Urban dynamics at regional scales has been increasingly important for economics, policies, and land use planning, and monitoring regional scale urban dynamics has become an urgent need in recent years. This study illustrated the use of time series nighttime light (NTL) data from the United States Air Force Defense Meteorological Satellites Program/Operational Linescan System (DMSP/OLS) to delineate urban boundaries and tracked three key urban changes: land cover change, population growth and GDP growth within Virginia. NTL data from different years were inter-calibrated to be comparable by using linear regression model and Pseudo Invariant Features (PIFs) method. Urban patches were delineated by applying thresholding techniques based on digital number (DN) values extracted from DMSP/OLS imagery. Compounded Night Light Index (CNLI) values were calculated to help estimate GDP, and these processes were applied in a time series from 2000 to 2010. Spatial patterns of DN change and the variation of CNLI indicate that human activities were increasing during the 10 years in Virginia. Accuracy of the results was confirmed using ancillary data sources from the U.S. Census and NLCD imagery. / Master of Science / Urban areas concentrate built environment, population, and economic activities, therefore, generating urban sprawl is a simultaneous result of land-use change, economic growth, population growth and so on. Remote sensing has been used to map urban sprawl within individual cities for a long time, while there has been less research focused on regional scale urban dynamics. However, the regional scale urban dynamics for economics, formulating policies, and land use planning has been increasingly important, and monitoring regional scale urban dynamics has become an urgent need in recent years. Here, we illustrated the use of multi-temporal United States Air Force Satellites data to help monitor urban sprawls by delineating urban patches and we measured a variety of urban changes, such as urban population growth and land cover change within Virginia based on the delineation. For doing so, digital number values, which measures the brightness of satellite imagery, were extracted and other relative index values were calculated based on digital number values, and these processes were applied in a time series from 2000 to 2010. Spatial patterns of digital number values change and the variation of another light index values indicate that human activities were increasing during the 10 years in Virginia.