GIS‑based hierarchical fuzzy MCDA framework for detecting critical urban areas in climate scenarios

In this research we propose a GIS-based multicriteria framework that implements a hierarchical MCDA fuzzy model aimed at the detection of urban areas at risk in climate hazard scenarios. The fuzzy-based multi-criteria approach adopted has the advantage of adapting to the hierarchical modeling of urban systems and of implementing the approximate reasoning adopted by decision makers. The criteria are defined in a hierarchical structure where the leaf nodes consist of fuzzy numbers; each node is assigned a weight, called coefficient of relative significance, which represents its relevance in the generation of the parent node in the upper level. The fuzzy set in the parent node is implemented through a fuzzy operator of intersection of the fuzzy sets of the child nodes. The framework was tested on a study area including densely populated neighborhoods in the municipality of Naples (Italy), with the aim of determining which subzones of the study area were most at risk in scenarios of heatwaves in the summer months. The results obtained are consistent with the results of the evaluations carried out by experts in the field.