Work

Identifying urban and rural settlement archetypes: clustering for enhanced risk-oriented exposure and vulnerability analysis

Year: 2025
Type: article
Abstract: . Identification of risks and vulnerabilities in urban areas is crucial for supporting city authorities in disaster risk reduction and climate change adaptation. Moreover, comparison of risk assessments across different cities may help effective allocation of adaptation funding towards more resilient and sustainable cities. The distinct physical, social, economic, and environmental characteristics of a city, along with the relevance of impending hazards, determine the level of risk and vulnerability faced by its residents. While the results of urban risk assessments will vary from one city to another, using general urban typologies (e.g. coastal cities, dryland cities, and inland or high-altitude cities) can effectively support in the understanding of risk in relation to its key drivers, helping to segmentate the complexity in otherwise too broad problem (Dickson et al., 2012). This study aims to reduce complexity in urban risk assessment at regional and national scale, ensure a baseline for comparison and identify potential hotspots in multi-hazard and multi-risk assessment frameworks. We propose a clustering methodology that groups urban settlements based on open-source data, used as proxies of urban vulnerability and exposure. Applying two widely used clustering techniques, we define 18 urban archetypes for the Italian territory, incorporating geographic, demographic, and socio-economic characteristics. These archetypes satisfy multiple validity dimensions of archetype analysis (Piemontese et al., 2022) and can serve as a valuable tool for policymakers. By providing a structured understanding of urban vulnerability profiles, they support the design of targeted interventions and urban resilience strategies tailored to specific risk conditions.
Language: English
Open Access status: gold
Estimated APC paid: $1,553
OpenAlex ID: W4414614652
FWCI: 16.17
Cites: 84
Cited by: 9
Related to: