An uneven distribution of rainfall and the higher rate of evaporation cause frequent droughts in southern Africa. Previous studies have shown that it is difficult to monitor droughts in real time by monitoring rainfall anomalies. Alternatively, a method to estimate the variation of surface soil moisture would be useful to help monitor droughts. This research explored the potential of using ASTER imagery to map the variation in moisture conditions in crop fields at a given time. ASTER imagery acquired on April 18, 2004 (i.e., around the harvesting time) near Pretoria, South Africa was used for this study. Thermal and reflective data were combined and used in the Vegetation Index (VI) - Land Surface Temperature (LST) triangular method to map the relative variation in moisture conditions in the study area. Modified Soil Adjusted Vegetation Index (MSAVI) from the Visible and Near Infra Red (VNIR) bands and land surface temperature from the Thermal Infra Red (TIR) bands were used as VI and LST respectively. The initial results were compared with the South African Development Community (SADC) precipitation data and US Geological Survey regional Water Requirement Satisfaction Index (WRSI). These results indicate that ASTER imagery has the potential to be used in a decision support system to estimate surface moisture.