curacao3 {bnRep} | R Documentation |
curacao Bayesian Networks
Description
Supporting spatial planning with a novel method based on participatory Bayesian networks: An application in Curacao.
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);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
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.