curacao1 {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 (Conservation BN). The probabilities were given in the referenced paper (input nodes are given a uniform distribution). The vertices are:
- CulturalSiteProximity
(low, med, high);
- FloraRichness
(low, med, high);
- KeySpeciesPresence
(no, yes);
- NeighborhoodConservationValue
(low, high);
- NeighborhoodNaturalLandCover
(low, med, high);
- SpeciesRelatedConservationValue
(low, high);
- SuitabilityForConservation
(no, yes);
- VisitorDemand
(low, med, high);
- WatershedConservationValue
(low, high);
- WSAboveMarineProtectedArea
(no, yes);
- WSIncludesOtherKeyDesignations
(no, yes);
- WSIncludesRAMSARArea
(no, yes);
- WSLandscapeVariability
(low, med, 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.