||Impervious surface detection is significant to urban dynamic monitoring and environment management. One of the most effective approaches to evaluating the impervious surface is the use of nighttime light imagery. However, little work on this subject was carried out with the new generation nighttime light data from Luojia 1-01 satellite, which has a finer spatial resolution than the predecessors such as the nightlight data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite. Therefore, this study conducted the first investigation of the capacity of Luojia 1-01 nighttime light data in detecting the extent and degree of impervious surfaces. Focusing on three cities of Beijing, Shanghai, and Guangzhou, several maps of the spatial extent of impervious surface areas were first extracted from two types of nighttime lights data (Luojia 1-01 and NPP-VIIRS data) by applying a dynamic threshold segmentation method. Meanwhile, a series of polynomial regression models were adopted to estimate the relation between imperiousness degree and light intensity. The results compared with the reference data derived from Landsat 8 Operational Land Imager (OLI) show that Luojia 1-01 data can produce a more precise map of the spatial extent of impervious surfaces than NPP-VIIRS data owing to the finer spatial resolution and the wider measurement range. Nevertheless, Luojia 1-01 data failed to provide reliable estimates of the imperviousness degree in comparison with NPP-VIIRS data as this nighttime light imagery with finer spatial resolution can better discriminate the surfaces that have the same imperviousness degree but are illuminated with different light intensities, consequently resulting in a weak correlation between imperviousness degree and light intensity. The over- and under-estimates of imperviousness degree suggested an increase in spatial resolution of nightlight imagery does not always improve the accuracy and reliability of nighttime light-based estimations. These study results confirmed that Luojia 1-01 nightlight imagery is a potential and promising data source for mapping the spatial extent of impervious surface areas, but difficult to accurately estimate the imperviousness degree. Future research may improve the accuracy of imperviousness degree estimation by integrating the Luojia 1-01 nightlight imagery with other useful data sources.