<p>Spatial objects can be interconnected and mutually dependent in complex ways. In Geographical Information Science, spatial objects’ topological relationships are not discussed together with their attributes’ dependencies, and the vagueness of spatial objects is often ignored during the spatial modelling process. To address this, a spatial fuzzy influence diagram (SFID) is introduced. Compared to the traditional statistical or fuzzy modelling approach, the influence diagram brings advantages in helping decision-makers structure complex interdependency problems. A questionnaire was developed to evaluate the applicability of using an influence diagram in modelling spatial objects’ dependencies. As a case study, an SFID is applied to tree-related electric outages. The result of the case study is represented as a vulnerability map of electrical networks. The map shows areas at risk due to tree-related electric outages. The results were first validated by using a visual comparison of the vulnerability map and electricity fault data. In the second validation step, the percentage of fault data, which has received values in different vulnerability categories, was calculated. The results of the case study can be used to support the decision-making process of electrical network maintenance and planning.</p>

2017