Modelling uncertainty in natural resource analysis using fuzzy sets and Monte Carlo simulation: slope stability prediction
Authors: Davis, Trevor J.; Keller, C. Peter
Source: International Journal of Geographical Information Science, Volume 11, Number 5, 1 July 1997 , pp. 409-434(26)
Publisher: Taylor and Francis Ltd
Abstract:The techniques of fuzzy logic and Monte Carlo simulation are combined to address two incompatible types of uncertainty present in most natural resource data: thematic classification uncertainty and variance in unclassified continuously distributed data. The resultant model of uncertainty is applied to an infinite slope stability model using data from Louise Island, British Columbia. Results are summarized so as to answer forestry decision support queries. The proposed model of uncertainty in resource data analysis is found to have utility in combining different types of uncertainty, and efficiently utilizing available metadata. Integration of uncertainty data models with visualization tools is considered a necessary prerequisite to effective implementation in decision support systems.
Document Type: Research Article
Publication date: July 1, 1997