The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
| Autor: | Masatomo Suzuki, Junichiro Mori, Takashi Nicholas Maeda, Jun Ikeda |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Journal of Asian Architecture and Building Engineering, Vol 22, Iss 3, Pp 1110-1125 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1347-2852 13467581 32416407 |
| DOI: | 10.1080/13467581.2022.2070492 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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