A personal construct-based knowledge acquisition process for natural resource mapping

Abstract

This paper presents an iterative, structured knowledge-acquisition process for extracting human understanding of relationships between a natural resource and its environment. This understanding can then be used to map natural resources as spatial continua. The knowledge acquisition process is based on personal construct theory and consists of several iterations. Each iteration has five structured interview sessions: preparation, key development, description, comparison, and quantification. The knowledge derived from each iteration is represented as a set of membership functions that describes the degree to which a given environmental condition impacts the status of the given resource. The final set of membership functions, which is the final version of knowledge, is derived through the comparison and 'fusion' of the membership functions from each iteration. The comparison of the membership functions among different iterations is also used to measure the consistency (integrity) of an expert's understanding of the relationships. In a soil mapping case study, knowledge on soil-environment relationships was acquired from a local soil scientist using the knowledge acquisition process. The case study shows that knowledge sets extracted a year apart were consistent with each other. The study also shows that the soil expert was more familiar with the relationships between soils and some environmental variables than with other environmental variables. The expert's understanding about soil-environmental relationships also differed among soil series. Although it was designed to extract expert knowledge for mapping natural resources as spatial continua under a GIS environment, this knowledge elicitation process can be easily adapted to extract expert knowledge for other knowledge-based applications.