||Quantifying the spatial and temporal changes of urban extent is important for understanding the burgeoning process of urbanization. Numerous well-performing methods have been used to map urban areas and detect urban changes using nighttime light data, but many of these methods assume that the urban area is equivalent to regions with high percentages of impervious surfaces or developed land. We present an approach to efficiently map urban areas at the regional scale, which also provides opportunities to recognize urban extents from different theoretical perspectives. In our approach, appropriate demarcating criteria and urban indicators were chosen based on understanding the current state of urbanization of the study area. After object-based segmentation and detection of initial urban centers, urban patches are discerned by expanding from these initial urban centers through a grouping algorithm, delineating the relative fringes of the urban area. We tested this new approach for mainland China, using 2010 Defense Meteorological Satellite Program/Operational Linescan System nighttime light data and county-level administrative units. We found a total urban area of 146,806 spread across 2489 counties and amounting to 1.5% of the land in mainland China. The delineated boundary of the urban patches had different values by compass direction. Mean values of fringes and sizes of different urban patches varied greatly across regions. We detected all provincial capitals, 97.3% of the prefecture-level cities and 91.0% of the county-level cities. This approach is thus capable of identifying urban patches with reliable accuracy at the regional scale.