Periodic Reporting for period 2 - RescueME (Equitable RESilience solutions to strengthen the link between CUltural landscapEs and coMmunitiEs)
Reporting period: 2024-02-01 to 2025-01-31
The project aims to address critical gaps in current approaches to heritage conservation and resilience in the face of climate change. In Europe, Cultural Heritage (CH) is not only personally significant but also crucial for the European Union's identity and economy. The main goal of RescueME is to develop, test and demonstrate the effectiveness of an Actionable Framework based on the Resilient Historical Landscape approach (RHL) complemented by data, models, methods, and tools able to assess risks and opportunities, co-develop inclusive and just resilience strategies and innovative solutions to protect European cultural heritage and cultural landscapes. Social sciences and humanities play a vital role in the project, particularly in co-designing frameworks and strategies, engaging stakeholders, and co-producing knowledge.
The project is structured in eight objectives:
1. Building the frame: Developing a replicable RescueME Actionable Framework based on the Resilient Historical Landscape approach, integrating socio-ecological-cultural aspects and utilizing advanced technologies for data-driven assessment.
2. Triggering action using a multi-scale method to make the value of Cultural Landscapes (CL) and heritage diversity quantifiable, considering soft benefits like well-being and tourism, aiming to trigger action at both European and local levels.
3. Mobilize resources through ready-to-use tools like organigraphs for stakeholder mapping, Agent-Based Modeling (ABM), and crowdsourcing techniques, engaging communities and cultural sectors for heritage stewardship.
4. Facilitate evidence-based decision-making with a meta-repository of solutions from previous projects, characterized by their impact and carbon footprint, implemented through a dynamic decision support system.
5. Co-produce local knowledge and increase engagement of communities with CL through interactive knowledge co-production, aiming to enhance social awareness and appreciation of resilience measures.
6. Monitoring & managing: Develop an indicator-based monitoring strategy linked to resilience pathways, engaging communities in co-monitoring heritage diversity and identifying adaptive governance models.
7. Transfer & scale-up, and tailor proposed policies and actions through a Community of Practice, producing a long-term agenda for transformative resilience and providing user-friendly information through a one-stop-shop.
The project is structured in eight objectives:
1. Building the frame: Developing a replicable RescueME Actionable Framework based on the Resilient Historical Landscape approach, integrating socio-ecological-cultural aspects and utilizing advanced technologies for data-driven assessment.
2. Triggering action using a multi-scale method to make the value of Cultural Landscapes (CL) and heritage diversity quantifiable, considering soft benefits like well-being and tourism, aiming to trigger action at both European and local levels.
3. Mobilize resources through ready-to-use tools like organigraphs for stakeholder mapping, Agent-Based Modeling (ABM), and crowdsourcing techniques, engaging communities and cultural sectors for heritage stewardship.
4. Facilitate evidence-based decision-making with a meta-repository of solutions from previous projects, characterized by their impact and carbon footprint, implemented through a dynamic decision support system.
5. Co-produce local knowledge and increase engagement of communities with CL through interactive knowledge co-production, aiming to enhance social awareness and appreciation of resilience measures.
6. Monitoring & managing: Develop an indicator-based monitoring strategy linked to resilience pathways, engaging communities in co-monitoring heritage diversity and identifying adaptive governance models.
7. Transfer & scale-up, and tailor proposed policies and actions through a Community of Practice, producing a long-term agenda for transformative resilience and providing user-friendly information through a one-stop-shop.
In this second period two significant milestones for the project have been achieved, the local resilience baseline and local Impact Chains (milestone 3 in WP4) and the RescueME resilience meta-repository (milestone 4 in WP2). WP1 activities were completed by around 70%. The Actionable Resilient Historic Landscape Framework developed in the 1RP was used to guide the methodological process across all tasks. This framework conceptualizes Cultural Landscapes as a Socio-Ecological-Technical System (SETS), comprising five key capitals (natural, built, social, human, and financial) and four measuring objectives (sensitivity, coping capacity, adaptive capacity, and transformative capacity). This framework has been linked to resilience measures and indicators, as a basis for the characterization of the solutions included in the meta-repository and pathways definition. The heritage values and ecosystem services have been analysed for local resilience assessments and predictive impact assessment models are under development. A new deliverable, D1.7 was submitted, detailing data and methods for European coastal heritage landscapes typologies and climate change impacts following the recommendation of the 1RP.
WP2 activities were also completed by around 70%. The RescueME resilience meta-repository was finalized, collecting 1000 solutions, including those from the culture and creative industries sector and innovative financing strategies. Adaptive governance solutions were included, and governance maps were co-created with R-Labs. In WP3, technical specifications and data mapping were upgraded, updated, and integrated, providing a comprehensive reference for all partners. AI-based tools, including mapping models, the Social Media Data Analysis (SMDA) tool, and the Chatbot, were designed, implemented, and deployed.
Similarly to the first period, WP1, WP2 and WP3 have been continually supported, fed, shaped and fine-tuned by the work carried out in WP4, where the 5 R-Labs that were established across Europe have been coordinated to provide continuous inputs for co-creation, validation and replication of all the results. These R-Labs have been supported theoretically and methodologically by the co-creation and engagement framework for the community approach that was created in the first period. In the second reporting period, WP4 activities were completed to approximately 60%. The local resilience baseline assessment was finalized by evaluating questionnaires about indicators provided by the R-Labs.
WP2 activities were also completed by around 70%. The RescueME resilience meta-repository was finalized, collecting 1000 solutions, including those from the culture and creative industries sector and innovative financing strategies. Adaptive governance solutions were included, and governance maps were co-created with R-Labs. In WP3, technical specifications and data mapping were upgraded, updated, and integrated, providing a comprehensive reference for all partners. AI-based tools, including mapping models, the Social Media Data Analysis (SMDA) tool, and the Chatbot, were designed, implemented, and deployed.
Similarly to the first period, WP1, WP2 and WP3 have been continually supported, fed, shaped and fine-tuned by the work carried out in WP4, where the 5 R-Labs that were established across Europe have been coordinated to provide continuous inputs for co-creation, validation and replication of all the results. These R-Labs have been supported theoretically and methodologically by the co-creation and engagement framework for the community approach that was created in the first period. In the second reporting period, WP4 activities were completed to approximately 60%. The local resilience baseline assessment was finalized by evaluating questionnaires about indicators provided by the R-Labs.
The RescueME resilience meta-repository is an extensive collection of 1000 solutions, categorized into three typologies and five domains, focused on cultural landscapes. It surpasses existing resilience frameworks by integrating diverse solution types, including policy recommendations, lessons learned, and place-based solutions. Advanced AI models for mapping hazards like wildfires, floods, and landslides utilize satellite imagery for real-time monitoring and historical analysis. The integrated impact assessment capability transforms geographical data into actionable intelligence by cross-referencing affected areas with population density and infrastructure data. Additionally, the Social Media Data Analysis (SMDA) tool and Chatbot leverage AI for crowdsourcing intelligence, providing detailed categorization of responses into Positive Performance, Attention Needed, or Identified Weaknesses. This holistic approach represents a significant advancement in resilience research and practice for cultural landscapes.