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

Land use change is a major driver of environmental degradation, necessitating appropriate planning to navigate trade-offs between societal objectives and ecological impacts. Sound planning is limited in some regions by data scarcity and incomplete scientific knowledge on local dynamics shaping development of land. In this paper, we present a novel expert -based participatory approach that uses Bayesian networks to determine land use suitability and potential conflicts for emerging land uses. This method encompasses a workshop phase for building suitability models for different sectors, data assembly and preparation, spatialization of networks, and iterative validation with experts. Mapped suitabilities for all land uses were used to assess potential competition for land across sectors and to quantify alignment of the expert -modeled outcomes with established land use policy. Applied to Cura & ccedil;ao, a data -poor environment in the Caribbean facing high land use competition, the method enabled the construction and parameterization of 5 Bayesian networks driven by 35 spatial input datasets generated through various methods from participatory mapping to social media analysis. Overlap in suitable locations for conservation and tourism development along segments of the coastline and roadsides of the western island highlight potential conflict stemming from coincidence of desirable natural amenities and ecologically sensitive areas. Results yield key insights that can drive discussion and inform policymakers and spatial planners as they navigate tradeoffs and seek optimal use of limited land resources. Process -based suitability predictions and knowledge of underlying drivers can also enable exploratory analysis into possible future scenarios of change.