Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management)
Online ISSN : 2185-6540
ISSN-L : 2185-6540
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Paper (In Japanese)
  • Ryoji MATSUNAKA, Tetsuharu OBA, Dai NAKAGAWA, Takuya TACHIBANA
    2019 Volume 75 Issue 4 Pages 202-211
    Published: 2019
    Released: October 20, 2019
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     This paper carried out comparative analysis of the status of pedestrian area in city center, the service level of urban rail transit, and the proximity between railway stations and pedestrian area, among Japanese, German and French provincial cities. Our results indicate that Germany and France have more provincial cities that have a high service level of urban rail transit, larger pedestrian areas in their city centers, and closer proximity between railway stations and pedestrian areas than in Japan. After analyzing the relationship between population distribution and the service level of urban rail transit, as well as the proximity between railway stations and pedestrian areas, we clarified that the service level of railways has a relation to the ratio of population concentration around stations in city centers. Finally, population density around railway stations is higher in city than in suburban areas.

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  • Haruka WAKE, Ayaka MIZUNO, Takehito UJIHARA, Hirofumi ABE
    2019 Volume 75 Issue 4 Pages 212-220
    Published: 2019
    Released: October 20, 2019
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     The numbers of vacant homes are increasing steadily throughout Japan. Their distribution in the market must be promoted. This study analyzed the actual conditions of owners’ and non-owners’ awareness. Then we evaluated approaches to promote the distribution of vacant houses in markets based on results of the analysis. The analysis results demonstrated that preferences for vacant houses differed depending on the number of years they were vacant and the age of the owners. For example, young people were willing to lease out or sell houses and to use official systems. Renovation of vacant houses should start in the early stage of vacancy.

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  • Yukitsugu KOMAZAWA, Noboru HARATA, Kiyoshi TAKAMI, Giancarlos TRONCOSO ...
    2019 Volume 75 Issue 4 Pages 221-232
    Published: 2019
    Released: November 20, 2019
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     In old age, outdoor activities are positively related to physical health and well-being. However, the decline of physical functioning makes it difficult to go outside. In this study, to capture the mitigation effects of car usage on this decline of going outside behaviors, the relationship among car availability, physical functioning, and going-out behavior was investigated on older Japanese aged 65 and above by using data from the 6th nationwide person trip survey conducted in 2015. Logistic regression models indicate that in case of maintenance activities (shopping) the availability of a personal car seemed to mitigate the deleterious effects of physical functioning decline. However, the possession of a family-shared car was not necessarily significant. Moreover, in case of leisure activities (eating out, social activities, and leisure), among females, the same mitigation effects were observed. These findings suggest that there is a gender difference in the role of car availability among older people whose physical functioning has been deteriorating.

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  • Kiyoshi KOBAYASHI, Kiyoyuki KAITO, Daijiro MIZUTANI, Yasuhito SAKAI
    2019 Volume 75 Issue 4 Pages 233-249
    Published: 2019
    Released: November 20, 2019
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     The number of cases where the deterioration of an infrastructure is caused by an external factor immediately is not so large. The effects of such external factors tend to accumulate and then cause deterioration after a while. In this study, the authors monitor the progress of deterioration of a structure based on the measurements obtained on a real-time basis for a long period of time, and proposes a methodology for detecting abnormalities in a preventive manner. In detail, the authors propose an ARFIMAX-FIGARCH model considering long-term memories regarding the effects of external factors on structures to model deterioration of a structure with a time lag. Furthermore, the proposed methodology is applied to the monitoring data of the expansion joints of actual expressways, in order to discuss its effectiveness.

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  • Ryoko ARASHIDA, Kazumasa OZAWA
    2019 Volume 75 Issue 4 Pages 250-261
    Published: 2019
    Released: November 20, 2019
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     Damage from the Impending Tokyo Inland Earthquake is predicted to influence property demand and produce market disparities all over the city. The Tokyo government designates City Reconstruction Areas to prioritize reconstruction and redevelopment activities, but the majority of the city will likely fall under non-designated areas. Experiences from the Great Hanshin earthquake revealed that such non-designated areas generate many persistent empty lots. To alleviate the expected problem of empty lots, this research utilizes data from the Great Hanshin earthquake (approximately 1400 properties) to construct a Random Forest prediction model. The model is able to predict the presence or absence of land transactions of damaged property five years after the earthquake, at an accuracy rate of 81%. Further analysis of the model revealed two measures to promote land transactions: 1) property merging, and 2) allowing zoning reclassification from “commercial use” to “residential”. Impacts of the two measures were tested with data from Tokyo, and it is estimated that a combination of both measures is predicted to decrease empty lots by 30% after the Tokyo Inland Earthquake.

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  • Mikihisa ONDA, Daisuke MURAKAMI, Minoru OSAWA, Yuki TAKAYAMA, Kiyohiro ...
    2019 Volume 75 Issue 4 Pages 262-272
    Published: 2019
    Released: November 20, 2019
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     This paper introduces a two-stage linear modeling for coarse regional population distribution data on top of the group-theoretic spectrum analysis method by Onda et al.1) In the first step, the proposed method employs Lasso estimator to select a set of a small number of explanatory variables. In the second step, a hierarchical modeling-based variation partitioning combined with a significance test is introduced to rank the explanatory power of the selected variables. Employing actual population data of Stuttgart, Köln, Atlanta, and Dallas, we demonstrate effectiveness of the proposed method.

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