Resolving Uncertainty within the Inductive Environmental Model in Geographical Information Systems (GIS)

N. Suryana, D.N.C. Ling (Malaysia), and M. Molenaar (The Netherlands)


Inductive Environmental Model; Inference Processing Model; Uncertainty and Certainty Factor; Plausibility Reasoning; GIS


This paper discusses the application of Evidence Theory (plausibility reasoning) in a GIS for handling uncertainty ambiguity associated with experts' inference in predicting the occurrence of active processes in particular areas. Based on how a model used in a GIS is constructed, the Inductive Environmental Model (IEM) is classified as a logical or inference processing model. By this is meant that this logical model is not based on a mathematical formula and does not admit to the application of error propagation theory. In this regard, the proposed IEM more closely represents the working of environmental expert than does the USLE mathematical model. Datasets on locational active processes (erosion class), influential related factors and their Certainty Factor (CF) obtained from the study area were used to provide an example of how the uncertainty ambiguity associated with the IEM can be handled in a GIS environment.

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