Linking the results of remote sensing with production provide resource managers some flexibility for analyzing and monitoring spatial and temporal aspects of land-use. statistics to create land-use maps is problematic. This ar-Naturally, this has resulted in extensive research on landticle presents a technique that integrates two significant use and land cover mapping. Linking results of remote data sets relating to agricultural land-use, namely, sursensing with other geographically referenced information vey-based production statistics and vegetation growth (Estes, 1992), including production statistics, however, has profiles derived from satellite data. The article describes been problematic (Benie and Thomson, 1992), especially an application of this technique in which production data due to inconsistencies in geographical coverage. from an administrative survey are used to constrain the In this article, we present a technique, called SPREAD, classification of NDVI profiles of land cover classes. Befor generating a representation of current land-use in a cause the technique reallocates aggregated production timely and cost-effective manner. The procedure intestatistics consistent with low-resolution imagery and with grates two significant data sets relating to agricultural limited ground control information, it is a particularly land-use, namely, production statistics gathered through cost-effective method of extensive land-use mapping. periodic census and vegetation growth profiles derived Β©Elsevier Science Inc., 1998 from satellite data. This approach significantly enhances the usefulness of course resolution satellite data for rapid resource assessment and monitoring changes in the spa-*CSIRO Division of Wildlife and Ecology, Lyneham, Australia of agricultural land-use systems.