A Spatial Analysis Of the Distance Parameters in Seoul, Korea: With a Comparison between Gravity and Entropy Maximizing Models

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  • 空間的相互作用モデルにおける距離パラメータの地域パターンおよびそれに関連する社会・経済的特性
  • クウカンテキ ソウゴ サヨウ モデル ニ オケル キョリ パラメータ ノ チイ
  • ソウルの事例

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Many researchers have constructed various types of spatial interaction models including gravity, intervening-opportunity, electro-static field, multiple regression and entropy maximizing models. Among these models, the authors focused upon the distance parameters αi and βi of the gravity and entropy maximizing models (eqns. 2-4), and attempted to investigate empirically the spatial variation patterns and their causes of the distance parameters of the models in Seoul in comparison with them through the above two models.<br>For the purpose of this study, the 111×111 OD data on daily movement of persons within Seoul were employed by the two models, respectively. The distance parameter αi of each unit zone i in the gravity model was estimated by ordinary least square method and, on the other hand, the distance parameter βi in the entropy maximizing model was iteratively calculated with equation 6 derived by Hyman (1969). The results of this analysis can be summarized as follows:<br>1. The spatial variation patterns of the distance parameters αi and βi (in Figs. 2 and 3) indicate that Seoul can be devided into some distinct radii centering from the central business district. These two distance parameters show the far high values in the northeast radius and the low values in the west where the inner-suburban agricultural areas are existed. The intermediate values are revealed in the southeast radius.<br>2. Figure 4 shows the differences between the standardized values of the distance parameters yielded by the two models. Since zones with the remarkable difference are mainly located along the Han River across Seoul from east to west and around the Mt. Bughan in the north, it is considered that the natural topography should influence upon the spatial autocorrelation element in the distance parameter αi of the gravity model.<br>3. As the result of step-wise regression analysis to pursue the causes of the distance parameters in terms of some spatial socio-economic attributes, the percentage of employed persons in the primary industry and the level of income have effect on the both values of the distance parameters (Table 3 and 4). Only in the case of the gravity model, the percentage of employed persons in the secondary industry is considered as a kind of the cause which effects on the distance parameter αi. Though all of these three causes mentioned above decrease the distance parameter values, the percentage of employed persons of the primary industry is the most effective one.

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