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Understanding the type of spaces and scenery that people prefer is important when designing and managing tourist destinations. A technique based on participants’ own photography has been used to analyze visitors’ scenic perceptions during their on-site experiences. We created a density map of visitors’ photo-taking locations and thus evaluated the space potential, based on their visual preferences. This study attempts to reduce certain biases by modeling the maps using the kernel density estimation (KDE) method. Two types of weighted scores are used in the density computation and five indicators are set as the components of the weighted scores: the scores of likeability which indicates the emotional distance with each photograph, the scores based on the object types of photos, the reciprocal number of photographs created by each participant, the distance between the photo-taking locations and the participants’ starting points, and the reciprocal of the photo-taking time. The weighted scores enabled more accurate density maps of the photo-taking locations, better indicating the potential of locations when compared to the result with non-weighted scores. The results will contribute to park management and to policies relating to the conservation, maintenance, and promotion of visual resources.

Visualizing the Sightseeing Potential of Urban Recreational Spaces: A Study of Weighted Scores on the Density Estimation of Points of Visual Interest