China has been undergoing a remarkably rapid urbanization process in the last several decades. Urbanization is a complicated phenomenon involving imbalanced transformation processes, such as population migrations, economic advancements and human activity dynamics. It is important to evaluate the imbalances between transformation processes to support policy making in the realms of environmental management and urban planning. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime lights time series imagery provides a consistent and timely measure to estimate socioeconomic dynamics and changes in human activity. In this study, we jointly compared the annual ranks of three variables: the population, the gross domestic product (GDP) and the sum of weighted DMSP/OLS nighttime lights to estimate spatial and temporal imbalances in the urbanization processes of 226 cities in China between 1994 and 2011. We used ternary plots and a Euclidean distance-based method to quantitatively estimate the spatial and temporal imbalances between cities and to classify diverse urban development patterns in China. Our results suggest that, from 1994 to 2011, the imbalances of urbanization processes observed in the eastern, western and middle cities decreased, respectively, by 35.26%, 29.04% and 25.84%; however, imbalances in the northeast increased by 33.29%. The average decrement in imbalances across all urbanization processes in the 226 cities was 17.58%. Cities in the eastern region displayed relatively strong attractions to population, more rapid economic development processes and lower imbalances between socioeconomic and anthropogenic dynamics than cities in other regions. Several types of urban development patterns can be identified by comparing the morphological characteristics of temporal ternary plots of the 226 cities in China. More than one third (35.40%) of the 226 cities presented balanced states during the period studied; however, the remainder showed alternative urban development patterns.