Learn R Programming

bnRep (version 0.0.3)

curacao4: curacao Bayesian Networks

Description

Supporting spatial planning with a novel method based on participatory Bayesian networks: An application in Curacao.

Arguments

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

Format

A discrete Bayesian network to determine land use suitability and potential conflicts for emerging land uses (Conventional agriculture BN). The probabilities were given in the referenced paper (input nodes are given a uniform distribution). The vertices are:

AgriculturalDensity

(low, med, high);

AllRoadAccess

(no, yes);

BuiltUpDensity

(low, med, high);

CoUserInteractionConstraints

(low, high);

EnvironmentalConstraints

(yes, no);

Geology

(colluvial clay, diabase or other, limestone bare rock);

GroundwaterDepth

(less than 25m, between 25 and 60m, over 60m);

InfrastructureConstraints

(low, high);

ProductivityConstraints

(low, high);

SiteConstraints

(low, high);

Slope

(flat, moderate, steep);

SuitabilityConventionalAgriculture

(no, yes);

UtilitiesAccess

(no, planned, yes);

References

Steward, R., Chopin, P., & Verburg, P. H. (2024). Supporting spatial planning with a novel method based on participatory Bayesian networks: An application in Curacao. Environmental Science & Policy, 156, 103733.