The development of climate change adaptation policies must be underpinned by a sound understanding of climate change risk. As part of the Hyogo Framework for Action, governments have agreed to incorporate climate change adaptation into the risk reduction process. This paper explores the nature of climate change risk assessment in the context of human assets and the built environment. More specifically, the paper's focus is on the role of spatial data which is fundamental to the analysis. The fundamental link in all of these examples is the National Exposure Information System (NEXIS) which has been developed as a national database of Australia's built infrastructure and associated demographic information. The first illustrations of the use of NEXIS are through post-disaster impact assessments of a recent flood and bushfire. While these specific events can not be said to be the result of climate change, flood and bushfire risks will certainly increase if rainfall or drought become more prevalent, as most climate change models indicate. The second example is from Australia's National Coastal Vulnerability Assessment which is addressing the impact of sea-level rise and increased storms on coastal communities on a national scale. This study required access to or the development of several other spatial databases covering coastal landforms, digital elevation models and tidal/storm surge. Together, these examples serve to illustrate the importance of spatial data to the assessment of climate change risk and, ultimately, to making informed, cost-effective decisions to adapt to climate change.

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).

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 is a short and informative 3.3 minute movie for the Engineering, Economics and Exposure Project - NEXIS Development for DCCEE - late 2010. It is a promotional movie that demonstrates NEXIS capabilities, and explains how NEXIS will be benefitial to the NEXIS stakeholder. This movie may also go onto the web, where it's purpose is to convince the public that NEXIS is a worthwhile investment in Australia's future.

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.

This project aims to improve the estimation of tropical cyclone risk in the Australian region by employing a numerical simulation approach based on a climate model. Climate models are the main tools used for predicting the effects of climate change, but usually they have employed resolutions too coarse to simulate reliably smaller weather systems such as tropical cyclones. In this work, a regional climate model of unprecedented fine resolution (the CSIRO regional model CCAM) will be implemented over the Australian region and an improved estimate both of present-day and future tropical cyclone hazard will be made. When combined with the results of a tropical cyclone damage model, new estimates of the tropical cyclone risk to infrastructure in northern Australia will be obtained

This is a short and informative 5.0 minute movie for the Engineering, Economics and Exposure Project - NEXIS Development for DCCEE. This second version of the movie is based on the original NEXIS movie (10-4830 created in late 2010). This 11-5376 movie is a promotional movie that demonstrates NEXIS capabilities, and explains how NEXIS will be benefitial to the NEXIS stakeholder. This movie may also go onto the web, where it's purpose is to convince the public that NEXIS is a worthwhile investment in Australia's future.

Effective disaster risk reduction is founded on knowledge of the underlying risk. While methods and tools for assessing risk from specific hazards or to individual assets are generally well developed, our ability to holistically assess risk to a community across a range of hazards and elements at risk remains limited. Developing a holistic view of risk requires interdisciplinary collaboration amongst a wide range of hazard scientists, engineers and social scientists, as well as engagement of a range of stakeholders. This paper explores these challenges and explores some of the common and contrasting issues sampled from a range of applications addressing earthquake, tsunami, volcano, severe wind, flood, and sea-level rise from projects in Australia, Indonesia and the Philippines. Key issues range from the availability of appropriate risk assessment tools and data, to the ability of communities to implement appropriate risk reduction measures. Quantifying risk requires information on the hazard, the exposure and the vulnerability. Often the knowledge of the hazard is reasonably well constrained, but exposure information (e.g., people and their assets) and measures of vulnerability (i.e., susceptibility to injury or damage) are inconsistent or unavailable. In order to fill these gaps, Geoscience Australia has developed computational models and tools which are open and freely available. As the knowledge gaps become smaller, the need is growing to go beyond the quantification of risk to the provision of tools to aid in selecting the most appropriate risk reduction strategies (e.g., evacuation plans, building retrofits, insurance, or land use) to build community resilience.

The dataset contains spatial locations in point format as a representation of Immigration Detention Facilities in Australia. Definition: Immigration detention centres primarily accommodate people who have overstayed their visa, breached their visa conditions and had their visa cancelled or have been refused entry at Australia's entry ports.

This point dataset contains the major airport control towers in Australia.