This study develops a spatially varying coefficient model by extending the random effects eigenvector spatial filtering model. The developed model has the following properties: its coefficients are interpretable in terms of the Moran coefficient; each of its coefficients can have a different degree of spatial smoothness; and it yields a variant of a Bayesian spatially varying coefficient model. Also, parameter estimation of the model can be executed with a relatively small computationally burden. Results of a Monte Carlo simulation reveal that our model outperforms a conventional eigenvector spatial filtering (ESF) model and geographically weighted regression (GWR) models in terms of the accuracy of the coefficient estimates and computational time. We empirically apply our model to the hedonic land price analysis of flood risk in Japan.

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This 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 ;0.348C in the dispersed-city scenario and decreased by ;0.18C 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 of the denser population. This result suggests that the compact-city form is not always appropriate for moderation of the urban-heat-island effect. This scenario would need to combine with other mitigation strategies, such as the additional greening of urban areas, especially in the central area. This study suggests that it is important to design a plan to adapt to higher urban temperatures, which are likely to ensue from future global warming and the urban heat island, from several perspectives; that is, designs should take into account not only climatological aspects but also impacts on urban inhabitants.

Abstract. Large-scale transportation projects such as the construction of a commuter railway accessible to metropolises have a significant regional impact. This study attempts to measure this impact using spatial statistical models and land price data. First, dynamic changes in the land price are analysed and the so-called announcement effect is presented using the spatial interpolation techniques. Second, various types of land price models are constructed by employing the existing methods of spatial econometrics and geostatistics; their estimates and project benefits are compared and discussed, particularly from the viewpoint of policy implications. JEL classification: C21, L92

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