A Rule‐based System to Map Soil Properties

Abstract

AbstractConventional soil mapping is limited in its capabilities in that it presents a summary of the soil surveyor's conceptual view of soil variation. As such, the method conveys little regarding what is known about the variation of individual soil properties, or the quantitative nature of their variation. We developed a new method for soil mapping, based on the concepts employed in the PROSPECTOR mineral exploration system, which builds on existing soil surveyor knowledge to construct quantitative statements about individual soil properties via the development of a network of rules. These rules operate within a system of Bayesian inference to assign the varying probability of occurrence of a soil property of interest within an area, given evidence that relates to it in a known way. Permissible evidence includes the range of attributes normally used by a soil surveyor, such as landform, vegetation, land use, or parent material, and can also include remotely sensed digital data. Evidence is weighted according to the uncertainty associated with it, and combined to produce a single estimate of probability of a given attribute. The relationship between the evidence and prediction is stated explicitly at each stage of the procedure and is thus repeatable in a consistent manner. The system has the advantage that while it does not discard the evidence and knowledge used in conventional soil survey, it produces quantitative estimates of the distribution of soil properties, which can be used for a wide range of applications. The data produced is amenable to storage in geographic information systems and related data bases. As such, it can be updated or enhanced as new information or knowledge becomes available.