Skip to main content
The Application of Data Mining Techniques to Characterize Agricultural Soil Profiles
ECU Publications Pre. 2011
  • Leisa Armstrong, Edith Cowan University
  • D Diepeveen, Department of Agriculture and Food
  • R Maddern, Edith Cowan University
Publication Date
Document Type
Conference Proceeding
Australian Computer Society Inc
Computing, Health and Science
Computer and Information Science

This article was originally published as: Armstrong, L. , Diepeveen, D., & Maddern, R. (2007). The application of Data Mining techniques to characterize agricultural soil profiles. Proceedings of Australasian Data Mining Conference (AusDM'07). (pp. 85-99). Gold Coast, Australia. Australian Computer Society Inc. Original article available here

The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data; this has lead to new methods and techniques such as data mining that can bridge the knowledge gap. This research aimed to assess these new data mining techniques and apply them to a soil science database to establish if meaningful relationships can be found. A large data set extracted from the WA Department of Agriculture and Food (AGRIC) soils database has been used to conduct this research. The database contains measurements of soil profile data from various locations throughout the south west agricultural region of Western Australia. The research establishes whether meaningful relationships can be found in the soil profile data at different locations. In addition, comparison was made between current data mining techniques such as cluster analysis and statistical methods to establish the most effective technique. The outcome of the research may have many benefits, to agriculture, soil management and environmental
Access Rights


Citation Information
Leisa Armstrong, D Diepeveen and R Maddern. "The Application of Data Mining Techniques to Characterize Agricultural Soil Profiles" (2007)
Available at: