SPATIAL ANALYSIS OF THE DISTANCE PARAMETER OF THE SPATIAL INTERACTION MODEL WITHIN THE TOKYO METROPOLITAN AREA

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This study focuses on the distance parameter that is an indispensable component of a spatial interaction model. Though recent theoretical studies on the distance parameter have proposed the behavioral, configurational and spatial autocorrelation components in the parameter, empirical studies have, for the greater part, discussed the parameter re flecting the spatial autocorrelation and scarecely taken into account both of the behavioral and configurational components. In this study as an empirical one, an attempt is made, first, to extract a spatial pattern of the distance parameter prescribed only by the behavioral and configurational components and then, to pursue the causes of that pattern, by taking zonal attributes into con sideration. The production-constrained entropy-maximizing type of spatial interaction model (Egns. (2) to (4)) is employed to the car-traffic flows within the Tokyo metropolitan area (Fig. 1). The results of this study are summarized as follows: 1. The modified Hyman's procedure including the iterative calculation based on the Eqns. (5) to (8) was utilized to estimate the distance parameter βi of each unit zone i. Then, the cluster analysis by the relative likelihood ratio λij in Eqn. (9) was executed to extract a spatial pattern of the distance parameter (Fig. 2). As a result, the distance parameter increases its value from the inner part to the outer part within the Tokyo metropolitan area (Fig. 3 and Table 1). Since the extracted pattern showed marked differ ence from the pattern affected only by the configurational component, the extracted pattern was strongly affected by the behavioral component. 2. In order to explain the extracted pattern, specific tonal attributes which affect the behavioral component was seeked. After thirteen location quotients which show industrial concentration were prepared, a multiple regression model, in which some of them should be selected as independent variables and the distance parameter was a dependent variable, was formulated by a step-wise procedure. As a result, the regression model included four location quotients. These location quotients were referred to the industries of transport and communication, services, wholesales and government (Table 2). These location quotients were mapped in Fig. 4. The standardized regression coefficients in Table 2 showed that the industrial concentrations of transport and communication, services and wholesales reduced the distance parameter value, while the concentration of government increased it. 3. The residuals (Fig. 5) by the regression model were explained by the accessibility to the freeway network (Fig. 6). First, the unit zones were divided into A and B-groups the A-group consisted of zones with accessibility which was equal to or less than a given accessibility D0, and the B-group of zones with accessibility which was greater than D0. Second, the average values of the residuals in each group were calculated. Finally, the significant level of the difference between the two averages was evaluated by a variance test. These processes were repeated at intervals of 0.5km of Do. The differences at the 20% significant level existed at the five cases of Do. Especially the case with D0=4.5 showed the difference at the 5% level (Table 3). Hence, zones more accessible to the freeway network had lower distance parameter value, while zones with less accessibility did higher distance parameter value.
The Association of Japanese Geographersの論文

SPATIAL ANALYSIS OF THE DISTANCE PARAMETER OF THE SPATIAL INTERACTION MODEL WITHIN THE TOKYO METROPOLITAN AREA

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