Methods

The emBRACE project is methodologically rich.This Methods section of the Handbook introduces the separate reports prepared for:

• Agent Based Modelling

• Data Collection for Health & Social Services

• Disaster Databases of Human Impacts in Europe

• Disaster Footprints

• Resilience Indicators

• Social Learning

• Social Network Analysis

• In addition, project partners used a number of standard quantitative and qualitative methods in the case studies in particular.

Agent Based Modelling

This part of the work concerns computer simulation models (agent-based models), and its focus of enquiry is on resilience at the municipality, organisation, or city level. Agent based models can be good test beds for thinking about decision-making and management alternatives in many different human domains including those linked with transformative resilience to natural disasters.

Data Collection for Health & Social Services

Coming soon...

Disaster Databases of Human Impacts in Europe

Despite prolonged discussions on terminologies, only a few examples exist in the literature that actually attempt to measure resilience. One area even more under-researched in the field of disaster risk research, is on what and who will provide the data to construct such a resilience index (i.e. as one way to measure disaster resilience) in the future, and specifically how the disaster community’s provision of impact data might contribute to it. This study shows that only a small percentage of indicators may be required from disaster databases whereas most of the data likely is compiled by governmental agencies. Overall, this exercise shows the complexity of the task, particularly in Europe, and the need for higher-resolution (community-level) data at European level. The need to integrate quantitative- and qualitatively-gathered indicators and context versus generalizable indicators is highlighted and discussed.

Disaster Footprints

The report aims to test the use of diffused datasets that are normally available for public administration in tracking the “footprint” of natural disaster on their territory. Secondly, it aims to contribute to a better understanding if and how coarse scale quantitative data can prove useful in a study on resilience. Concluding, the main goal of the work is the exploitation of large datasets in search for indicators and information valuable for resilience research.

Resilience Indicators

This report discusses indicators and indicator systems of community resilience by taking into account current research activities and findings obtained from the emBRACE project. It uses an integrated approach for assessing community resilience by means of indicators, considering multiple level of measurements, scales and perspectives of community resilience. The emBRACE conceptual framework and the empirical grounded indicators of the emBRACE case studies allow us to derive key-indicators of community resilience that can be applied across different contexts and types of natural hazards.

Social Learning

This report explores how the challenges faced by communities at risk from environmental hazards might be tackled via the application of social learning practices. By outlining the theoretical framework for social learning a better understanding of its application for developing resilient communities is been proposed. The mechanisms for triggering social learning are then outlined, with examples from flood and heat wave risk in the UK employed to highlight how this might be achieved. Gaps and further opportunities for learning and research are outlined, again supported with examples from the UK and Turkey.

Social Network Analysis

The capacity of social network maps as a multi-purpose heuristic device is very useful – indeed necessary – if we want to explore ideas of community resilience and planning in the face of natural disasters. As White (1945) put it, if “floods are ‘acts of God’, flood losses are largely acts of man” and therefore being able to present a formalized, structured understanding of social aspects (“the social”) is critical to understanding, communicating, and providing truly integrative research on what community resilience to multiple hazards actually means in practice. Resilience cannot be left to hydrologists and physical planners alone, it must include the social. Our social network maps provide such a model of the links between significant individuals involved in key stages of the disaster planning, response and recovery phases. Further, they do so in a structured manner which allows this necessary social data to be communicated across disciplinary divides and also to be located within the context of a wider conceptual framework that links (social) knowledge networks and (institutional) decision-making structures. As a result, better decisions may be made.

Quantitative and Qualitative Methods

This large category is used to provide some of the survey or interview tolos that emBRACE Partners used in the case study research.

Introduction | Concepts | Methods | Case Studies | Reaching Out | Resources

Agent Based Modelling | Data Collection for Health & Social Services | Disaster Databases of Human Impacts in Europe | Disaster Footprints | Resilience Indicators | Social Learning | Social Network Analysis | Quantitative & Qualitative Methods