A major impediment to effective management of soil and water resources in most agricultural and riverine environments of Australia is the lack of information on the spatial distribution of natural resources required for management planning and implementation. With respect to the soil resource the major problems are that traditional methods used for the acquisition of soil information, including soil survey, are time consuming and costly. The data collected is therefore usually sparse and because of time constraints was subjectively interpreted and therefore implications for land use management are uncertain.Numerical clustering algorithims such as fuzzy k-means (FKM) have over the last 15 years been used successfully to continuously classify multiple soil attributes. More recently, FKM combined with geostatistical methods have been used to create representations of the soil continuum using remotely sensed information such as Digital Elevation Model (DEM) and deep sensing electromagnetic (EM) data.The use of gamma radiometric data is increasingly being used to assist with the recognition of surface soil patterns. This is because gamma radiometric data, which consists of Potassium (K), Uranium (U), Thorium (Th) decay rates as well as the total radioactivity (i.e. Total Count-TC) of the soil and regolith, are related to the age and mineralogy of the soil.In this project, the aim is to explore the possible use of FKM analysis of gamma radiometric data (i.e. K, U, Th and TC in cps) and secondary data derived from a DEM to identify geomorphological and geological units and associated soil units within the Edgeroi district. The results suggest that the FKM approach, including the use of fuzzy performance index (FPI) and normalized classification entropy (NCE), provides a framework for identifying a small number of classes (c = 7) to investigate for interpretation. We conclude that the classes derived from radiometric data, were consistent with the known soil variability and broad geology and geomorphology of the Edgeroi district (i.e. erosional, depositional and dust-mantled plains). The best results were achieved within the depositional and dust-mantled plains where we were able to discern differences between the depositional Namoi floodplain and the first and second terraces from the third and fourth terraces of Namoi alluvium. The approach also discerned the location of the dust-mantled plains associated with the fourth and eroded fifth fans of local alluvium. The results with respect to the erosional landscape were equivocal.