Mapping impervious surfaces over regional or continental scale study areas with high spatial resolution imagery is difficult due to the cost and time involved in processing the large number of images required. This study investigated the benefits of using the coarse spatial resolution, high temporal resolution MODIS sensor to produce impervious surface maps. MODIS NDVI data for multiple years were analyzed with two multi-temporal image analysis methods: the Sequential Maximum Angle Convex Cone and Linear Spectral Unmixing. Impervious surface maps were generated and compared with a set of reference data and a Landsat-derived impervious cover map. The mapping accuracies for the algorithms used were generally good, particularly for the LSU approach, which was able to identify areas with 50-60% impervious cover at 77% accuracy and areas with a cumulative impervious cover of 50% or greater at 80% accuracy. The methods presented in this paper have potential for mapping impervious cover over large areas where the use of higher spatial resolution data is impracticable.