# Hierarchical Fuzzy MCDA Multi-Risk Model for Detecting Critical Urban Areas in Climate Scenarios
###### Abstract
Furthermore, when the analyzed ecosystem consists of an urban settlement, the assessment of vulnerability to climate hazards is difficult because of the co-presence of the different elements of which it is composed and their interrelationships. In recent years, many researchers have proposed models to assess the vulnerabilities of cities to various climate events. A primary role in the assessment of climate vulnerability in urban settlements is managed by the spatial modeling scale of the city, on which the information detail to be acquired and the forecasting and simulation approaches to be used depend [10]. The typology and geomorphology of the urban settlement are also primary characteristics to take into consideration since, depending on the typology of the city and its geomorphological typification, different responses are generated to documented stresses and adverse climatic phenomena. For example, although coastal cities in hot periods are cooler than nearby inland cities, they may be warmer than nearby cities in rural areas if the presence of buildings prevents the flow of sea breezes [11]. A serious critical point of climate vulnerability models in urban settlements is the uncertainty or limitation of the available data. In [12], a climate vulnerability model based on a set of geomorphological and social indicators in coastal cities under rapid urbanization is proposed; the results carried out on a set of different expanding coastal cities show that the lack of detailed data at a local scale prevents the assessment of vulnerability to local climatic phenomena. An attempt to carry out climate vulnerability assessments that can be used in different countries and consider different sectors has been proposed in [13], where the authors propose a composite climate vulnerability index in which endogenously generated weights are used to aggregate six different vulnerability indices; these weights differ locally from sector to sector and from country to country. However, as the results of statistical tests carried out show, further variables and indices would be necessary to obtain information relating to the variation in climate vulnerability across nations. Thismay be necessary for the study of climate vulnerability in urban settlements, where the urban system and its microclimate need to be modeled [14]. MCDA models have recently been proposed to evaluate climate vulnerability in the presence of different hazard scenarios. They facilitate the identification of the most vulnerable areas of the area of study, considering a large number of climatic, geomorphological, environmental, and socio-economic characteristics. In [15], an MCDA model is applied to evaluate vulnerability to drought scenarios in the Namakkal district, India. The model was implemented on a GIS platform using the Analytic Hierarchy Process (AHP) method [16; 17]. A multicriteria model based on a fuzzy-based AHP model [18] in which triangular fuzzy numbers are used to assign the weights is proposed in [19] to evaluate the alluvial areas most vulnerable to flooding phenomena; the model is applied to evaluate flood vulnerability in AqQala county in Iran, taking into consideration the topographical, geomorphological, climatological, and social characteristics of the area. A MCDA model based on AHP was proposed in [20] for studying the risks of wildfire outbreaks in the northeast and northern regions of Ghana. This model is computationally fast but does not take into account the city-scale characteristics needed to assess the vulnerabilities of buildings and impervious open spaces. In [21], an AHP-based MCDA model is applied to assess the vulnerability of coastal cities to erosion. The model considers a set of environmental and human activity criteria to evaluate the most vulnerable cities. The model was tested in the coastal city of Kuala Terreganu, Malaysia, producing reliable results. Its main limitation is that it is not portable to other urban settlements, as the hierarchy of criteria was built considering the local characteristics of Kuala Terreganu.