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dc.contributor.authorJohnson, Sandra
dc.contributor.authorLow-Choy, Sama
dc.contributor.authorMengersen, Kerrie
dc.description.abstractBayesian networks (BNs) are becoming increasingly common in problems with spatial aspects. The degree of spatial involvement may range from spatial mapping of BN outputs based on nodes in the BN that explicitly involve geographic features, to integration of different networks based on geographic information. In these situations, it is useful to consider how geographic information systems (GISs) could be used to enhance the conceptualization, quantification, and prediction of BNs. Here, we discuss some techniques that may be used to integrate GIS and BN models, with reference to some recent literature which illustrate these approaches. We then reflect on 2 case studies based on our own experience. The first involves the integration of GIS and a BN to assess the scientific factors associated with initiation of Lyngbya majuscula, a cyanobacterium that occurs in coastal waterways around the world. The 2nd case study involves the use of GISs as an aid for eliciting spatially informed expert opinion and expressing this information as prior distributions for a Bayesian model and as input into a BN. Elicitator, the prototype software package we developed for achieving this, is also briefly described. Whereas the 1st case study demonstrates a GIS‐data driven specification of conditional probability tables for BNs with complete geographical coverage for all the data layers involved, the 2nd illustrates a situation in which we do not have complete coverage and we are forced to extrapolate based on expert judgement.
dc.publisherSociety of Environmental Toxicology and Chemistry
dc.relation.ispartofjournalIntegrated Environmental Assessment and Management
dc.subject.fieldofresearchApplied statistics
dc.subject.fieldofresearchChemical sciences
dc.subject.fieldofresearchEnvironmental sciences
dc.subject.fieldofresearchEnvironmental management not elsewhere classified
dc.subject.fieldofresearchBiological sciences
dc.titleIntegrating bayesian networks and geographic information systems: Good practice examples
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorLow-Choy, Sama J.

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