelligence’ is defined as groups of individuals doing things collectively that seem intelligent. Currently, many students have digital cameras or cell-phone cameras. Moreover, a good network environment is commonly available and it has become very easy to collect email photos. We aimed to analyze a landscape cognition using ‘collective intelligence’ to collect large number of photos taken of a target place by many students. A web-based system was developed to aggregate the collected photos. On this web system, each student used subjective criteria to put all of the collected photos into groups of ‘similar’ photos. A similarity matrix between the collected photos was measured to sum up each student's subjective perceptions of similarities. The configuration of photos (i.e. a landscape similarity map) was obtained by using MDS. The landscape similarity map was uploaded to the web. A landscape survey conducted by 22 students from the Tama farm of the University of Tokyo revealed three major landscape components of ‘buildings’, ‘farms’ and ‘roads’. Another landscape survey conducted by 29 students from the Hongo and Yayoi campuses of the University of Tokyo revealed four major components of ‘buildings’, a ‘pond’, a ‘mighty tree’ and ‘roads’.
