curacao5 {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 (Structural 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);
- SuitabilityStructuralAgriculture
(no, yes);
- UtilitiesAccess
(no, planned, yes);
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.