ABSTRACT
Understanding urbanization dynamics, or how intensity of urbanization changes over time, is an important basis for urban planning and management, which has been investigated using various data-driven approaches. Considering the advantages and constraints of different data sources, we use pixel-based, time-series night-time light (NTL) trajectories to characterize urbanization dynamics in mainland China where massive urban development has been occurring in recent decades. After pre-processing the data, we extracted time-series NTL trajectories for each 1 km × 1 km pixel between 1992 and 2013 and used the unsupervised k-means classification to identify the major typologies of these trajectories as urbanization dynamics based on their main statistical parameters. The classification identified five urbanization dynamics, namely, stable urban activity, high-level steady growth, acceleration, low-level steady growth, and fluctuation. Their distributions and spatial patterns were further summarized and compared among different Chinese administrative divisions. We specifically analysed the acceleration trajectories that showed rapid transitions from rural to urban, as we considered these trajectories as potential indicators for aggressive urbanization. We found several clusters at prefecture city and county levels with high proportion of the acceleration, and referred to the underlying socioeconomic characteristics and developmental history to understand how these clusters could had been formed. Through this study, we revealed the dominant tendencies of urbanization in China over space and time, and developed an analysis framework that could be extended to other regions.
