Evidence based disaster management enables decision makers to manage more effectively because it yields a better informed understanding of the situation. When based on evidence, the decision making process delivers more rational, credible and objective disaster management decisions, rather than those influenced by panic. The translation of fundamental data into information and knowledge is critical for decision makers to act and implement the decisions. The evidence from appropriate information helps both tactical and strategic responses to minimise impacts on community and promote recovery. The information requirements of such a system are quite comprehensive in order to estimate the direct and indirect losses; the short and long term social and economic resilience. Disasters may be of rapid onset in nature like earthquakes, tsunamis and blast. Others are slow onset such those associated with gradual climate change. Climate change has become a real challenge for all nations and the early adaptors will reduce risk from threats such as increased strength of tropical cyclones, storm surge inundations, floods and the spread of disease vectors. The Australian Government has recognised the threats and prioritised adaptation as an opportunity to enhance the nation's existing infrastructure and thereby reduce risk. A thorough understanding of the exposure under current and future climate projections is fundamental to this process of future capacity building. The nation's exposure to these increased natural hazards includes all sectors from communities to businesses, services, lifeline utilities and infrastructure. The development of a 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 multi-hazard impacts.

Note: A more recent version of this product is available. This dataset contains the high voltage electricity transmission lines that make up the electricity transmission network in Australia. For government use only. Access through negotiation with Geoscience Australia

Disaster management is most effective when it is based on evidence. Evidence-based disaster management means that decision makers are better informed, and the decision making process delivers more rational, credible and objective disaster management outcomes. To achieve this, fundamental data needs to be translated into information and knowledge, before it can be put to use by the decision makers as policy, planning and implementation. Disaster can come in all forms: rapid and destructive like earthquakes and tsunamis, or gradual and destructive like drought and climate change. Tactical and strategic responses need to be based on the appropriate information to minimise impacts on the community and promote subsequent recovery. This implies a comprehensive supply of information, in order to establish the direct and indirect losses, and to establish short and long term social and economic resilience. The development of the National Exposure Information System (NEXIS) is a significant national project being undertaken by Geoscience Australia (GA). NEXIS collects, collates, manages and provides the information required to assess multi-hazard impacts. Exposure information may be defined as a suite of information relevant to all those involved in a natural disaster, including the victims, the emergency services, and the policy and planning instrumentalities.

Exposure refers to the elements at risk which may be subjected to the impact of severe hazards within a defined geographic area or region. These elements include the built environment, i.e buildings, infrastructure services and utilities, and also population and business activity. Geoscience Australia (GA) is developing the National Exposure Information System (NEXIS) as a national capability to provide an exposure profile to underpin analysis of natural hazards; potential disaster footprints, risk assessments and climate change adaptation research. The NEXIS capability enables modelling to gain a greater understanding of the impact and risk exposure to these events. The information is used to inform evidence based decision making and future planning to aid in the prevention, preparedness, response and recovery to severe hazard events and climate change adaptation. The current NEXIS database provides exposure profile on building type, building construction materials (roof and wall), number of floors, floor area, year built and population demographics, business activity (turnover) and employee numbers. NEXIS is a demonstrated capability used in response to Tropical Cyclone Yasi, Victoria Bushfires, Queensland Floods and other recent national disaster events. The database also provides input data for use with the Earthquake Risk Model (EQRM) and Tropical Cyclone Risk Model (TCRM) to estimate direct and indirect losses to the built environment and possible population casualities. Further development of the database is planned to incorporate infrastructure and facilities data to enhance the capability and availability of nationally consistent data and exposure information.

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.

Manila is one of the world's megacities, and the Greater Metro Manila Area is prone to natural disasters. These events may have devestating consequences for individuals, communities, buildings, infrastructure and economic development. Understanding the risk is essential for implementing Disaster Risk Reduction programs. In partnership with AusAID, Geoscience Australia is providing technical leadership for risk analysis projects in the Asia-Pacific Region. In the Philippines, Geoscience Australia is engaging with Government of the Philippines agencies to deliver the "Enhancing Risk Analysis Capacities for Flood, Tropical Cyclone Severe Wind and Earthquake in the Greater Metro Manila Area" Project.

Large research initiatives such as the Global Earthquake Model (GEM) or the Seismic HAzard haRmonization in Europe (SHARE) projects concentrate a great collaborative effort for defining a global standard for seismic hazard estimations. In this context, there is an increasing need for identifying ground motion prediction equations (GMPEs) that can be applied at both global and regional scale. With increasing amounts of strong motion records which are now available worldwide, observational data can provide a valuable resource to tackle this question. Using the global dataset of Allen and Wald (2009), we evaluate the ability of fifteen GMPEs for active shallow crustal regions to predict ground-motion in California, Japan, Europe and Middle East, Italy and Turkey. Adopting the approach of Scherbaum et al. (2009), we rank these GMPEs according to their likelihood of having generated the data. In particular, we estimate how strongly data support or reject the models with respect to the state of non-informativeness defined by a uniform weighting. Such rankings derived from this particular global dataset enable us to determine conditions in terms of magnitudes and distances under which a model could be applied in its main region of derivation but also in other regions. In the ranking process, we particularly focus on the influence of the distribution of the testing dataset compared to the GMPE's native dataset. One of the results of this study is that some non-indigenous models present a high degree of consistency with the data from a target region. Two models in particular demonstrated a strong power of geographically wide applicability in different geographic regions with respect to the testing dataset: the models of Akkar and Bommer (2010) and Chiou et al. (2010).

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.

The impacts of climate change, including sea level rise and the increased frequency of storm surge events, will adversely affect infrastructure in a significant number of Australian coastal communities. In order to quantify this risk and develop suitable adaptation strategies, the Department of Climate Change and Energy Efficiency (DCCEE) commissioned the National Coastal Vulnerability Assessment (NCVA). With contributions from Geoscience Australia (GA) and the University of Tasmania, this first-pass national assessment has identified the extent and value of infrastructure that is potentially vulnerable to impacts of climate change. In addition, the NCVA examined the changes in exposure under a range of future population scenarios. The NCVA was underpinned by a number of fundamental national scale datasets; a mid-resolution digital elevation model (DEM) used to model a series of sea level rise projections incorporating 1 in 100 year storm-tide estimates where available; the 'Smartline' (nationa; coastal geomorphology dataset) identified coastal landforms that are potentially unstable and may recede with the influence of rising sea level. The inundation outputs were then overlain with GA's National Exposure Information System to quantify the number and value of infrastructure elements (including residential and commercial buildings, roads and rail) potentially vulnerable to a range of sea-level rise and recession estimates for the year 2100.

Hydrometeorological events make up or contribute to a majority of disasters in Australia and around the world. Scientists expect climate change will accelerate the frequency and intensity of these events in the future. Information on the location and characteristics of the built and social environment combined with hazard modelling and spatial analysis can facilitate the identification of buildings, people and infrastructure exposed to a particular natural hazard event. This information informs evidence based decision making and future planning to aid in the preparedness, response and recovery to severe hazard events. In Australia, the National Exposure Information System (NEXIS) is a significant national project being undertaken by Geoscience Australia (GA). In 2006 GA embarked on the development of NEXIS in response to the Council of Australian Governments (COAG) reform commitment on Australian's ability to manage natural disasters and other emergencies. The COAG commitment called for the establishment of a 'nationally consistent system of data collection, research and analysis to ensure a sound knowledge base on natural disasters and disaster mitigation' (DOTARS 2002). NEXIS database contains information on buildings, people, businesses and infrastructure and is derived from publicly available demographic, structural, economic and statistical data. Exposure profiles contain information on: building type, size, construction materials, age, replacement costs and population demographics for all residential, commercial and industrial buildings in Australia. Aggregated exposure information underpins risk assessment, emergency management, climate change adaptation, urban planning, insurance industry and research to help assist evidence based decision making. NEXIS development and operationalisation is crucial to support the decision makers and underpins community safety, emergency management and disaster risk reduction initiatives Australia This paper will discuss the development of NEXIS and its application in several national projects with the Department of Climate Change Energy and Efficiency (DCCEE) in Australia and recent national disaster impacts assessments on: Queensland tropical cyclone Yasi, Victoria bushfires and the Queensland floods.