Geospatial Bayesian Methods for Disaster Impact Estimation

In the first hours and days following a disaster event (such as an earthquake or cyclone), a number of critical decisions are made in the coordination of response and relief efforts. These include decisions regarding the locations of emergency infrastructure, the amount of funding provided by major humanitarian donors, and the mobilisation of emergency aid.

The goal of this project is the further development of the Oxford Disaster Displacement Real-time Information Network (ODDRIN), a tool aiming to provide initial estimates of the humanitarian impact of a disaster event. ODDRIN combines real-time information on hazard severity with existing data describing population exposure and vulnerability such as population density and GNP.

Via the model, this is then used to estimate humanitarian impacts such as population displacement. ODDRIN currently focuses on earthquake impact estimation.

The contribution of this research is the development of a unified prediction tool for mortality, displacement and building destruction that has been fitted using Bayesian methodologies and benefits from the associated uncertainty quantification. Currently, the main providers of hazard impact estimates include the Global Disaster Alert and Coordination System (GDACS), Hazard-US (HAZUS), the Pacific Data Center (PDC), and Climate-Adapt.

These tools either require data that prevents them from being applied globally, do not offer numeric human impact estimates, or do not accessibly provide a transparent underlying model.

The aims of this project include the further development of ODDRIN to predict mortality and aggregated building damage; applying and developing Bayesian approaches to fit the model; leveraging high-performance computing resources to accelerate model fit; and validating the model fit using testing data. Fitting and testing the model also requires the collection and processing of data from a range of sources including the Emergency Events Database (EMDAT), the Center for International Earth Science Information Network (CIESIN), the World Bank, Open Street Maps, and the United States Geological Survey (USGS).

Further objectives will include the extension of ODDRIN to sustained events such as cyclones and floods, and the development of an online interface through which users can apply ODDRIN and investigate performance on historical events. This project falls within the EPSRC Statistics and Applied Probability research area.