A Geospatial Decision Support Tool for Seismic Risk Management: Florence (Italy) Case Study

Matassoni, L.; Giovinazzi, Sonia; Pollino, Maurizio; Fiaschi, A.; Porta, Luigi La; Rosato, Vittorio

doi:10.1007/978-3-319-62395-5_20

Cited by 23 publications

(17 citation statements)

References 31 publications

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“…Furthermore, a specific seismic risk module has been realized, which operates as a stress tester enabling to simulate earthquakes and assessing the resulting chain of events (Matassoni et al., 2017). Such CIPCast module firstly simulates the ground shake map (related to earthquake intensity), by also considering the amplification effects, and then estimates the expected damages to buildings and other infrastructure elements.…”

Section: Software System For Qualitative Semantic Spatiotemporal Assementioning

confidence: 99%

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

Coletti

Nicola

Pietro

et al. 2020

Contingencies & Crisis Mgmt

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Risk assessment of urban areas aims at limiting the impact of harmful events by increasing awareness of their possible consequences. Qualitative risk assessment allows to figure out possible risk situations and to prioritize them, whereas quantitative risk assessment is devoted to measuring risks from data, in order to improve preparedness in case of crisis situations. We propose an automatic approach to comprehensive risk assessment. This leverages on a semantic and spatiotemporal representation of knowledge of the urban area and relies on a software system including: a knowledge base; two components for quantitative and qualitative risk assessments, respectively; and a WebGIS interface. The knowledge base consists of the TERMINUS domain ontology, to represent urban knowledge, and of a geo‐referenced database, including geographical, environmental and urban data as well as temporal data related to the levels of operation of city services. CIPcast DSS is the component devoted to quantitative risk assessment, and WS‐CREAM is the component supporting qualitative risk assessment based on computational creativity techniques. Two case studies concerning the city of Rome (Italy) show how this approach can be used in a real scenario for crisis preparedness. Finally, we discuss issues related to plausibility of risks and objectivity of their assessment.

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Section: Software System For Qualitative Semantic Spatiotemporal Assementioning

confidence: 99%

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

Coletti

Nicola

Pietro

et al. 2020

Contingencies & Crisis Mgmt

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“…The possibility to account for the seismic microzonation (i.e. the possible amplification of the seismic hazard and therefore of the expected impacts due to soil conditions) was also included within CIPCast-ES, and was used for the case study of Florence Municipality, where a seismic microzonation study, providing the-specific amplification factor AF was provided [21].…”

Section: Cipcast Decision Support Systemmentioning

confidence: 99%

“…A shake map is then generated using a suite of ground motion prediction equations (GMPEs). Currently CIPCast-ES implements Sabetta and Pugliese GMPE [27] in terms of PGA and different GMPEs in terms of Macroseismic Intensity I [21]. The seismic performance of above ground components of electric power networks, such as substations, can be assessed against PGA.…”

Section: Seismic Hazard Representationmentioning

confidence: 99%

Towards a Decision Support Tool for Assessing, Managing and Mitigating Seismic Risk of Electric Power Networks

Giovinazzi

Pollino

Kongar

et al. 2017

Computational Science and Its Applications – ICCSA 2017

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Recent seismic event worldwide proved how fragile the electric power system can be to seismic events. Decision Support Systems (DSSs) could have a critical role in assessing the seismic risk of electric power networks and in enabling asset managers to test the effectiveness of alternative mitigation strategies and investments on resilience. This paper exemplifies the potentialities of CIPCast, a DSS recently created in the framework of the EU-funded project CIPRNet, to perform such tasks. CIPCast enables to perform risk assessment for Critical Infrastructures (CI) when subjected different natural hazards, including earthquakes. An ad-hoc customization of CIPCast for the seismic risk analysis and management of electric power networks is featured in this paper. The international literature describes effective and sound efforts towards the creation of software platforms and frameworks for the assessment of seismic risk of electric power networks. None of them, unfortunately, achieved the goal of creating a user-friendly and ready available DDS to be used by asset managers, local authorities and civil protection departments. Towards that and building on the international literature, the paper describes metrics and methods to be integrated within CIPCast for assessing the earthquake-induced physical and functional impacts of the electric power network at component and system level. The paper describes also how CIPCast can inform the service restoration process.

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“…Towards the definition of the ARCH DSS software architecture and of the assessment methods therein implemented, reference has been made to internationally recognized GIS-based platforms for seismic risk assessment, e.g., the Global Earthquake Model (GEM) (https://www.globalquakemodel.org/gem, accessed on 12 May 2021); the HAZUS-MH platform used by the US Federal Emergency Management Agency (FEMA) [6]; the CAPRA Probabilistic Risk Assessment Platform (https://ecapra.org/, accessed on 12 May 2021), among several others [7][8][9][10][11][12][13][14][15][16]. However, none of the existing tools and platforms, to the authors' knowledge, specifically target the HAs that are and should be regarded as complex social-ecological systems where institutional, social, cultural, physical, economic, environmental, and intangible dimensions exist and strongly interact.…”

Section: Introductionmentioning

confidence: 99%

Assessing Earthquake Impacts and Monitoring Resilience of Historic Areas: Methods for GIS Tools

Giovinazzi

Marchili

Pietro

et al. 2021

IJGI

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Historic areas (HAs) are highly vulnerable to natural hazards, including earthquakes, that can cause severe damage, if not total destruction. This paper proposes methods that can be implemented through a geographical information system to assess earthquake-induced physical damages and the resulting impacts on the functions of HAs and to monitor their resilience. For the assessment of damages, making reference to the universally recognised procedure of convoluting hazard, exposure, and vulnerability, this paper proposes (a) a framework for assessing hazard maps of both real and end-user defined earthquakes; (b) a classification of the exposed elements of the built environment; and (c) an index-based seismic vulnerability assessment method for heritage buildings. Moving towards the continuous monitoring of resilience, an index-based assessment method is proposed to quantify how the functions of HAs recover over time. The implementation of the proposed methods in an ad hoc customized WebGIS Decision Support System, referred to as ARCH DSS, is demonstrated in this paper with reference to the historic area of Camerino-San Severino (Italy). Our conclusions show how ARCH DSS can inform and contribute to increasing awareness of the vulnerabilities of HAs and of the severity of the potential impacts, thus supporting effective decision making on mitigation strategies, post-disaster response, and build back better.

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A Geospatial Decision Support Tool for Seismic Risk Management: Florence (Italy) Case Study

Cited by 23 publications

References 31 publications

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

Towards a Decision Support Tool for Assessing, Managing and Mitigating Seismic Risk of Electric Power Networks

Assessing Earthquake Impacts and Monitoring Resilience of Historic Areas: Methods for GIS Tools

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