臺灣都市階層體系變動趨勢之探討

A Study on the Trend of Urban Hierarchical Change in Taiwan

10.6128/CP.202103_48(1).0001

黃國慶(Kuo-Ching Huang)；詹士樑(Shih-liang Chan)；蘇冠臻(Kuan-Chen Su)；王姿懿(Tzu-Yi Wang)

都市階層體系 ； 空間互動模型 ； 都市衰退 ； urban hierarchy system ； spatial interaction model ； urban declining

都市與計劃

48卷1期（2021 / 03 / 31）

1 - 26

繁體中文

臺灣過去的經濟發展與產業結構改變，吸引人口從鄉村移向都市，促成都市的快速成長，6大直轄市人口達1600萬人，約佔全臺人數的70%，2014年住在都市計畫區內人口即接近80%，顯示臺灣都市化程度相當高。然而，根據國發會人口推估，臺灣總人口已達最高峰期，之後將呈現負成長趨勢。從遠距連結的觀點，都市與鄉村，或主領都市與其他都市間的推拉作用，以及維持高位階都市規模的政策，均可視為影響其他地區產生變化的驅動力，而如何因應中小型或衛星都市的衰退，勢必成為臺灣未來在整體都市體系與國土發展上的重要議題，也關乎臺灣的永續發展。本文應用空間互動模型模擬兩個情境下的人口分布，透過都市階層變動指標RMI（Rank Mobility Index; RMI）及空間聚集統計量Gi*，討論不同情境下面臨都市衰退的區域，呈現未來可能面臨明顯衰退的區位，期能提供都市發展政策訂定之參考。

Taiwan's past economic development and industrial structure changes have brought with the rapid growth of the urban areas, and caused the population movement from rural to urban areas. The population of the six major municipalities reached 16 million, accounting for 70% of the total number of people in Taiwan. In addition, the population living in the urban planning area is close to 80% in 2014, indicating that the high degree of urbanization in Taiwan. However, according to the population estimates of the National Development Council, the total population of Taiwan has reached the peak period, and will then turn to a negative growth trend. Under the influence of the push-pull between major municipalities and other areas, and the policy to maintain the scale of high-ranking cities, how to respond to the decline of small and medium-sized or satellite cities will become an important issue for Taiwan's overall urban system and national development in the future. It is also related to the sustainable development of Taiwan. This paper applies the spatial interaction model to simulate the population distribution for two scenarios. Through the urban rank mobility index (RMI) and the spatial association statistics Gi *, the clustered areas facing urban recession in different situations are discussed, and the trend simulation is compared with the policy simulation results. The results identify the areas that maight face a significant shrink in the future. It can provide the reference for further formulation of urban development policy.

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