The purpose of this study is to investigate the usefulness of variography for landscape change detection when applied to a time series of unclassified remote-sensing data. Specifically, the challenge was to identify and describe land-cover change, the result of rapid urbanisation, across a 12-year chronology of satellite images for which little temporally specific ground information was available. Using semivariograms, and the remote sensing technique of band-overlay for visual reference, the change in spatial extent of land-cover type, as well as feature richness (variance in reflectance values), was determined for Landsat and SPOT imagery obtained for the Sanya Region of Hainan, China in 1987, 1991, 1997 and 1999. Comparison of results with a traditional post-classification change trajectory confirms that time-series semivariograms are instructive at identifying general changes to land cover resulting from urbanisation. They are complementary of traditional post-classification approaches where sufficient in-situ and time-specific data exist; where these data are absent, the semivariogram approach to change analysis is recommended as a precursory tool for monitoring land-cover change.