Though many researches have already indicated that physical activity such as walking is important to reduce the risk of disease related lifestyle. Especially in Europe and the United States, the built environment is recognized as key factors in promoting physical activity. However it is not quantitatively clear that the relation between them. In this study, we analyzed the relation between the built environment of residential zoning scale and physical activity levels by the analysis using the data of 40 cities from 1987 to 2005. We made it clear that the higher convenience of public transportation and commercial in a residential area is, the higher the physical activity levels is regardless of the location in the city. We also clarified that the characteristics of the residential zone are important factors to increase physical activity levels compared with personal attributes from the causal structural model. As well as the population density, in recent years, the accessibility to railway stations and bus stops and the frequency of the public transportation services had even more significant associations with physical activity levels of individuals.
Recently, people flow information has become necessary to mitigate secondary disasters following earthquakes, fires, or other major events, and to improve congestion at railway stations, roads, and public spaces. With the fast development of information technologies, nowadays the collection of people flow data becomes much easier and we can have different kinds of measurement data, such as train use data gotten by IC card, high way use data gotten by Electronic Toll Collection System, and so on. However, most of them have been used separately. In this research, we are trying to estimate people flow in an urban area by combining these different kinds of observation data together to make a more accurate estimation about people, based on data assimilation techniques. We propose an algorithm using Particle Filters for data assimilation of people flow data and estimate people flow in Tokyo metropolitan area, assuming that we can get the number of people who ride or drop trains at each station as observations and the number of people who use each main road in Tokyo metropolitan area. In this algorithm, we make a people flow estimation model from Person Trip Data in Tokyo metropolitan area, the actual people flow data gotten by 3 percent people of the area with questionnaires, and particles are made by this model. We evaluate the particles by the assumed observations. For the validation, we assume that only people who are included in Person Trip Data are in Kanto urban area and regard Person Trip Data as the complete people flow. We then select 3 percent of this to make the probabilistic people flow estimation model and estimate people flow of the assumed Kanto urban area. This assumption makes us possible to verify the estimation by comparing it with Person Trip Data.
Under flood conditions, a river flow can have a scouring action on a bridge pier foundation, reducing its stability and even toppling it, and as a result causing a severe train accident. In addition to installing protection works and rebuilding deteriorated piers, imposing operational restrictions according to water level is a practical method to secure safe train operations. In order to decide an appropriate regulation, it is required to investigate structural condition of bridge piers. However, it is impossible to estimate the conditions of whole scouring apprehended bridge piers in more detail. Therefore, it is important to establish the extraction system for such bridge piers from simple parameters related to scouring. In this paper, a relationship between structural data of bridge pier from routine inspection work and past scouring phenomenon were examined by multiple statistical analysis. Based on a result of their analysis, we proposed simple estimating method for scouring apprehended bridge piers under flood conditions.
The purpose of this study is to clarify the mechanism for the formation of hierarchical urban systems. Specifically, we show that relocation costs is a source for the emergence of urban hierarchies. To achieve this purpose, a multi-industrial core-periphery (CP) model is developed by extending a single-industrial CP model of Pflüger1), and by incorporating relocation costs that are heterogeneous across industries. Applying the analytical and numerical approaches provided by Akamatsu et al.2) and Ikeda et al.3), we show that hierarchical industrial location patterns emerge as stable equilibria of the model.
Cooperation is one of the effective methods for local governments to build geospatial data economically. In this study, we focus aerial photograph and tried to make a method to estimate the cost saving effect of cooperation. Using this method local government officials who may not necessarily have technical knowledge of aerial survey can estimate cost save. We estimate the costs to take aerial photos by the method to set a flight course easily that took a rule of survey into account. We get the result the test calculation level of cost save from 40% to 80% according to a number and an area of cities. These results almost meet preceding studies.