Modelling ambiguity in urban planning
Binay Adhikari, Jianling Li · Annals of GIS · 2013
Most data related to urban and regional planning and the assessment of economic, environmental and social sustainability of a city or region have a spatial component. Some of these data are also inherently ambiguous in nature. Traditional Boolean logic in GIS lacks the capability to model the fuzziness, uncertainties and imprecision of data in geographic information and human decision-making processes. While considerable studies have investigated applications of fuzzy system in urban planning, only a few studies have attempted to integrate fuzzy inference within a GIS platform with the Mamdani method. To facilitate the efficient modelling and displaying of the imprecision of geographic data and human judgement, we develop a rule-based fuzzy inference system within ArcGIS environment using the Sugeno method. This article describes the development process of the system and demonstrates the usefulness of fuzzy logic application in urban planning. It concludes with a discussion of implications for urban planning and needs for further research.