China is experiencing a rapid urbanization process and impervious surface is an important indicator to urban sprawl and its related economic and environmental issues. Multitemporal remote sensing, with the auxiliary of change detection methods, provides an efficient, consistent and economical means to monitor the impervious surface change. Traditional change detection methods require prior information to produce the change of impervious surface change, which is time consuming and labor cost. To tackle this issue, this paper presents an integrated approach to detect impervious surface change using satellite image (i.e., Landsat 8) and volunteered geographic information (i.e., Open Street Map). The presented approach was applied to map the impervious surface change in the city of Hefei, China. The results show that the presented approach was able to produce a satisfactory compared to supervised classification methods. The presented approach sheds new light to automatically map and estimate impervious surface change in a reliable and efficient way.