Impervious surface area is a key factor affecting urbanization and urban environmental quality. It is of great significance to analysis timely and accurately the dynamic changes of impervious surface for urban development planning. In this study, we use a comprehensive method to extract the time series data on the impervious surface area (ISA) from the multi-temporal Landsat remote sensing images with a high overall accuracy of 90%. The processes and mechanisms of urban expansion at different political administration and direction level in the Nanjing metropolitan area are investigated by using the comprehensive classification method consisting of minimum noise fraction, linear spectral mixture analysis, spectral index, and decision tree classifiers. The expansion of Nanjing is examined by using various ISA indexes and concentric regression analyses. Results indicate that the overall classification accuracy of ISA is higher than 90%. The ISA in Nanjing has dramatically increased in the past three decades from 427.36 km2 to 1780.21 km2 and with a high expansion rate of 0.48 from 2000 to 2005. The city sprawls from monocentric to urban core with multiple subcenters in a concentric structure, and the geometric gravity center of construction land moves southward annually. The stages of urbanization in different district levels and the dynamic changes in different direction levels are influenced by the topographic and economic factors.
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