A predictive model has been established and tested to account for variations in the landscape to reflect changes in agricultural land capability class (on a progressive rating of 1: good - 7: poor). This dataset (and map) provides a prediction of the most likely land capability class to be expected in a particular location based on several layers of readily available information. These layers included geology, rainfall, slope, elevation, forest cover and surface drainage status. These data layers were input into a Geographic Information System modelling framework. Using previous experience and limited visits in the field, the output has been produced as a digital dataset and 1: 100,000 map. It was found to provide a relatively good impression of the landscapes potential for agricultural persuits (ie cropping and grazing). It was found to represent changes in capability class very well where geology, climate or slope control capability. In those areas where subsurface drainage controlled land capability it was found to be less reliable. Overall however as these areas of the State were previously devoid of any broadscale land resource information for this purpose - this map provides a valuable fist step in discerning land capability.
