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Abstract This article contributes to developing an indicator-based vulnerability assessment framework for cultural heritage sites. It provides a vulnerability index for heritage sites potentially exposed to multiple hazards, including sudden-onset and slow-onset hazards, while considering climate change influences. Through determining particular criteria and indicators, the Cultural Heritage Vulnerability Index incorporates structural and non-structural factors of the heritage site and its local and national settings. The assessment procedure was applied to the case of the Roman Ruins of Tróia in Portugal. The findings highlight those areas of sensitivity (e.g., the existing deterioration patterns and types of foundation) and coping and adaptive capacities (e.g., institutional setting and response plan) that significantly contribute to the level of vulnerability and risk. The results of vulnerability assessment will further enable determining priorities and developing risk mitigation and preparedness measures, in particular reducing structural sensitivity and promoting coping capacities.

The resilience measurement focuses on urban shocks and stresses, which are excluded from current spatial resilience assessments. As a result, existing literature suggests that research in secondary cities of the global south is needed to understand better spatial resilience in the face of multivariate, intersecting, and uncertain challenges. This study aims to determine the factors affecting the spatial resilience of Ethiopia's secondary cities to urban uncertainties using household perceptions of Kombolcha city. The study collected empirical data through questionnaires and key informant interviews, and then analyzed those using SPSS and the Analytic Hierarchy Process. Accordingly, seventeen environmental and physical urban problems affecting the spatial resilience of the country's secondary cities were identified. Deforestation, surface flooding, landslides, poor solid waste management, and inadequate drainage facilities were perceived as top priority urban problems in Kombolcha city with the respective values of 19.73%, 13.02%, 12.70%, 7.59%, and 6.82% of the four hundred sampled households. However, water scarcity and wind-related shocks, scoring 1.48% and 1.89%, respectively, were the least recurring urban problems. The city's spatial resilience is further limited by unsustainable material and resource consumption, a lack of infrastructure, poor transportation system conditions, poor implementation of response measures: lack of appropriate planning, and non-long-lasting biophysical measures. The household perception also showed that the urban uncertainties are severe in the city, with a 49.48% response rate. The findings also revealed a relationship and commonalities amongst the problems exacerbated by land-use zoning changes and the thriving informal settlements. The study implied that improving secondary cities' coping, adaptation, and governance systems are critical for mitigating the perceived urban problems and making cities spatially resilient. Thus, the study's spatial planning implications are that local governments in secondary cities commit to localizing international initiatives, strictly establishing and enforcing local resource utilization strategies, and improving living conditions in their cities.

Reducing vulnerability is essential for adaptation to climate change. Compared to approaches that examine vulnerability to a specific hazard, our analysis offers an alternative perspective that conceptualizes vulnerability to climate change as a phenomenon that is independent of any specific type of hazard but relevant to multiple hazards. Vulnerability is thus a product of structural inequality and systemic in nature. Based on two established index systems, we perform global analyses of specific phenomena—such as poverty, access to basic infrastructure services and forced migration—that influence and determine vulnerability. Our statistical and spatial analyses reveal an emerging pattern of climate vulnerability within regional clusters and shows that vulnerability is a transboundary issue, crossing political, sectorial and geographical borders and impacting shared resources. The spatial statistical hotspot analysis of vulnerability underscores that hotspots, for example of high vulnerability, state fragility, low biodiversity protection or forced migration, emerge in multi-country clusters. This aspect has often been overlooked, most attention to-date having been given to the positioning of individual countries within vulnerability rankings. In hotspots such as in the Sahel, East and Central Africa, as well as in Southern Asia and Central America, vulnerability is interwoven with high levels of state fragility, making adaptation solutions more complex. The recognition of the regional clusters and the transboundary nature of vulnerability calls for new research and action on how to strengthen transboundary approaches for vulnerability reduction, potentially enhancing prospects for successful adaptation.

Tsunami hazard can be analyzed from both deterministic and probabilistic points of view. The deterministic approach is based on a “credible” worst case tsunami, which is often selected from historical events in the region of study. Within the probabilistic approach (PTHA, Probabilistic Tsunami Hazard Analysis), statistical analysis can be carried out in particular regions where historical records of tsunami heights and runup are available. In areas where these historical records are scarce, synthetic series of events are usually generated using Monte Carlo approaches. Commonly, the sea level variation and the currents forced by the tidal motion are either disregarded or considered and treated as aleatory uncertainties in the numerical models. However, in zones with a macro and meso tidal regime, the effect of the tides on the probability distribution of tsunami hazard can be highly important. In this work, we present a PTHA methodology based on the generation of synthetic seismic catalogs and the incorporation of the sea level variation into a Monte Carlo simulation. We applied this methodology to the Bay of Cádiz area in Spain, a zone that was greatly damaged by the 1755 earthquake and tsunami. We build a database of tsunami numerical simulations for different variables: faults, earthquake magnitudes, epicenter locations and sea levels. From this database we generate a set of scenarios from the synthetic seismic catalogs and tidal conditions based on the probabilistic distribution of the involved variables. These scenarios cover the entire range of possible tsunami events in the synthetic catalog (earthquakes and sea levels). Each tsunami scenario is propagated using the tsunami numerical model C3, from the source region to the target coast (Cádiz Bay). Finally, we map the maximum values for a given probability of the selected variables (tsunami intensity measures) producing a set of thematic hazard maps. 1000 different time series of combined tsunamigenic earthquakes and tidal levels were synthetically generated using the Monte Carlo technique. Each time series had a 10000-year duration. The tsunami characteristics were statistically analyzed to derive different thematic maps for the return periods of 500, 1000, 5000, and 10000 years, including the maximum wave elevation, the maximum current speed, the maximum Froude number, and the maximum total forces.

Conceptual frameworks are vital for identifying relevant components, dimensions and indicators to assess vulnerability to natural hazards and climatic change. Given the fact that vulnerability is applied and used in various disciplines and by multiple schools of thought, several conceptual frameworks to assess and conceptualise vulnerability have been developed. Even though these frameworks have been widely cited in research, the range and context of application and contextual use of such frameworks have rarely been explored. This paper provides a systematic review of the MOVE (Methods for the Improvement of Vulnerability Assessment in Europe) framework. Bibliometric and systematic analyses were performed to better understand who and how the MOVE framework has been taken up by other researchers. The MOVE framework has been widely cited in different research fields. Several studies directly used the framework for assessing vulnerability both in terms of its factors and the different thematic dimensions of vulnerability (e.g. social, physical, ecological). Some studies have used it as a basis for developing context-specific studies of vulnerability and risk assessment frameworks. Finally, we also discuss critiques of the MOVE framework that can provide direction for future vulnerability assessments. Contribution: Critique of the MOVE framework can be helpful in further improvement and development of a multi-hazard holistic framework that would be flexible enough to support multiple theoretical perspectives in disaster risk and climate change discourses.

Abstract Within the framework of disaster risk management, this article proposes an interdisciplinary method for the analysis of multiple natural hazards, including climate change’s influences, in the context of cultural heritage. A taxonomy of natural hazards applicable to cultural heritage was developed based on the existing theoretical and conceptual frameworks. Sudden-onset hazards, such as earthquakes and floods, and slow-onset hazards, such as wetting–drying cycles and biological contamination, were incorporated into the hazard assessment procedure. Future alteration of conditions due to climate change, such as change in heat waves’ duration, was also taken into account. The proposed hazard assessment framework was applied to the case of the Historic Centre of Rethymno, a city on the northern coast of the island of Crete in Greece, to identify, analyze, and prioritize the hazards that have the potential to cause damage to the center’s historic structures. The assessment procedure includes climate model projections, GIS spatial modeling and mapping, and finally a hazard analysis matrix to enable the sharing of a better understanding of multiple hazards with the stakeholders. The results can facilitate decision making by providing the vulnerability and risk analysis with the nature and spatial distribution of the significant hazards within the study area and its setting.

Socio-economic indicators are key to understanding societal challenges. They disassemble complex phenomena to gain insights and deepen understanding. Specific subsets of indicators have been developed to describe sustainability, human development, vulnerability, risk, resilience and climate change adaptation. Nonetheless, insufficient quality and availability of data often limit their explanatory power. Spatial and temporal resolution are often not at a scale appropriate for monitoring. Socio-economic indicators are mostly provided by governmental institutions and are therefore limited to administrative boundaries. Furthermore, different methodological computation approaches for the same indicator impair comparability between countries and regions. OpenStreetMap (OSM) provides an unparalleled standardized global database with a high spatiotemporal resolution. Surprisingly, the potential of OSM seems largely unexplored in this context. In this study, we used machine learning to predict four exemplary socio-economic indicators for municipalities based on OSM. By comparing the predictive power of neural networks to statistical regression models, we evaluated the unhinged resources of OSM for indicator development. OSM provides prospects for monitoring across administrative boundaries, interdisciplinary topics, and semi-quantitative factors like social cohesion. Further research is still required to, for example, determine the impact of regional and international differences in user contributions on the outputs. Nonetheless, this database can provide meaningful insight into otherwise unknown spatial differences in social, environmental or economic inequalities.