Access to detailed knowledge about soil and its properties is essential to a range of activities, e.g. precision farming, handling of contaminated soils and management of soils with varied fertility. The high costs involved in acquiring and compiling detailed soil data in classical soil mapping activity is a barrier to the implementation of detailed soil data driven management.

To address this issue, we focus our research efforts on developing cost-effective methods for scientists, farmers and others to access soil information using technologically advanced but easily used digital soil maps. Digital soil maps are computer-assisted statistically produced maps of soil types and soil properties.

We employ digital mapping techniques that are based on the covariance between a range of "low-cost" variables such as digital elevation models and their derivatives. Ongoing projects enhance our understanding of and ability to measure these variables through the development and testing of mobile proximal soil sensors.

The data is converted into digital soil maps using geo-statistical and predictive mapping methods. Ther resulting digital maps are flexible tools useable at the field level as well as the regional and even national scales.