bnRep (version 0.0.3)

curacao3: curacao Bayesian Networks

Description

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

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 (Urban fabric BN). The probabilities were given in the referenced paper (input nodes are given a uniform distribution). The vertices are:

AccessToPublicTransportation

(no, yes);

AirNuisance

(no, yes);

CoastalView

(no, yes);

LuxuryAmenities

(low, high);

NearbySupportingFunctions

(low, medium, high);

NeighborhoodFactors

(low, high);

NeighborhoodSafetyScore

(low, medium, high);

NoiseNuisance

(no, yes);

PollutedSoils

(no, yes);

PrimaryRoads

(no, yes);

ProximityToBeach

(no, yes);

ProximityToCoast

(far, near, immediate);

SiteFavorability

(low, high);

SlopeLimited

(no, yes);

SmallRoads

(no, yes);

SuitabilityForUrbanFabric

(no, yes);

TransportationAccess

(low, high);

ViewExtent

(low, medium, high);

ViewQuality

(low, high);

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.