A comprehensive earthquake impact assessment requires an exposure database with attributes that describe the distribution and vulnerability of buildings in the region of interest. The compilation of such a detailed database will require years to develop for a moderate-sized city, let alone on a national scale. To hasten this database development in the Philippines, a strategy has been employed to involve as many stakeholders/organizations as possible and equip them with a standardized tool for data collection and management. The best organizations to tap are the local government units (LGUs) since they have better knowledge of their respective area of responsibilities and have a greater interest in the use of the database. Such a tool is being developed by PHIVOLCS-DOST and Geoscience Australia. Since there are about 1,495 towns and cities in the country with varying financial capacities, this tool should involve the use of affordable hardware and software. It should work on ordinary hardware, such as an ordinary light laptop or a netbook that can easily be acquired by these LGUs. The hardware can be connected to a GPS and a digital camera to simultaneously capture images of structures and their location. The system uses an open source database system for encoding the building attributes and parameters. A user-friendly GUI with a simplified drop-down menu, containing building classification schema, developed in consultation with local engineers, is utilised in this system. The resulting national database is integrated by PHIVOLCS-DOST and forms part of the Rapid Earthquake Damage Assessment System (REDAS), a hazard simulation tool that is also made available freely to partner local government units.

As part of the Climate Futures for Tasmania project (CFT) Geoscience Australia's Risk and Impact Analysis Group (RIAG) is conducting a severe wind hazard assessment for Tasmania under current climate conditions as well as two future climate scenarios. The assessment uses climate-simulated data generated by a high resolution regional model. A poster presented to this workshop shows the main results of the project [1]; a brief description of the methodology developed for the project is discussed in a paper also presented to this workshop [2]. In this paper three possible sources of error in the calculation of the severe wind hazard (using the methodology discussed in [2]) will be examined and recommendations on ways to improve the model results will be provided.

11-5519 Metropolitan Manilla (Philippines). Philippine GIS data-sets should arrive from the source on the 15th of July, 2011. GAV will process the data, and produce a short movie. The movie will reveal the 17 town halls of the greater metro Manilla; and outline the fault line, as well as earthquake affected areas, flood affected areas and cyclone affected areas. This movie is for the Philippine Govt. via Ausaide, and will include photographs of Philippine nationals assisting in disaster reduction work. The aquired data-sets will be stored on the GA data store, where access can be gained through communication with Luke Peel - GEMD National Geographic Information Section, Geoscience australia.

The National Exposure Information System (NEXIS) project is an initiative of Geoscience Australia in response to the Australian Government's research priority of safeguarding Australian communities from natural hazards, critical infrastructure failures and policy development. The governmental priority urges the implementation of a 'nationally consistent system of data collection, research and analysis to ensure a sound knowledge-base on natural disasters and disaster mitigation'. The infrastructure exposure definition and development framework suitable for multi hazards and climate change impact analysis is highly complex. NEXIS aims to meet the challenge by collecting, collating and maintaining nationally consistent exposure information at the individual building level. This requires detailed spatial analysis and the integration of available demographic, structural and statistical data for various sectors. The system integrates data from several national spatial databases, such as the Geocoded National Address File, the Property Cadastre, Australian Bureau of Statistics (ABS) census data, and building data from Australian state governments. It also includes post disaster survey information and data from several infrastructure agencies and local government bodies. NEXIS provides a representative assessment of asset exposure to several hazard models which can be aggregated to an appropriate level from State to mesh block level for the required application. By integrating the information with the decision-support tools of alert systems and early warning, it can enable the rapid forecasting of the impacts due to various hazards (infrastructure damage and casualties). Currently it is being used for tactical response for emergency managers and strategic policy and planning development. In addition to enabling research in Geoscience Australia's risk and impact analysis projects, it supports several government initiatives across the departments and national committees.

In order to calibrate earthquake loss models for the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) system, two databases have been developed: an Atlas of ShakeMaps and a catalog of human population exposures to moderate to strong ground shaking (EXPO-CAT). The full ShakeMap Atlas currently contains over 5,600 earthquakes from January 1973 through December 2007, with almost 500 of these maps constrained by instrumental ground motions, macroseismic intensity data, community internet intensity observations, and published earthquake rupture models. The catalog of human exposures is derived using current PAGER methodologies. Exposure to discrete levels of shaking intensity is obtained by merging Atlas ShakeMaps with a global population database. Combining this population exposure dataset with historical earthquake loss data provides a useful resource for calibrating loss methodologies against a systematically-derived set of ShakeMap hazard outputs. Two applications of EXPO-CAT are illustrated: i) a simple objective ranking of country vulnerability to earthquakes, and; ii) the influence of time-of-day on earthquake mortality. In general, we observe that countries in similar geographic regions with similar construction practices tend to cluster spatially in terms of relative vulnerability. We find only limited quantitative evidence to suggest that time-of-day is a significant factor in earthquake mortality. Finally, we combine all the Atlas ShakeMaps to produce a global map of the peak ground acceleration (PGA) observed in the past 35 years, and compare this composite ShakeMap with existing global hazard models. In general, these analyses suggest that existing global and regional hazard maps tend to overestimate hazard.

This paper is an introduction to the two AJEM Special Issues on risk assessment. The role of risk assessment in emergency management in Australia is firmly established and much progress has been made in utilising risk modelling tools and supporting data to develop new information on risk for some hazards. Significant further work is required to reach an understanding of all hazards risks nationally.

A model to assess severe wind hazard using climate-simulated wind speeds has been recently completed at Geoscience Australia. The model can calculate return period of wind speeds over a given region considering current as well as future climate conditions. The winds extracted from the climate simulations are winds at 10m height over open terrain. In hazard studies it is important however, to refer the wind speeds to the characteristics of the given location in order to calculate the actual severe wind hazard at the regional level. This is achieved by multiplying the generic wind hazard by a number of wind multipliers. One of those multipliers is wind direction. The wind direction multiplier recognises the prevailing direction of the strongest winds and affects the wind hazard accordingly. Lower wind hazard would correspond to the direction of low wind speeds. In practical applications engineers calculate the wind load in structures by multiplying the design wind speeds recommended by the Australian/NZ standards for wind loading in structures (AS/NZS 1170.2:2010) by some generic multipliers also given in the standards. The multipliers have been developed considering a number of Bureau of Meteorology (BoM) weather recording stations at particular locations in Australia; this method cannot capture the actual regional characteristics in such a vast country like Australia. In this paper we propose a new methodology for calculation of wind direction multipliers based on wind speeds and direction extracted from climate simulations. Our method allows a more realistic assessment of the wind direction multiplier at a particular region.

An increase in the frequency and intensity of storms, coastal flooding, and spread of disease as a result of projected climate change and sea-level rise is likely to damage built environments and adversely affect a significant proportion of Australia's population. Understanding the assets at risk from climate change hazards is critical to the formulation of adaptation responses and early action is likely to be the most cost effective approach to managing the risk. Understanding the level of exposure of assets, such as buildings, lifeline utilities and infrastructure, under current and future climate projections is fundamental to this process. The National Exposure Information System (NEXIS) is a significant national capacity building task being undertaken by Geoscience Australia (GA). NEXIS is collecting, collating, managing and providing the exposure information required to assess climate change impacts. It provides residential, business and infrastructure exposure information derived from several fundamental datasets. NEXIS is also expanding to include institutions (such educational, health, emergency, government and community buildings) and lifeline support infrastructure exposure. It provides spatial exposure data in GIS format at a building level and is often provided to clients for an area of interest. It is also designed to predict future exposure for climate change impact analysis. NEXIS is currently sourcing more specific datasets from various data custodians including state and local governments along with private data providers. NEXIS has been utilised in various climate change impact projects undertaken by CSIRO, the Department of Climate Change (DCC), the Department of Environment, Water, Heritage and the Arts (DEWHA), and several universities. Examples of these projects will be outlined during the presentation.

Imagine you are an incident controller sitting in front of a computer screen that is showing you where a fire that's just started is likely to head. Not just that, but also what houses and other structures in the fire's path are likely to burn, and even the number and type of people living in the area - children, adults, elderly. In addition imagine that you can quantify the uncertainty in both the fire weather and also the state of the vegetation so as to deliver a range of simulations relating to the expected firespread which allow the incident controller to address 'what if' scenarios. Think of the advantages of such a program in making speedy, accurate decisions about where best to send fire trucks and fire-suppression aircraft; in being able to issue timely, locality-specific warning messages; in judging whether this fire will become so bad that it might warrant recommending not only an early, orderly evacuation of communities in its way, but also identifying the least risky roads for people to get to safety. A computer program that will not only be able to help with all this and more in a fire, but will also be capable of use at any time in identifying what structures, streets and communities would be at risk should a fire occur, enabling those at risk to undertake remedial work around their properties in advance to make them better fire-ready. This will be achieved by building up a library of possible / credible fire impact scenarios based on the knowledge of observed (historical) severe fire weather conditions as well as vegetation information (fuel type/amount/moisture).

Geoscience Australia (GA) is currently undertaking a process of revising the Australian National Earthquake Hazard Map using modern methods and an updated catalogue of Australian earthquakes. This map is a key component of Australia's earthquake loading standard, AS1170.4. Here we present an overview of work being undertaken within the GA Earthquake Hazard Project towards delivery of the next generation earthquake hazard map. Knowledge of the recurrence and magnitude (including maximum magnitude) of historic and pre-historic earthquakes is fundamental to any Probabilistic Seismic Hazard Assessment (PSHA). Palaeoseismological investigation of neotectonic features observed in the Australian landscape has contributed to the development of a Neotectonic Domains model which describes the variation in large intraplate earthquake recurrence behaviour across the country. Analysis of fault data from each domain suggests that maximum magnitude earthquakes of MW 7.0-7.5±0.2 can occur anywhere across the continent. In addition to gathering information on the pre-historic record, more rigorous statistical analyses of the spatial distribution of the historic catalogue are also being undertaken. Earthquake magnitudes in Australian catalogues were determined using disparate magnitude formulae, with many local magnitudes determined using Richter attenuation coefficients prior to about 1990. Consequently, efforts are underway to standardise magnitudes for specific regions and temporal periods, and to convert all earthquakes in the catalogue to moment magnitude. Finally, we will review the general procedure for updating the national earthquake hazard map, including consideration of Australian-specific ground-motion prediction equations. We will also examine the sensitivity of hazard estimates to the assumptions of certain model components in the hazard assessment.