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Urban Transformation in China: From ...
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Han, Ruibo.
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Urban Transformation in China: From an Urban Ecological Perspective.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Urban Transformation in China: From an Urban Ecological Perspective./
作者:
Han, Ruibo.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2012,
面頁冊數:
289 p.
附註:
Source: Dissertation Abstracts International, Volume: 74-09(E), Section: A.
Contained By:
Dissertation Abstracts International74-09A(E).
標題:
Geography. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR98275
ISBN:
9780494982754
Urban Transformation in China: From an Urban Ecological Perspective.
Han, Ruibo.
Urban Transformation in China: From an Urban Ecological Perspective.
- Ann Arbor : ProQuest Dissertations & Theses, 2012 - 289 p.
Source: Dissertation Abstracts International, Volume: 74-09(E), Section: A.
Thesis (Ph.D.)--University of Ottawa (Canada), 2012.
Studying China's urbanization is an opportunity to contribute to the field of urban studies in an unprecedented manner. This complex urban system is examined using a hierarchical, top-down approach. At the highest level is a Macro-scale analysis of the national urban system, followed by a study of the regional urban system: the JingJinJi Metropolitan Area at the Meso-scale, and finally a Micro-scale examination with a focus on the city of Beijing. Since urban systems develop over both time and space, the urban system is analyzed spatio-temporally on all three levels.
ISBN: 9780494982754Subjects--Topical Terms:
524010
Geography.
Urban Transformation in China: From an Urban Ecological Perspective.
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Studying China's urbanization is an opportunity to contribute to the field of urban studies in an unprecedented manner. This complex urban system is examined using a hierarchical, top-down approach. At the highest level is a Macro-scale analysis of the national urban system, followed by a study of the regional urban system: the JingJinJi Metropolitan Area at the Meso-scale, and finally a Micro-scale examination with a focus on the city of Beijing. Since urban systems develop over both time and space, the urban system is analyzed spatio-temporally on all three levels.
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Research at the national scale is composed of two parts. First, the challenges and opportunities of China's urban development since the foundation of the People's Republic of China in 1949 are investigated in a general context. The institutional barriers that impede the management and continuation of China's urban development are also discussed. Rank-size Analysis and satellite images are used to present the structural transitions of city scaling and urban clusters. These changes come with a series of challenges that are also iterated and discussed. This is followed by an analysis of the spatial distribution and transition patterns of China's urban system using Centrographic Analysis, particularly since the post-1979 reforms. Second, the Macro-scale research focuses on a study of the urban hierarchy that is based on inter-city interactions as determined by the Synthesized Gravity Model (SGM). Under this model socioeconomic variables are synthesized and represented by the Influential Factor, while the Function Distance is derived from a Network Analysis that is based on multiple transportation methods. As an improvement on the conventional Gravity Model (GM), the SGM is used to accurately establish and represent the nodal structure of China's urban system, the evolution of its hierarchical structure, and the relationships that exist between the nodal structure and socioeconomic factors. The results based on the SGM indicate that China's national urban system is characterized by the emergence of urban clusters with stronger inter-city interactions since the 1990s. However, development among cities within certain urban clusters is not even, although the general pattern indicates a lessening inequality among cities. Spatially, while most cities at the top of the hierarchy are located in the east of China, cities in the middle and west of the country are also gaining higher positions in the hierarchy over time.
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On the Meso-scale, the applicability of the Cellular Automata (CA)-based SLEUTH model for regional urban growth pattern is studied through a focus on the JingJinJi Metropolitan Area (Beijing-Tianjin-Hebei). By integrating socioeconomic factors into a modified SLEUTH model, the urban growth dynamics and future development scenarios of the area are simulated and predicted. The results based on the CA model show that this region is characterized by a dynamic development pattern with high spreading and breeding growth rules that relies greatly on the growing transportation systems. It also allows for the projection of three possible future urban growth scenarios, each occurring under different environmental and development conditions, showing the future urban growth with or without further intervention. This research confirms that four factors play essential roles in the formulation of the urban growth mechanism of the JingJinJi Metropolitan Area: Urban policies, Industry restructuring, Rural-urban migration, and Reclassification of urban boundaries.
520
$a
The Micro-scale study of Beijing is conducted from two perspectives: the social and natural. The social aspect adopts the factorial ecology approach to identify the social landscape patterns and the factors that have shaped Beijing's social space in 1990 and 2000. The social mosaic has experienced a significant change due to suburbanization, resulting in a more dynamic and complex internal structure since the 2000s. From a natural perspective, Beijing's physical landscape patterns are extracted by processing remotely sensed images that have the same temporal span. The physical change through landscape metrics demonstrates that Beijing's expansion has generated a more complex and fragmented land use/cover pattern. Meanwhile, transportation systems play a significant role in urban expansion, although the expansion across the space (zonal rings and directional sectors) is not even. Finally, the relationship between the social and physical landscapes is quantitatively defined by the Geographically Weighted Regression (GWR) technique, using physical landscape metrics as dependent variables and social areas as independent variables. The GWR is able to demonstrate the relationship between the social and physical landscapes at this level: as a city's social mosaic becomes more varied over time it results in the fragmentation of that city's physical space. (Abstract shortened by UMI.).
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR98275
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