Hajime Seya

Moderation of Summertime Heat Island Phenomena via Modification of the Urban Form in the Tokyo Metropolitan Area

AbstractThis study investigated the moderation of the urban heat island via changes in the urban form in the Tokyo metropolitan area (TMA). Two urban scenarios with the same population as that of the current urban form were used for sensitivity experiments: the dispersed-city and compact-city scenarios. Numerical experiments using the two urban scenarios as well as an experiment using the current urban form were conducted using a regional climate model coupled with a single-layer urban canopy model. The averaged nighttime surface air temperature in TMA increased by ~0.34°C in the dispersed-city scenario and decreased by ~0.1°C in the compact-city scenario. Therefore, the compact-city scenario had significant potential for moderating the mean areal heat-island effect in the entire TMA. Alternatively, in the central part of the TMA, these two urban-form scenarios produced opposite effects on the surface air temperature; that is, severe thermal conditions worsened further in the compact-city scenario because...

Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits

This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.

Creation of future urban environmental scenarios using a geographically explicit land-use model: a case study of Tokyo

In the present study, a large-scale geographically explicit land-use model was developed for projecting the geographical distribution of urban environmental variables, such as population density and fraction of urban and green vegetation land cover, for different urban forms. These variables form key inputs for regional climate models, yet they are sometimes addressed in an ad hoc manner. This study employs a land-use equilibrium model based on urban economic theory, which endogenously projects the geographical distribution of households, residential floor space/rent and land area/rent. The model can deal with not only urban growth but also urban shrinkage, which is becoming an important issue for developed countries, including Japan, confronting population decrease. The model is calibrated for the Tokyo Metropolitan Area at the micro-district level. Using the model, this paper demonstrates an extreme urban compact city scenario for the year 2050, and it is compared to the business as usual (BAU) scenario.

Application of Lasso to the Eigenvector Selection Problem in Eigenvector Based Spatial Filtering

Eigenvector based spatial filtering is one of the well-used approaches to model spatial autocorrelation among the observations or errors in a regression model. In this approach, subset of eigenvectors extracted from a modified spatial weight matrix is added to the model as explanatory variables. The subset is typically specified via the forward stepwise model selection procedure, but it is disappointingly slow when the number of observations n takes a large number. Hence as a complement or alternative, the present paper proposes the use of the LASSO (L1-penalized regression) to select the eigenvectors. The LASSO model selection procedure is applied to the well-known Boston housing dataset and simulation dataset, and its performance is compared with that of the stepwise procedure. The obtained results suggest that the LASSO is fairly fast compared the stepwise procedure, and can select eigenvectors effectively even if dataset is relatively large (n = 10000), to which the forward stepwise procedure is uneasy to apply.

Large-scale traffic simualtion for low-carbon city

This paper considers environmental city design using land use scenarios and large-scale traffic simulation. Low Carbon City (LCC) can be achieved by combining appropriate land use and transportation. We simulate the possible low carbon city by combining spatially explicit land use equilibrium (LUE) model and agent-based traffic model. First, land use scenarios of a city with different urban forms (compact and dispersed etc.) are created using the LUE model. Then the corresponding transportation is projected under each urban form with a large-scale traffic simulator for a case study city (Yokohama) in Japan. We also simulate the current traffic using the detailed person-trip data. Finally, we analyze the relationship between the urban form and the resulting CO2 emission both from land use and transportation are estimated. The proposed method can be a useful tool for urban planners to test some land use and transportation policies for designing sustainable cities.

The Car-Dependent Life

This chapter focuses on car dependence in people’s life. The authors first describe a new phenomenon about the decline in young people’s car ownership and usage by providing additional facts and insights based on literature review and a case study in Japan. Especially, the case study in Japan uses data from a longitudinal national household expenditure survey and confirmed that car ownership and usage decisions in Japan are more or less associated with decisions about other household expenditures. Second, recent research on shared mobility is reviewed from the perspective of smart use of cars. Third, existing studies on cars from the life-oriented consideration are described by looking at shopping behavior (both store-shopping and online shopping) and general purchasing behavior as well as electric vehicle ownership and usage. As for electric vehicles, the influence of lifestyle is explored. Fourth, car ownership and usage for an inclusive society are discussed, where low-income persons, children, and the elderly are focused on. Fifth, behavioral changes toward less dependence on car from a long-term perspective are illustrated. Finally, discussions on car dependence from the life-oriented perspective are given.

Effects of the Residential Environment on Health in Japan Linked with Travel Behavior

This paper aims to clarify how the residential environment is associated with overall health-related quality of life (QOL) via active travel (walking and cycling), by reflecting the influence of different trip purposes in Japan. The health-related QOL includes physical, mental, and social dimensions. For this study we implemented a questionnaire survey in 20 cities in Japan in 2010 and obtained valid answers from 1202 respondents. The residential environment is defined in terms of distances to and densities of different daily facilities extracted from both the survey and external GIS data. We found that the effects of residential environment on active travel behavior are mixed and limited, depending on types of trip makers. Unexpectedly, travel behavior has no direct effects on the health-related QOL. The residential environment, which is only observed indirectly via lifestyle habits for commuters, has limited effects on health. As for noncommuters, neither their travel behavior nor the residential environment influences their health-related QOL.

Urban Economics Model for Land-Use Planning

This chapter introduces our newly developed Spatially explicit Urban Land-use Model (SULM) as a tool for resilient urban planning. The SULM can create land-use and social economic scenarios at micro districts level based on an urban economic theory. In order to co-design transformative urban plans with local stake holders, it is important to visualize possible future land-use scenarios. This model makes it possible to endogenously project the residential choice of households, floor space and land area with considering location-specific disaster risk as well as economic and environmental factors. With this model, we can create scenarios for not only urban growth, but also urban shrinking, thus the method could be useful for both developing and developed countries’ situations. In this study, the model was developed and calibrated for the Tokyo Metropolitan Area (Greater Tokyo) at the micro-district level (around 1 km grid) and used to simulate possible land-use scenarios with different urban forms. We have specifically looked at the implications for climate change mitigation and adaptation capacities. This chapter explains mainly the tested three land-use scenarios; (1) Business as usual scenario, (2) Extreme urban compact city scenario, and (3) Combined mitigation and adaptation scenario. The scenarios were assessed with multiple criteria including disaster/energy resilience and environmental sustainability (CO2 emissions, urban climate) and economic benefits. The obtained results have shown that fairly large future economic costs could be saved by additionally considering adaptation (flood risk) in combination with mitigation (CO2 emissions) in the scenario that we call “Wise Shrinking”. Our research suggests that integration of resilience thinking into urban planning is important and promising.

An Integrated Model for Assessing Carbon Dioxide Emissions Considering Climate Change Mitigation and Flood Risk Adaptation Interaction

Planning for climate change mitigation/adaptation for enhancing urban resilience against natural disaster risks is an important issue in Japan. For such planning to be effective, studies suggest that it is important to consider the interaction (co-benefits and trade-offs) between adaptation and mitigation measures. For example, climate change mitigation and adaptation measures could be compatible if our government got people to move from flood prone areas with considering urban structure (e.g., compact city). In order to simulate the effectiveness of such interactions, we propose an integrated assessment model for carbon dioxide (CO2) emissions under several urban land-use scenarios considering (i) urban form (dispersion/compact city) (ii) urban resilience (adaptation to flood risks) and (iii) diffusion of electric vehicles (EVs) and photovoltaic (PV) panels at a local town level in Tokyo. The developed model can be used to evaluate the co-benefits of both mitigation and adaptation measures from the viewpoint of CO2 emissions. Indirect emissions based on households’ expenditure are also estimated in addition to direct emissions. The obtained results suggest that climate change mitigation and adaptation can generate a synergistic effect from the viewpoint of CO2 emissions.

Parking: Learning from Japan

The discussion of reforming parking pricing in Europe and the US suffers from a lack of imagination, as it is hard to envision a city with spatially and temporally strong variance in parking prices within short ranges of distance given the Western historical precedent. This paper is intended to help spark the imagination by presenting the case of downtown Hiroshima, where such a regulatory framework has already been in place for decades. It will map and describe the outcomes for the core of this metropolitan area of just over one million inhabitants. This description is supported by an explanation of the regulatory framework and a chronicle of the development of the number of parking spaces across the country. Parking prices vary by a factor of 25 during daytime hours on weekdays within this 8-km area. The highest rates shift location by 1.25 km from daytime to nighttime. Rates fall to zero where there is no demand.