Disease caused by the soilborne plant pathogen Phytophthora cinnamomi causes long-term floristic and structural changes in native vegetation communities in Australia. Key components of the management of this disease are to know where it occurs and the rate at which it spreads. The distribution of P. cinnamomi has generally been assessed as locality points of infestation and mapping the extent of diseased vegetation in any area is difficult and costly. This study was undertaken in P. cinnamomi-infested heathland communities in southern Victoria, Australia, where the symptoms of P. cinnamomi arise as a mosaic within healthy vegetation. We investigated the potential to improve the efficiency and effectiveness of mapping and monitoring vegetation affected by P. cinnamomi using digital multi-spectral imaging. This technique was developed for the purposes of monitoring vegetation and provides a single, seamless ortho-rectified digital image over the total area of interest. It is used to spatially quantify small differences in the characteristics of vegetation. In this study, the symptoms of disease caused by P. cinnamomi infestation were related to differences in the imagery and were used to map areas of infestation. Comparison of the digital multi-spectral imaging indications with on-ground observations gave moderate accuracy between the datasets (κ = 0.49) for disease and healthy indications. This study demonstrates the ability of the technique to determine disease extent over broad areas in native vegetation and provides a non-invasive, cost effective tool for management.