| D1.1 - Data sources and Knowledge Lead partner SISTEMA This deliverable describes the “Identification of data and knowledge sources and integration and interoperability requirements” activities and outcomes with a focus on the identification, classification and evaluation of the data sources considered useful for Shelter scopes and on the applied methodology. |  | |
| D1.2 - Building of best/next practices observatory Lead partner UNIBO The overall objective of this report is to provide an effective codification of existing knowledge. This is achieved by adapting existing ontologies, building of a lesson learned and next practices observatory based on existing best practices on adaptive governance for cultural heritage management, local knowledge and historical event. | | |
| D1.3 - Data Lake Lead partner LINKS This deliverable describes the data lake structure and the data lake model. The data lake is the concept chosen in SHELTER to manage the huge amount of heterogeneous, geospatial, non-geospatial, structured and unstructured knowledge collected and generated during the project activities. The data lake approach is the response to the need of a dynamic, flexible, scalable and continuously evolving data model to exploit and take the maximum benefit from existing social knowledge and the knowledge generated within the project by means of co-creation processes. | | |
| D1.4 - Multiscale data model Lead partner EGIS This deliverable describes the data models that will be implemented to share and visualize georeferenced data for the Open Labs. The complexity of the CHM domain implies a multisource approach that takes into account the temporal, the spatial, the social and the cultural dimensions adapted to different scales from city to region in different levels of detail. The multiscale-multisource data model is the way the data lake content will be spatially exploited by the consortium and by the stakeholders. | | |
| D2.1 - HA Resilience structure Lead partner TECNALIA This deliverable defines the strategy for the integration of the different project methodological results in the SHELTER operative knowledge framework. The workflow and the dimensions for developing the framework has been established defining the interplay (output and inputs) of the Open Labs and data driven platform. | | |
| D2.2 - HA Systemic resilience assessment and monitoring framework Lead partner CRCM This deliverable developed the multiscale indicator that will be the basis for the risk dependent resilience assessment based on hazard, exposure and vulnerability (of single risk and combinations of risks) at artefact, building and district scale but also for the generalised multiscale resilience. | | |
| D2.3 - Anatomy of Historic Areas (HA) Lead partner POLITO This deliverable developed the multiscale indicator that will be the basis for the risk dependent resilience assessment based on hazard, exposure and vulnerability (of single risk and combinations of risks) at artefact, building and district scale but also for the generalised multiscale resilience. | | |
| D2.4 - Characterisation of hazards, Climate Change events and impacts Lead partner TECNALIA The deliverable describes the methodology for characterisation of hazards, climate change events and impacts and projections/scenarios. It classifies events and related impacts affecting Cultural Heritage identifying different time horizon scenarios and establishing what we know and do not know, making a distinction between known types of events, unknown types of events, and unexpected It will identify key uncertainties and possible gaps due to missing information. It comprises other non-climate stresses, such as the socio-economic impacts of Climate Change, including tourism, within the selected sites including the local knowledge extracted in Open Labs. | | |
| D2.5 - Specific Hazard risk assessment Lead partner EKO The deliverable describes a spatially explicit methodology to assess the risk regarding specific hazards and their synergistic impact based on the results of D2.2 “HA Systemic resilience assessment and monitoring framework”, its application to case studies and its fine tuning. It includes the procedure definition with the identification of required/existing data sources, the definition to detect the techniques and needs for transform, standardise and impute missing values, the algorithms and multiscale data analytics and geospatial computing required for indicators calculation; and the methods for weighting and combining vulnerability/resilience factors and categorizing and performing sensitivity analysis. | | |
| D2.6 - Agent Based Modelling for scenario analysis Lead partner EKOU The report describes the scenario simulation methodology using Agent Based Modelling (ABM) regarding the preparedness of agents to cover spatial and temporal patterns in case of the occurrence of disruptions. It describes, as well, the results of the simulations to determine and compare parameters such as fatality number, injury number, total number of citizens exposed to disaster, financial impact and recovery rate provided and complete recovery time needed after the event and the evaluation of preparedness in terms of infrastructure and equipment, communication needs, administrative and insurance preparedness and recovery scenarios. | | |
| D2.7 - Historic Areas Systemic Resilience Index Lead partner TECNALIA The deliverable defines the procedure for the implementation of the systemic resilience assessment methodology at Historic Area (HA) scale that will integrate the specific hazard risk assessment described in D2.5 as a nested concept and the results from Agent Based Modelling (ABM) (D2.6). The methodology for HA Resilience Index is described: i) integrating multidimensional resilience assessments results (building environment, cultural, social, governance and institutional resilience, economic and environmental resilience), ii) identifying the required data analysis and index computation, and iii) performing sensitivity and uncertainty analysis. | | |
| D4.1 - Resilience ID incremental strategy Lead partner TECNALIA This deliverable includes the detailed definition of the incremental strategy for the implementation of the Resilience ID, the workflow to generate it using the Data Driven Platform, the structure of the information and the visualisation in the multiscale data model. | | |
| D4.2 - Strategy for early recovery roadmap Lead partner UNIBO The deliverable provides a guideline for identifying acceptable, effective and pre-planned strategies to generate a roadmap that will be tested in each cases study through Open Labs (OLs), including guidelines for identifying acceptable and effective and pre-planned strategies. It defines the use of Resilience ID (D4.1) and the back-up models for the identification of relevant information necessary for the reconstruction process. | | |
| D6.1 - GLOCAL user requirements Lead partner CRCM The deliverable identified GLOCAL user requirements for Disaster Risk Management and Climate Change Adaptation to heritage looking at the bottom-up (local) and top-down (global) levels. Identification is based on the use case scenarios, ex-post analysis and international experience. | | |
| D6.2 - ICT-community interaction rulebook Lead partner ULIEGE The deliverable outlines the development of a community interaction rulebook (CIR) aiming to explore the role of information communication technology (ICT) in adaptive governance and identifies some key ‘rules’ to guide the development of the Open Labs within the SHELTER Project. | | |
| D6.3 - Adaptive Governance Schemes Mapping Lead partner ULIEGE This document provides a visual mapping of the different types of governance structures applicable at different stages of the Disaster Risk Management (DRM), with a detailed description of their advantages and limitations. Linked with the document, the Toolkit for Cultural Heritage Stakeholders to Map Governance Structures using the Organigraph technique. | | |
| D6.4 - Historic Areas resilience co-production playbook Lead partner CRCM The deliverable details the co-creation strategies blueprints that cover diverse hazards, Historic Areas typologies, Disaster Risk Management phases and type of solutions. | | |
| D6.5 - Methodology for Local Knowledge extraction Lead partner POLITO The deliverable defines a theoretical and practical framework to include and take into account those informal knowledge and local factors that represent the peculiar long-lasting interaction of the communities with their environment, providing tools for extracting Local Knowledge, Sense of place and Peer learning addressed to local stakeholders in Open Labs. | | |
| D8.1 - Dissemination and communication plan Lead partner EURONET The deliverable serves as a guideline for the promotion activities carried out by SHELTER Consortium, including a scouting of relevant conferences, workshops, events and journals aligned with the project scopes. | |
| Disaster risk management and cultural heritage: The perceptions of European world heritage site managers on disaster risk management Lead partners ULIEGE |
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| Managing water risks in archaeological sites: the flooding of the complex of Santa Croce in Ravenna Lead partners UNIBO |
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| Climate change risk assessment: A holistic multi-stakeholder methodology for the sustainable development of cities Lead partners UPV/EHU, TECNALIA |
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| Multilingual Text Classification from Twitter During Emergencies Lead partners LINKS |
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| Risk assessment methodologies to safeguard historic urban areas from the effects of climate change Lead partners UPV/EHU |
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| The complex of Santa Croce in Ravenna as a case study: integration of 3D techniques for surveying and monitoring of a historical site Lead partners UNIBO |
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| A contrastive distillation approach for incremental semantic segmentation in aerial images/ topic: Computer Vision, Semantic Segmentation Lead partners LINKS |
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| Prioritization methodology for resilience enhancement of historic areas facing climate-change-related hazards Lead partners UPV/EHU, TECNALIA |
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| Investigating cultural heritage resilience in historical areas: a good practice collection Lead partners UNIBO |
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| The risk of heat waves to historic urban areas. A GIS-based model for developing a risk assessment methodology Lead partners UPV/EHU, TECNALIA |
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| How are heat waves putting at risk historic urban areas? First steps for developing risk assessment methodologies Lead partners UPV/EHU, TECNALIA |
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| An agent-based model of greening a city for reducing pluvial flooding at a cultural heritage site Lead partners UNIBO, TECNALIA, EKOU |
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| Impatti del cambiamento climatico e dei rischi naturali sulle aree storiche: il contributo della pianificazione urbanistica per migliorare la resilienza urbana nel progetto Lead partners UNIBO |
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| Enhancing resilience of cultural heritage in historical areas: a collection of good practices Lead partners UNIBO |
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| Climate change risk assessment: A holistic multi-stakeholder methodology for the sustainable development of cities Lead partners UPV/EHU, TECNALIA |
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| A holistic and multi-stakeholder methodology for vulnerability assessment of cities to flooding and extreme precipitation events Lead partners UPV/EHU, TECNALIA |
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| Impact estimation of emergency events using social media streams Lead partners LINKS |
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| Transformer neural networks for interpretable flood forecasting Lead partners POLITO, LINKS |
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| Using Organigraphs to Map Disaster Risk Management Governance in the Field of Cultural Heritage Lead partners ULIEGE, ISRBC, EKO |
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| Do we know how urban heritage is being endangered by climate change? A systematic and critical review Lead partner UPV/EHU, TECNALIA |
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| AI-based flood event understanding and quantification using online media and satellite data Lead partner LINKS |
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| Water Segmentation with Deep Learning Models for Flood Detection and Monitoring Lead partner LINKS |
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| Supervised Burned Areas delineation by means of Sentinel-2 imagery and Convolutional Neural Networks Lead partner LINKS |
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| Sentinel-1 Flood Delineation with Supervised Machine Learning Lead partner LINKS, POLITO |
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| Double-Step U-Net - A Deep Learning-Based Approach for the Estimation of Wildfire Damage Severity through Sentinel-2 Satellite Data Lead partner LINKS, POLITO |
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| Investigating the Integration of Cultural Heritage Disaster Risk Management into Urban Planning Tools. The Ravenna Case Study Lead partner UNIBO |
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