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

Abstract. Identification of risks and vulnerabilities in urban and rural areas is crucial for supporting local authorities in disaster risk reduction and climate change adaptation. Moreover, comparison of risk assessments across different areas may help effective allocation of adaptation funding towards more resilient and sustainable communities. The distinct physical, social, economic, and environmental characteristics of a settlement, along with the relevance of impending hazards, determine the level of risk and vulnerability faced by its residents. While the results of risk assessments will vary from one settlement to another, using general settlement typologies (e.g. coastal cities, dryland cities, and inland or high-altitude cities) can effectively support the understanding of risk in relation to its key drivers, helping to segmentate the complexity in an otherwise too broad problem (Dickson et al., 2012). This study aims to reduce complexity in risk assessment of urban/rural settlements at regional and national scale, ensure a baseline for comparison and identify potential hotspots in risk assessment frameworks. We propose a clustering methodology that groups human settlements based on open-source data, used as proxies of urban vulnerability and exposure. Applying two widely used clustering techniques, we define 18 urban and rural 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 human settlements vulnerability profiles, they support the design of targeted interventions and resilience strategies tailored to specific risk conditions.