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MON4.4: Global exposure monitoring for multi-hazards risk assessments
Session organized by the Joint Research Centre, European Commission
Global exposure monitoring for multi-hazards risk assessments
1Bureau for Seismic and Volcanic Risk, Italian Civil Protection Department; 2Joint Research Centre, European Commission, Italy, Republic of
Disaster risk analysis is used for estimating potential future disaster and losses, and a guiding mechanism for implementing disaster risk reduction measures. Through international advocacy initiatives such as the ISDR promoted Hyogo protocol, an increasing number of countries are now including disaster risk analysis in their policies. However, the implementation of these policies requires knowledge that is not always available. Datasets, models and tools used in disaster risk assessment are often not available especially in low income countries where the information is needed most. A number of initiatives with a global scope are addressing this lack of data, of models, while other initiatives are already developing datasets and tools. In addition the research community is providing innovation that provides new opportunities for generating the required knowledge.
World Bank/GFDRR contributions to exposure modeling for global risk modeling initiatives and OpenDRI initiative
World Bank, United States of America
Risk assessments for natural hazards are starting points for disaster mitigation activities. The results from the assessments allow the stakeholder to have an understanding of the underlying risk present in the location in question. This enables the planning of appropriate interventions to be made. Risk is often defined as the product of the hazard, exposure (e.g. physical assets) and its vulnerability given certain hazard intensities. The quality of the exposure data that is fed into the risk models has a significant impact on the output from the risk model. Exposure data has traditionally been collected using official census data. Often in these cases, aggregate level statistics required disaggregation for the data to match the scale of the geographical unit used for the risk modeling. In the recent years, bottom up methodologies to model the assets exposed against potential natural hazards. Some involve the use of tools including hand held devices, remotely sensed data and sampling schemes.
Building a global exposure database
1Dipartimento di Ingegneria Industriale e dell'Informazione, University of Pavia, Italy; 2GEM Foundation, Italy
The Global Earthquake Model (GEM) is a global collaborative effort to provide organisations and people with open tools and resources for transparent assessment of earthquake risk anywhere in the world. Leading science is leveraged for the benefit of society; hundreds of individuals and organisations are working together through global projects and regional programmes to develop open-source tools, global datasets and best practices that follow the state-of-the-art in science on seismic hazard and risk. All contributions are integrated into a comprehensive platform (OpenQuake) that will become available in 2014.
Processing satellite imagery for mapping physical exposure globally
Joint Research Centre, European Commission, Italy, Republic of
Disaster risk models require exposure and hazard information. Physical exposure – information on villages, towns, cities and metropolitans areas - is still not available in a standardized form for local to national assessment, for properly quantifying disaster hotspots globally, or for between countries risk comparisons. The Global Exposure Database for Global Earthquake Model is the first initiative that addresses the systematic collection and population of a global exposure database. That database also needs to be populated. A potential source for up to date exposure information is provided by the large volume of satellite imagery available in image archives that are continuously updated. Medium scale and very fine scale satellite imagery is collected by space agencies and increasingly by private satellite operators. These data awaits now to be processed into exposure information that can be used within disaster risk models. That conversion from imagery displaying the surface of the Earth into human settlement layers and then exposure parameters to be used in risk models is underway. However, image processing information technology infrastructure is not typically designed to process massive volume of data covering countries and continents. New initiatives like the Global Human Settlement Layer analysis system developed at the Joint Research Centre and presented herein aims to analyze human settlements globally. The system can process the gigantic data volume required to cover continents or even the entirety of the Earth’s land masses. The presentations will illustrate examples of human settlement layers to be used as proxy variables for exposure. In particular, the presentation will show example of continental wide human settlement mapping, on systematic comparison of largest metropolitan areas, on changes in the extent of human settlement in time, and will briefly illustrate the complexity of human settlements as seen from very detailed satellite imagery.