Analyzing spatiotemporal characteristics of land-cover (LC) change is important for assessing environmental consequences of urban growth and supporting land management and planning. Less attention, however, has been given to the comparison between land-cover change patterns in developing and developed countries. In this study, Xuzhou city and Dortmund city region were selected as study areas. Multitemporal Landsat images were classified by using the integration method of maximum likelihood classifier, subpixel classifier, and multiple normalized difference vegetation index values based on Vegetation-Impervious Surface-Soil model. Urban growth patterns and processes of the two study areas were investigated and compared through land-cover change detection, buffer analysis, and jaggedness degree. The results indicated that the urban area in Xuzhou city increased more than threefold dramatically from 128.5 to 418.3 km2 , and the increased sprawling development trend was observed during the study period, while Dortmund city region showed a slight increase from 498 to 715.5 km2 in urban areas with an increasingly compact development trend. The results revealed a notable difference of spatiotemporal land-cover pattern dynamics between the two study areas as well as confirmed the effectiveness of the combined method of remote sensing and spatial analysis that can be used to support land management and policy decisions.