An Integrated Multidimensional Risk Framework for Volcanic Hazard Zones: Insights from Mt. Vesuvius, Italy

An Integrated Multidimensional Risk Framework for Volcanic Hazard Zones: Insights from Mt. 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Vesuvius, Italy Isabella Lapietra, Federico Benassi, Thaís García-Pereiro, Anna Paterno, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8146557/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Mt. Vesuvius, in Campania Region (Southern Italy), is considered one of the world’s most dangerous volcanoes due to its probability of future explosive eruptions in a densely populated area. When large populations or significant assets are exposed to volcanic hazards and exhibit high vulnerability, the potential for disaster increases. Consequently, combining volcanic hazard with demographic, social and building characteristics is essential to manage disasters. The present research applies an integrated multidimensional and multisource framework for risk analysis, based on diverse geospatial datasets, by exploring the relationship between long-term volcanic hazard (pyroclastic density currents), human population features (population exposure and social vulnerability) and building characteristics (building exposure and physical vulnerability). The challenge of this approach is to standardize the metrics belonging to physical hazard with those of potential vulnerability and exposure (which derived from different measures), to investigate the volcanic risk spatial distribution. Using cartographic and statistical methods at the Enumeration Area level, the framework identifies and prioritizes zones requiring focused mitigation strategies. The resulting risk map shows that the highest-risk areas (levels 4 and 5) are primarily located in the northwestern sector of Mount Vesuvius—particularly within Sant’Anastasia, Volla, Cercola, San Sebastiano al Vesuvio, Ercolano, Portici, and parts of Naples. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Natural hazards Earth and environmental sciences/Solid earth sciences Volcanic hazard exposure vulnerability statistical analysis GIS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Cities located near volcanoes face direct and indirect threats from a range of volcanic hazards such as pyroclastic density currents (PDCs), lahars, lava flows, tephra and ash falls, gas, debris avalanches, landslides and tsunamis that can potentially lead to loss of life and livelihoods, damage essential infrastructure, force population displacement and disrupt economic activities [1]. Currently, 500 million people globally live and work under the shadow of active volcanoes [2] although historically, severe urban settlements were affected by eruptions worldwide [3]. In this context, Mt. Vesuvius, in Campania Region (Southern Italy) (Fig. 1 ), is widely recognized as one of the most dangerous for its probability of future explosive eruptions in a densely populated area [4–6] that could affect large exposed territories with 700 thousand people living on the slopes of the volcano [7]. Historic and stratigraphic evidence of PDC and tephra fallout have underlined several eruptions in history [8]. The most famous and first documented Plinian eruption is the one that occurred on the 79 CE [9–10] that buried the cities of Pompeii, Oplontis, Stabies and Herculaneum, while the last eruption dates back to 1944 [11] causing 14,000 people affected and 26 deaths [12]. The volcano is currently in a state of quiescence, marked solely by fumarolic activity and low seismicity, and it is continuously monitored by the surveillance network of the Vesuvius Observatory, the Naples branch of the Italian National Institute of Geophysics and Volcanology (INGV). In terms of risk management, the National Civil Protection Department (CPD), carries out activities of forecasting, prevention, and mitigation of volcanic risk in Italy and adopts measures aimed at reducing the loss of human lives and properties in the event of an eruption. The authority, that is also responsible for overseeing the phases of emergency management and recovery, with the efforts of the Campania Region, defined the National Emergency Plans for the Vesuvius area consisting of two zones (Fig. 1 c). The red zone, covering 25 municipalities, includes the area exposed to pyroclastic flows (Red Zone 1) and the territory at high risk of roof collapse due to the accumulation of pyroclastic deposits (Red Zone 2). The yellow zone, comprising of 63 municipalities and three districts of the City of Naples, represents the area exposed to significant fallout of volcanic ash and pyroclastic material. Although this is the most recent official document for emergency planning and evacuation for the Vesuvius area, the red zone map does not take into account the impact that PDCs could have on buildings and people that requires the distribution of the impact parameters (flow temperature, flow duration, particle concentration and flow dynamic pressure) that better represent flow intensity in terms of damage potential over the volcano's surroundings [13]. For this reason and knowing that disaster risk depends on the severity of hazard, the number of people or assets exposed and the vulnerability or susceptibility of these elements to suffer loss and damage [16], combining volcanic hazard with demographic, social and building characteristics is crucial to manage disaster risk in highly populated areas such as the Mt. Vesuvius. The present research applies an integrated multidimensional and multisource framework for risk analysis based upon the definition provided by the United Nations Office for Disaster Risk Reduction (UNDRR) [16] by exploring the relationship between long-term volcanic hazard (pyroclastic density currents, PDCs), human population features (population exposure and social vulnerability) and building characteristics (building exposure and physical vulnerability). Volcanic hazard can be defined as the probability of long-term occurrence of PDCs to damage a territory in a specified period of time that is useful for cost/benefit analysis of risk mitigation actions [17], and for appropriate land use planning and location of settlements. Population and building exposure represent the number of people and buildings exposed to long-term volcanic hazard; while social and physical vulnerability can be described as the combination of demographic, socioeconomic factors and building characteristics that can (potentially) increase the impacts of the element exposed [18]. Over the past two decades, several studies have attempted to integrate hazard, exposure, and vulnerability in volcanic settings worldwide [19–27]. In the Vesuvius area, however, research mainly addressed one or two components of risk such as exposure and hazard [28]; building exposure and physical vulnerability [29–31]; overall vulnerability [32]; population exposure and social vulnerability [33]; hazard assessment [13,17,34–35]; or focusing on risk perception [36–38]. A further challenge lies in conducting risk analyses at the local level, where the lack of high-resolution spatial demographic and socio-economic census data [39] hampers comprehensive planning and necessitates spatial assessments that integrate place-specific hazard characteristics with demographic, social, and economic conditions at the enumeration area (EA) scale [40]. These aspects underlined the need to build a new approach that covers all the not previously examined aspects of risk through a multidisciplinary lens at the local level. The main aims are the investigation and mapping of (i) volcanic hazard, (ii) exposure, (iii) vulnerability and (iv) volcanic risk in the Mt. Vesuvius area at EA level in order to gain information about (v) inhabitants and buildings located in the different risk levels for cost-benefit analysis, land-use planning, risk mitigation, disaster preparedness, and community resilience. The challenge of this approach is to standardize the metrics belonging to physical hazard with those of vulnerability and exposure (which derived from different measures and sources). By the use of cartographic and statistical techniques, the method provides a clear and simplified procedure based on diverse integrated geospatial datasets to researchers and stakeholders who work in the field of disaster risk reduction, risk analysis, emergency planning and mitigation strategies. The results are presented in form of maps, while tables, included as supplementary materials, are provided to show the level of hazard, exposure, vulnerability and risk in each municipality under investigation. Results Volcanic hazard The spatial distribution of the volcanic hazard index intercepts an area of 432 km 2 which includes 43 municipalities and 6,608 EAs (Fig. S1 – supplementary) with a total population of 1,075,508 inhabitants and 100,804 buildings (Tab.S1 - supplementary). Figure 2 shows the volcanic hazard level distribution across the EAs under investigations, where 1 corresponds to very low hazard, 2 to low hazard, 3 to medium hazard, 4 to high hazard and 5 to very high hazard. The map highlights that the highest hazard levels (4 and 5) occur in EAs located near the volcano, particularly within municipalities of Sant’Anastasia, Pollena Trocchia, Somma Vesuviana, Ottaviano, and Massa di Somma with level 5 extending in the northwestern direction. Hazard levels gradually decrease with increasing distance from the volcano, reaching the lowest levels (1 and 2) near the outer boundaries of the study area. Consequently, municipalities that extend from the slopes of Mt. Vesuvius down to lower-altitude coastal zones — including Napoli, Ercolano, and Torre del Greco — may encompass the full range of volcanic hazard levels. Looking at Tab. S2 (supplementary), most of the municipalities (67%) include EAs with very low volcanic hazard level (level 1), 48% with medium level (level 3), 46% with low (level 2) and high (level 4) levels, while 37% of municipalities present very high level of volcanic hazard (level 5). As shown in the same table, almost half of the municipalities under investigation are characterized by the two highest volcanic hazard levels (4 and 5). Exposure Figure 3 illustrates the spatial distribution of population density (Fig. 3 a), building density (Fig. 3 b), and overall exposure (Fig. 3 c). Exposure levels are classified from 1 (very low) to 5 (very high). As observed in the maps, the two lowest exposure levels (1 and 2) are predominantly found in EAs located near the volcano and, more generally, in the northeastern portion of the study area. In contrast, exposure hotspots characterized by levels 4 and 5 are primarily clustered within coastal municipalities such as Portici, San Giorgio a Cremano, Napoli, and Ercolano, as well as in the western sector of the study area. Tab. S3 (supplementary) summarizes the distribution of exposure levels across the municipalities under investigation. The results indicate that the majority of municipalities exhibit medium (level 3; 95%) and high (level 4; 93%) exposure, followed by very high (level 5; 79%), low (level 2; 74%) and very low (level 1; 23%) exposure. Notably, approximately 80% of the municipalities—highlighted in Tab. S3 (supplementary) —are characterized by the highest level of exposure. Vulnerability Figure 4 depicts the spatial distribution of social (Fig. 4 a), physical (Fig. 4 b), and overall (Fig. 4 c) vulnerability levels. The classification scheme ranges from level 1 (very low vulnerability) to level 5 (very high vulnerability). As observed in the maps, the lowest vulnerability levels (1 and 2) are predominantly found in EAs located in the southeastern portion of the study area, particularly within the municipalities of Scafati, Terzigno, Pompei, and Palma Campania. Conversely, EAs situated in the western sector of the volcanic area exhibit higher vulnerability levels (3, 4, and 5), notably within the municipalities of Sant’Anastasia, Volla, Portici, and Afragola. Consistently with the other risk components, Tab. S4 (supplementary) shows the distribution of overall vulnerability levels across the municipalities under investigation. The results indicate that the majority of municipalities (83%) are characterized by high vulnerability (level 4), followed by medium (level 3; 81%), low (level 2; 81%), and very low (level 1; 79%) vulnerability levels. Moreover, more than half of the municipalities (62%) contain EAs associated with the highest degree of vulnerability (level 5) (Tab.S4 – supplementary). Volcanic risk Figure 5 shows the final results derived from the integration of volcanic hazard, exposure, and vulnerability indicators, depicting the spatial distribution of volcanic risk levels across the examined EAs. The classification ranges from 1 (very low volcanic risk) to 5 (very high volcanic risk). Overall, the map reveals that EAs characterized by the highest risk levels (4 and 5), shown in orange and in red, are predominantly concentrated in the northwestern portion of the study area—particularly within the municipalities of Sant’Anastasia, Volla, Cercola, San Sebastiano al Vesuvio, and along the coastal municipalities of Ercolano, Portici, and Napoli. Conversely, lower risk levels are primarily distributed around the volcano and throughout the eastern sectors of the study area. As reported in Tab. S5 (supplementary), the majority of municipalities (81%) contains EAs with low volcanic risk (level 2), followed by 76% with medium risk (level 3), 74% with high risk (level 4), and 67% with very low risk (level 1). Furthermore, 24% of municipalities exhibit EAs with very high volcanic risk (level 5). Notably, nearly half of the municipalities under investigation are characterized by high to very high volcanic risk levels (levels 4 and 5). In this context, Fig.S2 (supplementary) shows the proportion of inhabitants and buildings located within each volcanic risk level in the analyzed municipalities. As shown in the diagrams, the municipalities with the highest percentages of inhabitants (Fig.S2a - supplementary) and buildings (Fig.S2b - supplementary) that are classified at high (level 4) and very high (level 5) volcanic risk are: Afragola, Boscotrecase, Casalnuovo di Napoli, Casoria, Castello di Cisterna, Cercola, Napoli, Ottaviano, Pollena Trocchia, Pomigliano d’Arco, Portici, Ercolano, San Giorgio a Cremano, San Sebastiano al Vesuvio, Sant’Anastasia, Somma Vesuviana, Terzigno, Volla, Trecase and Massa di Somma. At the scale of the entire study area, 88.86% of the population resides within EAs exposed to volcanic risk, distributed as follows: 4.45% at very low risk, 9.97% at low risk, 14.35% at medium risk, 23.14% at high risk, and 36.94% at very high risk. Regarding buildings, 92.42% are located within areas exposed to volcanic risk: 7.62% at very low risk, 11.63% at low risk, 23.23% at medium risk, 20.70% at high risk, and 29.24% at very high risk. Discussion Volcanic risk mapping helps identifying which component most strongly influences the overall risk. For instance, in the case of Ercolano (Fig. S3 – supplementary), the spatial distribution of volcanic risk is largely conditioned by the spatial distribution of vulnerability, while the overall risk level is mainly determined by hazard and exposure. This implies that each municipality exhibits specific characteristics whereby certain components exert a greater influence on risk than others. Such differentiation may support territorial planning and urban expansion in relation to regulatory plans. Secondly, the extrapolation of volcanic risk data at the municipal scale can serve as a fundamental basis for damage assessment, decision-making processes, cost–benefit analyses [41–42], and for the activities of insurance companies [43–44]. Given that most mitigation strategies in volcanic hazard zones are primarily grounded on hazard assessment alone [45–46], the present framework could offer an alternative perspective for designing mitigation measures. These measures can follow two main approaches: (a) mitigation targeting the component with the major influence on overall risk, and (b) mitigation differentiated by levels of risk. Considering the municipality of Ercolano (Fig. S3 - supplementary), the first approach (a) could focus on reducing vulnerability. With this regard, both social (Fig. 4 a) and physical vulnerability (Fig. 4 b) maps may be employed to identify and prioritize mitigation actions based on specific vulnerability levels [47–49], taking into account social factors and structural reinforcement of the built environment. Conversely, the second approach (b) would enable the definition of mitigation measures that progressively intensify, from risk level 1 to level 5. Under this framework, level 1 areas would primarily involve maintaining public awareness and readiness without requiring direct interventions; level 2 areas would involve restrictions on new developments and the planning of simple evacuation routes and communication systems; level 3 areas would focus on enhancing preparedness through community training and improved monitoring and early-warning systems; level 4 areas would require continuous monitoring, enforcement of restricted zones, and optimized evacuation logistics; and level 5 areas would demand comprehensive protective strategies aimed at safeguarding human life and ensuring rapid recovery. In this context, Fig. 5 and Fig.S2 (supplementary) could represent the base of this approach in terms of critical areas and number of inhabitants and buildings at volcanic risk. A comparison between Fig. 5 and Fig. 1 c (the National Emergency Plans for the Vesuvius area) suggests that this study achieves a higher resolution of risk classification—five levels instead of two—thus allowing the formulation of detailed and spatially targeted mitigation strategies. Although the proposed methodology underscores the value of cartographic visualization in identifying high-risk areas, two main limitations should be acknowledged. The findings presented in this study are inherently constrained by the use of EAs as the primary territorial statistical unit. While this cartographic framework is indispensable for local-scale analyses, EAs exhibit substantial variation in spatial extent. Some delineate inhabited areas, whereas others consist solely of road segments or specialized zones shaped by distinct geomorphological features [39] complicating relative and comparative analyses within the same territorial context. Additionally, the unavailability of more recent census variables at the sub-municipal scale, especially for building-related information - that allowed us to use the 2011 dataset [50]— constrains the accuracy of the recent characteristics of the built environment, thus restricting the overall precision of vulnerability assessments. Consequently, improving socio-economic data collection at finer spatial resolutions is essential to support more robust and statistically rigorous risk analyses. Despite these limitations, the findings presented in this research could contributes to the development of a comprehensive geospatial database for the Mt. Vesuvius area, associating each EA with corresponding levels of hazard, exposure, vulnerability, and risk. Such a database could be updated on an annual basis, particularly concerning exposure and vulnerability, where recent census and built environment data remain limited. This could represent a practical tool for stakeholders and local authorities. The proposed methodology, which integrates statistical and cartographic techniques, enables the synthesis of diverse metrics within a coherent analytical framework that is applicable not only to volcanic contexts but also to other natural hazards and socio-demographic profiles. It may further serve as a foundation for developing a multi-hazard framework within the same territorial context especially in the Mt. Vesuvius area which is located within a complex volcanic system that includes Campi Flegrei and Ischia Island, supporting long-term and multi-risk mitigation planning. Methods Data source and variables involved in risk analysis The methodology presented in this paper was constructed with the aim of assessing volcanic risk in the Vesuvius area by analyzing, mapping and combining hazard, exposure and vulnerability at EA level. As shown in Tab. S6 (supplementary), in order to assess long-term volcanic hazard, four main variables linked to PDCs impact parameters were retrieved from Mele et al. [51]. These parameters are discussed in detail in Dellino et al. [13] and represent the PDCs flow characteristics useful for evaluating the damaging capacity. In the case of exposure, linked to population and buildings located in the possibly affected areas, the number of inhabitants of each EAs were collected from the ISTAT dataset [15], while the building structural aggregates shapefile was retrieved from the Civil Protection Department (CPD) repository [52]. Both databases refer to the year 2021. As regards the evaluation of social vulnerability, 8 main variables explaining the demographic and socioeconomic condition of each EA were collected from the 2021 ISTAT dataset [15], while data about buildings structural characteristics and housing conditions were retrieved from the 2011 ISTAT dataset [50] (currently the most recent for buildings). It is essential to highlight that, taking into account that there is no guideline concerning which data to use and how to treat this data for the construction of the vulnerability indexes [53], the choice of these variables is strictly linked to the most recent literature that underlines the significant factors influencing social and physical vulnerability, data availability at EA level and the socio-economic characteristics of the Campania population. Particularly, social vulnerability was expressed in terms of: percentages of individuals under 15 and over 76 years old, households with more than four members, foreign residents, unemployed males and females, and the share of male and female with at most a lower secondary education (low human capital). Physical vulnerability was instead evaluated by considering the type of building (residential or commercial), the construction material (masonry or other), the year of construction (before 1980), the number of floors (more than 4) and the state of preservation (poor and very poor). All of these variables were expressed as percentages. Lastly, in order to consider the spatial dimension of each territorial units (i.e. enumeration area) in the vulnerability investigation, we also included the spatial variables linked to centroid coordinates (X, Y) of the EAs computed by QGIS (3.32 version) [39]. The integrated multidimensional framework A combination of Geographic Information System (GIS) and statistical techniques was employed to develop an integrated multidimensional framework (Fig. 6 ) using QGIS and SPSS software. Starting from the volcanic hazard assessment (light orange), information on exposure (light green) and vulnerability (light violet) within the potentially affected area was derived to map the overall volcanic risk. The PDCs impact parameters (Tab.S6 - supplementary), mapped on a regular grid at 250m resolution [16], were first standardized and subjected to factor analysis (FA) to extract the main factor explaining the entire dataset. As only four variables were considered, the extracted factor was defined as “volcanic hazard index” and mapped on the same grid. Because this index had to be integrated with the subsequent risk components (exposure and vulnerability) at the EA level, the grid map was converted to match the 2021 ISTAT EA boundaries. The resulting vector data were then transformed into raster format and rescaled from 1 (very low hazard) to 5 (very high hazard). Rescaling converts raster cell values from their original range to a new range through a linear transformation, preserving spatial relationships while placing data on a uniform scale for easier map comparison and standardized index creation. Once the volcanic hazard was mapped, municipalities and corresponding EAs were intersected to retrieve exposure and vulnerability data from ISTAT [15] and CPD datasets [52] (Tab. S6 - supplementary). Following Fig. 6 , the exposure component was analyzed through two sub-components: population exposure and building exposure. Population exposure was calculated by measuring population density in each EA, expressed as the ratio between the number of inhabitants and the total EA area. EAs with zero population were excluded. The resulting vector data were converted into raster format and rescaled from 1 (very low population exposure) to 5 (very high population exposure). For building exposure, building density was computed by extracting building centroids from the building shapefile to count the number of buildings within each EA, then dividing by the EA area. EAs with zero buildings were likewise excluded. The results were converted into raster format and rescaled from 1 (very low building exposure) to 5 (very high building exposure). The total exposure was then obtained using the QGIS Raster Calculator tool by summing population and building exposure layers, with the final raster rescaled from 1 (very low exposure) to 5 (very high exposure). Social vulnerability was derived through Principal Component Analysis (PCA) applied to standardized demographic and socio-economic variables (Table 1). For each EA, factor scores were weighted by multiplying them by the percentage of variance explained by each factor and dividing by the total variance [53–54]. The composite Social Vulnerability Index (SVI) was then calculated using Eq. (1): $$\:\left(1\right)\:SVI=\frac{{\sum\:}_{i=1}^{N}({F}_{i}*{V}_{i})}{{V}_{tot}}$$ where F i represents factor i ; V i is the variance of F i ; V tot is the total variance and N the total number of factors. The results were mapped, converted to raster, and rescaled from 1 (very low social vulnerability) to 5 (very high social vulnerability). Building vulnerability for each EA was computed following the same procedure and using Eq. 1 to generate the Physical Vulnerability Index (PVI). Because the underlying variables referred to 2011 EAs (Tab. S6 - supplementary), a cartographic transposition from 2011 to 2021 ISTAT boundaries was performed in QGIS. The resulting vector was converted into raster and rescaled from 1 (very low physical vulnerability) to 5 (very high physical vulnerability). Overall vulnerability was then calculated with the QGIS Raster Calculator by summing the social and physical vulnerability layers, and the final raster was rescaled from 1 to 5. Lastly, volcanic risk was estimated by multiplying the hazard, exposure, and vulnerability layers using the same tool. The resulting raster was reclassified through quantile classification into five categories: 1 (very low volcanic risk), 2 (low), 3 (medium), 4 (high), and 5 (very high) allowing for the extraction of the number of inhabitants and buildings within each risk class. Declarations Acknowledgements This research was conducted within the RETURN Extended Partnership project and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan—NRRP, Mission 4, Component 2, Investment 1.3—D.D. 1243 August 2, 2022, PE0000005). Funding This research was conducted within the RETURN Extended Partnership project and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan—NRRP, Mission 4, Component 2, Investment 1.3—D.D. 1243 August 2, 2022, PE0000005). Author contributions statement I.L.: Writing – original draft, Software, Investigation, Formal analysis, Data curation, Conceptualization. F. B.: Writing – review & editing, Data curation. T. G-P: Writing – review & editing, Data curation. A. P.: Writing – review & editing, Data curation. P. D.: Writing – review & editing, Supervision, Funding acquisition. Data availability Data will be made available on request by contacting the following email address: [email protected] Additional information Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Loughlin, S. C., Sparks, R. 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16:41:58","extension":"xml","order_by":34,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80554,"visible":true,"origin":"","legend":"","description":"","filename":"1ad35c65aacd484d83720af84575d26e1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/88b9013ff0e18f2fc0e59e59.xml"},{"id":98057807,"identity":"319655db-7fd4-4f80-96af-a5409cc488f5","added_by":"auto","created_at":"2025-12-12 10:12:53","extension":"html","order_by":35,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89367,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/647a7d58e22177a00affd66b.html"},{"id":98426338,"identity":"1d740ea7-c9ab-48cf-acca-a6d529fa0b63","added_by":"auto","created_at":"2025-12-17 16:36:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3379455,"visible":true,"origin":"","legend":"\u003cp\u003eGeographic setting of Mt Vesuvius within the national context (a), a zoom at the local level (b) and the municipalities included in the Civil Protection National Plan of volcanic risk [14] (c). The regional and municipality boundaries were retrieved from the Italian National Statistical Institute (ISTAT) dataset [15], while Google Satellite was used as basemap. The figure was created in QGIS software 3.32.2.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/d265b612ba92e3a998c3f62b.jpg"},{"id":98057774,"identity":"3ac2ea9d-6760-466d-85e5-9baee1815bed","added_by":"auto","created_at":"2025-12-12 10:12:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4463180,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of volcanic hazard across the municipalities under investigation at EA level. Google Satellite was used as a basemap and the entire figure was generated in QGIS software 3.32.2.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/8a63fd80034b9d978b132b3f.jpg"},{"id":98426237,"identity":"26d23b9c-c433-41c7-a441-fadc23c281f3","added_by":"auto","created_at":"2025-12-17 16:35:55","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3799562,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of population (a), building (b) and overall (c) exposure across the municipalities under investigation at EA level. Google Satellite was used as a basemap and the entire figure was generated in QGIS software 3.32.2.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/f1c974d2368831816737e2be.jpg"},{"id":98057779,"identity":"783e257c-33c7-4d2b-9f3a-da9949cdf006","added_by":"auto","created_at":"2025-12-12 10:12:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4255208,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of social (a), physical (b) and overall (c) vulnerability across the municipalities under investigation at EA level. Google Satellite was used as a basemap and the entire figure was generated in QGIS software 3.32.2.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/8b393a97bc51f8a4d2b4a0b0.jpg"},{"id":98057781,"identity":"8ad1bdf5-58eb-4b1e-97cd-c3747b782b5e","added_by":"auto","created_at":"2025-12-12 10:12:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5123775,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of volcanic risk levels across the municipalities under investigation at EA level. Google Satellite was used as a basemap and the entire figure was generated in QGIS software 3.32.2.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/4bd6bd994e1b3e0ae2e76c06.jpg"},{"id":98427319,"identity":"2329085b-b8a2-4031-9918-248048f17f1d","added_by":"auto","created_at":"2025-12-17 16:40:05","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":750637,"visible":true,"origin":"","legend":"\u003cp\u003eOperational workflow for volcanic risk analysis based on the definition described in section 1. For \u003cu\u003eDATA INPUT\u003c/u\u003e please refers to Tab. 1. Symbol + represents a sum, while symbol x represents a multiplication.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/16bd79c3428ce688d4a80029.jpg"},{"id":103251123,"identity":"d830c669-ceb6-41e0-a30f-59830ecfe797","added_by":"auto","created_at":"2026-02-23 16:04:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":22301781,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/6bf218a9-46ea-4245-872e-b8e86ad3b7de.pdf"},{"id":98428196,"identity":"f305bbd0-8464-4c8e-9947-87d9ab6d8534","added_by":"auto","created_at":"2025-12-17 16:41:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1037312,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8146557/v1/fe690d8b8f83f32c46ba522e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Integrated Multidimensional Risk Framework for Volcanic Hazard Zones: Insights from Mt. Vesuvius, Italy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCities located near volcanoes face direct and indirect threats from a range of volcanic hazards such as pyroclastic density currents (PDCs), lahars, lava flows, tephra and ash falls, gas, debris avalanches, landslides and tsunamis that can potentially lead to loss of life and livelihoods, damage essential infrastructure, force population displacement and disrupt economic activities [1]. Currently, 500\u0026nbsp;million people globally live and work under the shadow of active volcanoes [2] although historically, severe urban settlements were affected by eruptions worldwide [3]. In this context, Mt. Vesuvius, in Campania Region (Southern Italy) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), is widely recognized as one of the most dangerous for its probability of future explosive eruptions in a densely populated area [4\u0026ndash;6] that could affect large exposed territories with 700 thousand people living on the slopes of the volcano [7]. Historic and stratigraphic evidence of PDC and tephra fallout have underlined several eruptions in history [8]. The most famous and first documented Plinian eruption is the one that occurred on the 79 CE [9\u0026ndash;10] that buried the cities of Pompeii, Oplontis, Stabies and Herculaneum, while the last eruption dates back to 1944 [11] causing 14,000 people affected and 26 deaths [12]. The volcano is currently in a state of quiescence, marked solely by fumarolic activity and low seismicity, and it is continuously monitored by the surveillance network of the Vesuvius Observatory, the Naples branch of the Italian National Institute of Geophysics and Volcanology (INGV). In terms of risk management, the National Civil Protection Department (CPD), carries out activities of forecasting, prevention, and mitigation of volcanic risk in Italy and adopts measures aimed at reducing the loss of human lives and properties in the event of an eruption. The authority, that is also responsible for overseeing the phases of emergency management and recovery, with the efforts of the Campania Region, defined the National Emergency Plans for the Vesuvius area consisting of two zones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The red zone, covering 25 municipalities, includes the area exposed to pyroclastic flows (Red Zone 1) and the territory at high risk of roof collapse due to the accumulation of pyroclastic deposits (Red Zone 2). The yellow zone, comprising of 63 municipalities and three districts of the City of Naples, represents the area exposed to significant fallout of volcanic ash and pyroclastic material. Although this is the most recent official document for emergency planning and evacuation for the Vesuvius area, the red zone map does not take into account the impact that PDCs could have on buildings and people that requires the distribution of the impact parameters (flow temperature, flow duration, particle concentration and flow dynamic pressure) that better represent flow intensity in terms of damage potential over the volcano's surroundings [13].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor this reason and knowing that disaster risk depends on the severity of hazard, the number of people or assets exposed and the vulnerability or susceptibility of these elements to suffer loss and damage [16], combining volcanic hazard with demographic, social and building characteristics is crucial to manage disaster risk in highly populated areas such as the Mt. Vesuvius. The present research applies an integrated multidimensional and multisource framework for risk analysis based upon the definition provided by the United Nations Office for Disaster Risk Reduction (UNDRR) [16] by exploring the relationship between long-term volcanic hazard (pyroclastic density currents, PDCs), human population features (population exposure and social vulnerability) and building characteristics (building exposure and physical vulnerability). Volcanic hazard can be defined as the probability of long-term occurrence of PDCs to damage a territory in a specified period of time that is useful for cost/benefit analysis of risk mitigation actions [17], and for appropriate land use planning and location of settlements. Population and building exposure represent the number of people and buildings exposed to long-term volcanic hazard; while social and physical vulnerability can be described as the combination of demographic, socioeconomic factors and building characteristics that can (potentially) increase the impacts of the element exposed [18]. Over the past two decades, several studies have attempted to integrate hazard, exposure, and vulnerability in volcanic settings worldwide [19\u0026ndash;27]. In the Vesuvius area, however, research mainly addressed one or two components of risk such as exposure and hazard [28]; building exposure and physical vulnerability [29\u0026ndash;31]; overall vulnerability [32]; population exposure and social vulnerability [33]; hazard assessment [13,17,34\u0026ndash;35]; or focusing on risk perception [36\u0026ndash;38]. A further challenge lies in conducting risk analyses at the local level, where the lack of high-resolution spatial demographic and socio-economic census data [39] hampers comprehensive planning and necessitates spatial assessments that integrate place-specific hazard characteristics with demographic, social, and economic conditions at the enumeration area (EA) scale [40]. These aspects underlined the need to build a new approach that covers all the not previously examined aspects of risk through a multidisciplinary lens at the local level.\u003c/p\u003e\u003cp\u003eThe main aims are the investigation and mapping of (i) volcanic hazard, (ii) exposure, (iii) vulnerability and (iv) volcanic risk in the Mt. Vesuvius area at EA level in order to gain information about (v) inhabitants and buildings located in the different risk levels for cost-benefit analysis, land-use planning, risk mitigation, disaster preparedness, and community resilience. The challenge of this approach is to standardize the metrics belonging to physical hazard with those of vulnerability and exposure (which derived from different measures and sources). By the use of cartographic and statistical techniques, the method provides a clear and simplified procedure based on diverse integrated geospatial datasets to researchers and stakeholders who work in the field of disaster risk reduction, risk analysis, emergency planning and mitigation strategies. The results are presented in form of maps, while tables, included as supplementary materials, are provided to show the level of hazard, exposure, vulnerability and risk in each municipality under investigation.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eVolcanic hazard\u003c/h2\u003e\u003cp\u003eThe spatial distribution of the volcanic hazard index intercepts an area of 432 km\u003csup\u003e2\u003c/sup\u003e which includes 43 municipalities and 6,608 EAs (Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e \u0026ndash; supplementary) with a total population of 1,075,508 inhabitants and 100,804 buildings (Tab.S1 - supplementary). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the volcanic hazard level distribution across the EAs under investigations, where 1 corresponds to very low hazard, 2 to low hazard, 3 to medium hazard, 4 to high hazard and 5 to very high hazard. The map highlights that the highest hazard levels (4 and 5) occur in EAs located near the volcano, particularly within municipalities of Sant\u0026rsquo;Anastasia, Pollena Trocchia, Somma Vesuviana, Ottaviano, and Massa di Somma with level 5 extending in the northwestern direction. Hazard levels gradually decrease with increasing distance from the volcano, reaching the lowest levels (1 and 2) near the outer boundaries of the study area. Consequently, municipalities that extend from the slopes of Mt. Vesuvius down to lower-altitude coastal zones \u0026mdash; including Napoli, Ercolano, and Torre del Greco \u0026mdash; may encompass the full range of volcanic hazard levels. Looking at Tab. S2 (supplementary), most of the municipalities (67%) include EAs with very low volcanic hazard level (level 1), 48% with medium level (level 3), 46% with low (level 2) and high (level 4) levels, while 37% of municipalities present very high level of volcanic hazard (level 5). As shown in the same table, almost half of the municipalities under investigation are characterized by the two highest volcanic hazard levels (4 and 5).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExposure\u003c/h3\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the spatial distribution of population density (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), building density (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), and overall exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Exposure levels are classified from 1 (very low) to 5 (very high). As observed in the maps, the two lowest exposure levels (1 and 2) are predominantly found in EAs located near the volcano and, more generally, in the northeastern portion of the study area. In contrast, exposure hotspots characterized by levels 4 and 5 are primarily clustered within coastal municipalities such as Portici, San Giorgio a Cremano, Napoli, and Ercolano, as well as in the western sector of the study area.\u003c/p\u003e\u003cp\u003eTab. S3 (supplementary) summarizes the distribution of exposure levels across the municipalities under investigation. The results indicate that the majority of municipalities exhibit medium (level 3; 95%) and high (level 4; 93%) exposure, followed by very high (level 5; 79%), low (level 2; 74%) and very low (level 1; 23%) exposure. Notably, approximately 80% of the municipalities\u0026mdash;highlighted in Tab. S3 (supplementary) \u0026mdash;are characterized by the highest level of exposure.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eVulnerability\u003c/h3\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e depicts the spatial distribution of social (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), physical (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), and overall (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec) vulnerability levels. The classification scheme ranges from level 1 (very low vulnerability) to level 5 (very high vulnerability). As observed in the maps, the lowest vulnerability levels (1 and 2) are predominantly found in EAs located in the southeastern portion of the study area, particularly within the municipalities of Scafati, Terzigno, Pompei, and Palma Campania. Conversely, EAs situated in the western sector of the volcanic area exhibit higher vulnerability levels (3, 4, and 5), notably within the municipalities of Sant\u0026rsquo;Anastasia, Volla, Portici, and Afragola. Consistently with the other risk components, Tab. S4 (supplementary) shows the distribution of overall vulnerability levels across the municipalities under investigation. The results indicate that the majority of municipalities (83%) are characterized by high vulnerability (level 4), followed by medium (level 3; 81%), low (level 2; 81%), and very low (level 1; 79%) vulnerability levels. Moreover, more than half of the municipalities (62%) contain EAs associated with the highest degree of vulnerability (level 5) (Tab.S4 \u0026ndash; supplementary).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eVolcanic risk\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the final results derived from the integration of volcanic hazard, exposure, and vulnerability indicators, depicting the spatial distribution of volcanic risk levels across the examined EAs. The classification ranges from 1 (very low volcanic risk) to 5 (very high volcanic risk). Overall, the map reveals that EAs characterized by the highest risk levels (4 and 5), shown in orange and in red, are predominantly concentrated in the northwestern portion of the study area\u0026mdash;particularly within the municipalities of Sant\u0026rsquo;Anastasia, Volla, Cercola, San Sebastiano al Vesuvio, and along the coastal municipalities of Ercolano, Portici, and Napoli. Conversely, lower risk levels are primarily distributed around the volcano and throughout the eastern sectors of the study area. As reported in Tab. S5 (supplementary), the majority of municipalities (81%) contains EAs with low volcanic risk (level 2), followed by 76% with medium risk (level 3), 74% with high risk (level 4), and 67% with very low risk (level 1). Furthermore, 24% of municipalities exhibit EAs with very high volcanic risk (level 5). Notably, nearly half of the municipalities under investigation are characterized by high to very high volcanic risk levels (levels 4 and 5). In this context, Fig.S2 (supplementary) shows the proportion of inhabitants and buildings located within each volcanic risk level in the analyzed municipalities. As shown in the diagrams, the municipalities with the highest percentages of inhabitants (Fig.S2a - supplementary) and buildings (Fig.S2b - supplementary) that are classified at high (level 4) and very high (level 5) volcanic risk are: Afragola, Boscotrecase, Casalnuovo di Napoli, Casoria, Castello di Cisterna, Cercola, Napoli, Ottaviano, Pollena Trocchia, Pomigliano d\u0026rsquo;Arco, Portici, Ercolano, San Giorgio a Cremano, San Sebastiano al Vesuvio, Sant\u0026rsquo;Anastasia, Somma Vesuviana, Terzigno, Volla, Trecase and Massa di Somma.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAt the scale of the entire study area, 88.86% of the population resides within EAs exposed to volcanic risk, distributed as follows: 4.45% at very low risk, 9.97% at low risk, 14.35% at medium risk, 23.14% at high risk, and 36.94% at very high risk. Regarding buildings, 92.42% are located within areas exposed to volcanic risk: 7.62% at very low risk, 11.63% at low risk, 23.23% at medium risk, 20.70% at high risk, and 29.24% at very high risk.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eVolcanic risk mapping helps identifying which component most strongly influences the overall risk. For instance, in the case of Ercolano (Fig. S3 – supplementary), the spatial distribution of volcanic risk is largely conditioned by the spatial distribution of vulnerability, while the overall risk level is mainly determined by hazard and exposure. This implies that each municipality exhibits specific characteristics whereby certain components exert a greater influence on risk than others. Such differentiation may support territorial planning and urban expansion in relation to regulatory plans.\u003c/p\u003e\u003cp\u003eSecondly, the extrapolation of volcanic risk data at the municipal scale can serve as a fundamental basis for damage assessment, decision-making processes, cost–benefit analyses [41–42], and for the activities of insurance companies [43–44]. Given that most mitigation strategies in volcanic hazard zones are primarily grounded on hazard assessment alone [45–46], the present framework could offer an alternative perspective for designing mitigation measures. These measures can follow two main approaches: (a) mitigation targeting the component with the major influence on overall risk, and (b) mitigation differentiated by levels of risk. Considering the municipality of Ercolano (Fig. S3 - supplementary), the first approach (a) could focus on reducing vulnerability. With this regard, both social (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) and physical vulnerability (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) maps may be employed to identify and prioritize mitigation actions based on specific vulnerability levels [47–49], taking into account social factors and structural reinforcement of the built environment. Conversely, the second approach (b) would enable the definition of mitigation measures that progressively intensify, from risk level 1 to level 5. Under this framework, level 1 areas would primarily involve maintaining public awareness and readiness without requiring direct interventions; level 2 areas would involve restrictions on new developments and the planning of simple evacuation routes and communication systems; level 3 areas would focus on enhancing preparedness through community training and improved monitoring and early-warning systems; level 4 areas would require continuous monitoring, enforcement of restricted zones, and optimized evacuation logistics; and level 5 areas would demand comprehensive protective strategies aimed at safeguarding human life and ensuring rapid recovery. In this context, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.S2 (supplementary) could represent the base of this approach in terms of critical areas and number of inhabitants and buildings at volcanic risk.\u003c/p\u003e\u003cp\u003eA comparison between Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec (the National Emergency Plans for the Vesuvius area) suggests that this study achieves a higher resolution of risk classification—five levels instead of two—thus allowing the formulation of detailed and spatially targeted mitigation strategies.\u003c/p\u003e\u003cp\u003eAlthough the proposed methodology underscores the value of cartographic visualization in identifying high-risk areas, two main limitations should be acknowledged. The findings presented in this study are inherently constrained by the use of EAs as the primary territorial statistical unit. While this cartographic framework is indispensable for local-scale analyses, EAs exhibit substantial variation in spatial extent. Some delineate inhabited areas, whereas others consist solely of road segments or specialized zones shaped by distinct geomorphological features [39] complicating relative and comparative analyses within the same territorial context. Additionally, the unavailability of more recent census variables at the sub-municipal scale, especially for building-related information - that allowed us to use the 2011 dataset [50]— constrains the accuracy of the recent characteristics of the built environment, thus restricting the overall precision of vulnerability assessments. Consequently, improving socio-economic data collection at finer spatial resolutions is essential to support more robust and statistically rigorous risk analyses.\u003c/p\u003e\u003cp\u003eDespite these limitations, the findings presented in this research could contributes to the development of a comprehensive geospatial database for the Mt. Vesuvius area, associating each EA with corresponding levels of hazard, exposure, vulnerability, and risk. Such a database could be updated on an annual basis, particularly concerning exposure and vulnerability, where recent census and built environment data remain limited. This could represent a practical tool for stakeholders and local authorities.\u003c/p\u003e\u003cp\u003eThe proposed methodology, which integrates statistical and cartographic techniques, enables the synthesis of diverse metrics within a coherent analytical framework that is applicable not only to volcanic contexts but also to other natural hazards and socio-demographic profiles. It may further serve as a foundation for developing a multi-hazard framework within the same territorial context especially in the Mt. Vesuvius area which is located within a complex volcanic system that includes Campi Flegrei and Ischia Island, supporting long-term and multi-risk mitigation planning.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eData source and variables involved in risk analysis\u003c/h2\u003e\u003cp\u003eThe methodology presented in this paper was constructed with the aim of assessing volcanic risk in the Vesuvius area by analyzing, mapping and combining hazard, exposure and vulnerability at EA level. As shown in Tab. S6 (supplementary), in order to assess long-term volcanic hazard, four main variables linked to PDCs impact parameters were retrieved from Mele et al. [51]. These parameters are discussed in detail in Dellino et al. [13] and represent the PDCs flow characteristics useful for evaluating the damaging capacity. In the case of exposure, linked to population and buildings located in the possibly affected areas, the number of inhabitants of each EAs were collected from the ISTAT dataset [15], while the building structural aggregates shapefile was retrieved from the Civil Protection Department (CPD) repository [52]. Both databases refer to the year 2021. As regards the evaluation of social vulnerability, 8 main variables explaining the demographic and socioeconomic condition of each EA were collected from the 2021 ISTAT dataset [15], while data about buildings structural characteristics and housing conditions were retrieved from the 2011 ISTAT dataset [50] (currently the most recent for buildings). It is essential to highlight that, taking into account that there is no guideline concerning which data to use and how to treat this data for the construction of the vulnerability indexes [53], the choice of these variables is strictly linked to the most recent literature that underlines the significant factors influencing social and physical vulnerability, data availability at EA level and the socio-economic characteristics of the Campania population. Particularly, social vulnerability was expressed in terms of: percentages of individuals under 15 and over 76 years old, households with more than four members, foreign residents, unemployed males and females, and the share of male and female with at most a lower secondary education (low human capital). Physical vulnerability was instead evaluated by considering the type of building (residential or commercial), the construction material (masonry or other), the year of construction (before 1980), the number of floors (more than 4) and the state of preservation (poor and very poor). All of these variables were expressed as percentages. Lastly, in order to consider the spatial dimension of each territorial units (i.e. enumeration area) in the vulnerability investigation, we also included the spatial variables linked to centroid coordinates (X, Y) of the EAs computed by QGIS (3.32 version) [39].\u003c/p\u003e\u003ch3\u003eThe integrated multidimensional framework\u003c/h3\u003e\u003cp\u003eA combination of Geographic Information System (GIS) and statistical techniques was employed to develop an integrated multidimensional framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e) using QGIS and SPSS software. Starting from the volcanic hazard assessment (light orange), information on exposure (light green) and vulnerability (light violet) within the potentially affected area was derived to map the overall volcanic risk. The PDCs impact parameters (Tab.S6 - supplementary), mapped on a regular grid at 250m resolution [16], were first standardized and subjected to factor analysis (FA) to extract the main factor explaining the entire dataset. As only four variables were considered, the extracted factor was defined as “volcanic hazard index” and mapped on the same grid. Because this index had to be integrated with the subsequent risk components (exposure and vulnerability) at the EA level, the grid map was converted to match the 2021 ISTAT EA boundaries. The resulting vector data were then transformed into raster format and rescaled from 1 (very low hazard) to 5 (very high hazard). Rescaling converts raster cell values from their original range to a new range through a linear transformation, preserving spatial relationships while placing data on a uniform scale for easier map comparison and standardized index creation. Once the volcanic hazard was mapped, municipalities and corresponding EAs were intersected to retrieve exposure and vulnerability data from ISTAT [15] and CPD datasets [52] (Tab. S6 - supplementary). Following Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the exposure component was analyzed through two sub-components: population exposure and building exposure. Population exposure was calculated by measuring population density in each EA, expressed as the ratio between the number of inhabitants and the total EA area. EAs with zero population were excluded. The resulting vector data were converted into raster format and rescaled from 1 (very low population exposure) to 5 (very high population exposure). For building exposure, building density was computed by extracting building centroids from the building shapefile to count the number of buildings within each EA, then dividing by the EA area. EAs with zero buildings were likewise excluded. The results were converted into raster format and rescaled from 1 (very low building exposure) to 5 (very high building exposure). The total exposure was then obtained using the QGIS Raster Calculator tool by summing population and building exposure layers, with the final raster rescaled from 1 (very low exposure) to 5 (very high exposure). Social vulnerability was derived through Principal Component Analysis (PCA) applied to standardized demographic and socio-economic variables (Table\u0026nbsp;1). For each EA, factor scores were weighted by multiplying them by the percentage of variance explained by each factor and dividing by the total variance [53–54]. The composite Social Vulnerability Index (SVI) was then calculated using Eq.\u0026nbsp;(1):\u003c/p\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\left(1\\right)\\:SVI=\\frac{{\\sum\\:}_{i=1}^{N}({F}_{i}*{V}_{i})}{{V}_{tot}}$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e represents factor \u003cem\u003ei\u003c/em\u003e; \u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e is the variance of \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e; \u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003etot\u003c/em\u003e\u003c/sub\u003e is the total variance and \u003cem\u003eN\u003c/em\u003e the total number of factors. The results were mapped, converted to raster, and rescaled from 1 (very low social vulnerability) to 5 (very high social vulnerability). Building vulnerability for each EA was computed following the same procedure and using Eq.\u0026nbsp;1 to generate the Physical Vulnerability Index (PVI). Because the underlying variables referred to 2011 EAs (Tab. S6 - supplementary), a cartographic transposition from 2011 to 2021 ISTAT boundaries was performed in QGIS. The resulting vector was converted into raster and rescaled from 1 (very low physical vulnerability) to 5 (very high physical vulnerability). Overall vulnerability was then calculated with the QGIS Raster Calculator by summing the social and physical vulnerability layers, and the final raster was rescaled from 1 to 5. Lastly, volcanic risk was estimated by multiplying the hazard, exposure, and vulnerability layers using the same tool. The resulting raster was reclassified through quantile classification into five categories: 1 (very low volcanic risk), 2 (low), 3 (medium), 4 (high), and 5 (very high) allowing for the extraction of the number of inhabitants and buildings within each risk class.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was conducted within the RETURN Extended Partnership project and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan\u0026mdash;NRRP, Mission 4, Component 2, Investment 1.3\u0026mdash;D.D. 1243 August 2, 2022, PE0000005).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted within the RETURN Extended Partnership project and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan\u0026mdash;NRRP, Mission 4, Component 2, Investment 1.3\u0026mdash;D.D. 1243 August 2, 2022, PE0000005).\u003c/p\u003e\n\u003cp\u003eAuthor contributions statement\u003c/p\u003e\n\u003cp\u003eI.L.: Writing \u0026ndash; original draft, Software, Investigation, Formal analysis, Data curation, Conceptualization. F. B.: Writing \u0026ndash; review \u0026amp; editing, Data curation. T. G-P: Writing \u0026ndash; review \u0026amp; editing, Data curation. A. P.: Writing \u0026ndash; review \u0026amp; editing, Data curation. P. D.: Writing \u0026ndash; review \u0026amp; editing, Supervision, Funding acquisition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request by contacting the following email address: [email protected]\u003c/p\u003e\n\u003cp\u003eAdditional information\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLoughlin, S. C., Sparks, R. S. J., Brown, S. 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A GIS-based approach to identify the spatial variability of social vulnerability to seismic hazard in Italy. \u003cem\u003eApplied geography\u003c/em\u003e \u003cstrong\u003e74\u003c/strong\u003e, 12-22 (2016). https://doi.org/10.1016/j.apgeog.2016.06.014. \u003c/li\u003e\n\u003cli\u003eSiagian, T. H., Purhadi, P., Suhartono, S. \u0026amp; Ritonga, H. Social vulnerability to natural hazards in Indonesia: Driving factors and policy implications. \u003cem\u003eNatural hazards\u003c/em\u003e \u003cstrong\u003e70\u003c/strong\u003e(2), 1603-1617 (2014). https://doi.org/10.1007/s11069-013-0888-3\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Volcanic hazard, exposure, vulnerability, statistical analysis, GIS","lastPublishedDoi":"10.21203/rs.3.rs-8146557/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8146557/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMt. Vesuvius, in Campania Region (Southern Italy), is considered one of the world\u0026rsquo;s most dangerous volcanoes due to its probability of future explosive eruptions in a densely populated area. When large populations or significant assets are exposed to volcanic hazards and exhibit high vulnerability, the potential for disaster increases. Consequently, combining volcanic hazard with demographic, social and building characteristics is essential to manage disasters. The present research applies an integrated multidimensional and multisource framework for risk analysis, based on diverse geospatial datasets, by exploring the relationship between long-term volcanic hazard (pyroclastic density currents), human population features (population exposure and social vulnerability) and building characteristics (building exposure and physical vulnerability). The challenge of this approach is to standardize the metrics belonging to physical hazard with those of potential vulnerability and exposure (which derived from different measures), to investigate the volcanic risk spatial distribution. Using cartographic and statistical methods at the Enumeration Area level, the framework identifies and prioritizes zones requiring focused mitigation strategies. The resulting risk map shows that the highest-risk areas (levels 4 and 5) are primarily located in the northwestern sector of Mount Vesuvius\u0026mdash;particularly within Sant\u0026rsquo;Anastasia, Volla, Cercola, San Sebastiano al Vesuvio, Ercolano, Portici, and parts of Naples.\u003c/p\u003e","manuscriptTitle":"An Integrated Multidimensional Risk Framework for Volcanic Hazard Zones: Insights from Mt. 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