As important mechanisms of regional strategy and policy, prefecture-level regions have played an increasingly significant role in the development of China＇s economy. However, little research has grasped the essence o...As important mechanisms of regional strategy and policy, prefecture-level regions have played an increasingly significant role in the development of China＇s economy. However, little research has grasped the essence of the economic development stage and the spatio-temporal evolution process at the prefecture level; this may lead to biased policies and their ineffective implementations. Based on Chenery＇s economic development theory, this paper identifies China＇s economic development stages at both national and prefectural levels. Both the Global Moran I index and the Getis-Ord Gi＊ index are employed to investigate the spatio-temporal evolution of China＇s economic development from 1990 to 2010. Major conclusions can be drawn as follows. （1） China＇s economic development is generally in the state of agglomeration. It entered the Primary Production Stage in 1990, and the Middle Industrialized Stage in 2010, with a ＇balanced-unbalanced-gradually rebalanced＇ pattern in the process. （2） China＇s rapid economic growth experienced a spatial shift from the coastal areas to the the inland areas. Most advanced cities in mid-western China can be roughly categorized into regional hub cities and resource-dependent cities. （3） Hot spots in China＇s economy moved northward and westward. The interactions between cities and prefectures became weaker in Eastern China, while cities and prefectures in Central and Western China were still at the stage of individual development, with limited effect on the surrounding cities. （4） While the overall growth rate of China＇s economy has gradually slowed down during the past two decades, the growth rate of cities and prefectures in Central and Western China was much faster than those in coastal areas. （5） Areas rich in resources, such as Xinjiang and Inner Mongolia, have become the new hot spots of economic growth in recent years. For these regions, however, more attention needs to be paid to their unbalanced industrial structures and the lagging social d展开更多
The increasing availability of data in the urban context(e.g.,mobile phone,smart card and social media data)allows us to study urban dynamics at much finer temporal resolutions(e.g.,diurnal urban dynamics).Mobile phon...The increasing availability of data in the urban context(e.g.,mobile phone,smart card and social media data)allows us to study urban dynamics at much finer temporal resolutions(e.g.,diurnal urban dynamics).Mobile phone data,for instance,are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics.While previous studies often use call detail record(CDR)data,this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage.We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data.Specifically,urban areas’diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data.Urban areas are then classified based on the obtained signatures.The classification provides insights into city planning and development.Using the proposed framework,a case study was implemented in the city of Wuhu,China to understand its urban dynamics.The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone(TAZ)level.This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu.This article concludes with discussions on several common challenges associated with using network-driven mobile phone data,which should be addressed in future studies.展开更多
基金National Natural Science Foundation of China, No.41171107
文摘As important mechanisms of regional strategy and policy, prefecture-level regions have played an increasingly significant role in the development of China＇s economy. However, little research has grasped the essence of the economic development stage and the spatio-temporal evolution process at the prefecture level; this may lead to biased policies and their ineffective implementations. Based on Chenery＇s economic development theory, this paper identifies China＇s economic development stages at both national and prefectural levels. Both the Global Moran I index and the Getis-Ord Gi＊ index are employed to investigate the spatio-temporal evolution of China＇s economic development from 1990 to 2010. Major conclusions can be drawn as follows. （1） China＇s economic development is generally in the state of agglomeration. It entered the Primary Production Stage in 1990, and the Middle Industrialized Stage in 2010, with a ＇balanced-unbalanced-gradually rebalanced＇ pattern in the process. （2） China＇s rapid economic growth experienced a spatial shift from the coastal areas to the the inland areas. Most advanced cities in mid-western China can be roughly categorized into regional hub cities and resource-dependent cities. （3） Hot spots in China＇s economy moved northward and westward. The interactions between cities and prefectures became weaker in Eastern China, while cities and prefectures in Central and Western China were still at the stage of individual development, with limited effect on the surrounding cities. （4） While the overall growth rate of China＇s economy has gradually slowed down during the past two decades, the growth rate of cities and prefectures in Central and Western China was much faster than those in coastal areas. （5） Areas rich in resources, such as Xinjiang and Inner Mongolia, have become the new hot spots of economic growth in recent years. For these regions, however, more attention needs to be paid to their unbalanced industrial structures and the lagging social d
基金Under the auspices of the National Natural Science Foundation of China(No.41571146)China Postdoctoral Science Foundation(No.2019M651784)。
文摘The increasing availability of data in the urban context(e.g.,mobile phone,smart card and social media data)allows us to study urban dynamics at much finer temporal resolutions(e.g.,diurnal urban dynamics).Mobile phone data,for instance,are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics.While previous studies often use call detail record(CDR)data,this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage.We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data.Specifically,urban areas’diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data.Urban areas are then classified based on the obtained signatures.The classification provides insights into city planning and development.Using the proposed framework,a case study was implemented in the city of Wuhu,China to understand its urban dynamics.The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone(TAZ)level.This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu.This article concludes with discussions on several common challenges associated with using network-driven mobile phone data,which should be addressed in future studies.
