Authors: Yuanshuo Xu*, Cornell University
Topics: China, Urban and Regional Planning, Spatial Analysis & Modeling
Keywords: Shrinking Cities, Urban China, Time-series Clustering, State Rescaling, Geographic Weighted Model
Session Type: Paper
Start / End Time: 3:05 PM / 4:45 PM
Room: 8212, Park Tower Suites, Marriott, Lobby Level
Presentation File: No File Uploaded
Shrinking cities has become one of the most critical challenges. Despite of being extensively studied in Western countries, this issue is lack of being addressed in the developing world, especially in rapidly urbanized China. In addition, urban changes are largely studied in non-scalar perspective. China’s urbanization model is primarily state-led at different scales, in which local government has played a critical role within its multilevel structure and state rescaling process. Led by a powerful central state, rescaling process in China is unevenly affecting urban development across space and time.
Therefore, this paper measures urban growth and shrinkage in China and explore its relationships with state rescaling. Using remote sensing data, and the city statistical Yearbook data, our study first developed a comprehensive metric system including demographic, economic, geospatial, and social service aspects of urban changes to capture the multi-dimensional urbanization process for all prefecture-level cities from 2006 to 2015. We further employed the Dynamic Time Warping technique and developed an algorithm for time-series clustering that can differentiate cities based on their urban trends. The diversity of urban trajectories is identified. Cities are found under continuous growth, continuous shrinkage, stabilized growth, stabilized shrinkage, recovery, decline, and cyclical growth or shrinkage. These different typologies are further examined in a geographical weighted statistical model to show the spatially varied impacts of state rescaling on urban development.