A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
Visual impression of urban landscape has been investigated in detail through behavioral experiments and questionnaire surveys in the field of architecture. However, in order to give an incentive to build and maintain a good residential environment, an economic consideration of the urban landscape across space is also an important aspect. Employing a semantic segmentation approach using Google Street View images, we investigate the relationship between urban landscapes and property prices in low-rise residential areas in a suburban city of Tokyo, Japan. Such visual images are used to represent the landscape of both surrounding districts in general and the street-level landscape; more specifically, the latter is derived after controlling for the district fixed effect. We first show that greenery, openness and visual enclosure are positively correlated with property price at street level. We also investigate the value of urban landscapes commonly seen in Japan: (i) the presence of a power pole is negatively correlated with property price at district level; and (ii) the presence of a road shoulder or farmland, either of which may disrupt the continuity of a residential area, does not exhibit negative correlations with property price at either district or street level.
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
Visual impression of urban landscape has been investigated in detail through behavioral experiments and questionnaire surveys in the field of architecture. However, in order to give an incentive to build and maintain a good residential environment, an economic consideration of the urban landscape across space is also an important aspect. Employing a semantic segmentation approach using Google Street View images, we investigate the relationship between urban landscapes and property prices in low-rise residential areas in a suburban city of Tokyo, Japan. Such visual images are used to represent the landscape of both surrounding districts in general and the street-level landscape; more specifically, the latter is derived after controlling for the district fixed effect. We first show that greenery, openness and visual enclosure are positively correlated with property price at street level. We also investigate the value of urban landscapes commonly seen in Japan: (i) the presence of a power pole is negatively correlated with property price at district level; and (ii) the presence of a road shoulder or farmland, either of which may disrupt the continuity of a residential area, does not exhibit negative correlations with property price at either district or street level.
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
Masatomo Suzuki (author) / Junichiro Mori (author) / Takashi Nicholas Maeda (author) / Jun Ikeda (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
| Taylor & Francis Verlag | 2023
Changing Urban/suburban landscapes
| British Library Conference Proceedings | 2001
Street furniture, Tokyo, Japan
| British Library Online Contents | 2001