The ecological conditions of urban areas have been deteriorating in some aspects due to population growth and increasing expansion, with significant effects on human health. Impervious surface areas are an important indicator of urban ecological environmental change, therefore quickly and accurately estimating impervious surface areas is essential to monitoring the urban dynamics of change and human activities and their effects on urban environmental quality. Currently, few methods that are applied in estimating urban impervious surfaces are capable of providing results quickly and accurately. Accordingly, this study proposes a new index, named the normalized difference impervious index (NDII), based on Landsat TM images, which uses the visible (red, green, and blue) and thermal bands. The index was used to extract the impervious surface areas of Nanjing city, Jiangsu Province, China, and we assume that the average value of five times strict supervised classification is the true value of impervious surfaces. A combination of red and thermal bands extracted the impervious surfaces with a producer’s accuracy of 86.9%, a user’s accuracy of 84.6%, an overall accuracy of 91.4%, and a kappa coefficient of 0.8. The accuracy is 87.7% validated by high-resolution images. This method can rapidly extract urban impervious surface areas with promising accuracy.