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  • This report presents the initial building vulnerability schema proposed for the Bushfire and Natural Hazards Collaborative Research Centre (BNHCRC) project entitled 'Improving the Resilience of Existing Housing to Severe Wind Events'. The project is a collaboration between the Cyclone Testing Station of James Cook University and Geoscience Australia. The report discusses the utility of a building schema and identifies which building attributes are the most important for distinguishing between housing classes of different vulnerabilities in the Australian building stock.

  • Report on an assessment of earthquake impact at three localities in WA for three return period earthquakes at each locality.

  • PLEASE NOTE: There is a more recent version of this product which can be accessed via the link on the right hand pane. It has been widely recognised that Light Detection And Ranging (LiDAR) data is a valuable resource for estimating the geometry of natural and artificial features. While the LiDAR point cloud data can be extremely detailed and difficult to use for the recognition and extraction of three dimensional objects, the Digital Elevation Model and Digital Surface Model are useful for rapidly estimating the horizontal extent of features and the height variations across those features. This has utility in describing the characteristics of buildings or other artificial structures. LiDAR is an optical remote sensing technology that can measure the distance from the sensor to a target area by illuminating the target area with light, often using pulses from a laser scanner. LiDAR has many applications in a broad range of fields, including aiding in mapping features beneath forest canopies, creating high resolution digital elevation and surface models. A Digital Surface Model (DSM) represents the earth's surface and includes all objects on it, while the Digital Elevation Model (DEM) represents the bare ground surface without any natural or artificial objects such as vegetation, structures and buildings. The Building Geometry Model (BGM) application is a Python-based software system, used to execute ArcGIS geoprocessing routines developed by Geoscience Australia, which can derive the horizontal and vertical extents and geometry information of building and other elevated features from LiDAR data. The Building Geometry Model algorithms were developed in response to the availability of LiDAR data for the development of exposure information for natural hazard risk analysis. The LiDAR derivatives were used to estimate building footprint areas, inter-storey heights across areas occupied by buildings, and eventually an estimate of gross floor area of different types of buildings. The design and development of the BGM application started in February 2012 as part of a natural hazard risk analysis project in the Philippines. Many of the examples of interface usage in this document contain references to locations and terms used in the Philippines. However, the BGM application has been designed to process data regardless of its geographic location. The object-oriented programming techniques and design patterns were used in the software design and development. In order to provide users with a convenient interface to run the application on Microsoft® Windows, a Python-based Graphical User Interface (GUI) was implemented in March 2012 and significantly improved in the subsequent months. The application can be either run as a command-line program or start via the GUI. The BGM application is currently benchmarked as Version 1.0 as it is still under development. This document is a user guide to the BGM GUI. It describes the main User Interface (UI) components, functionality and procedures for running the BGM processes via GUI.

  • In order for the Global Earthquake Model (GEM) to be able to calculate the impact of earthquakes it is necessary for it to be able to assess the building replacement cost at the level of individual buildings. This document outlines the methodology proposed by Geoscience Australia to determine the replacement cost for buildings. The methodology proposes a method for determining the rate (measured in currency per unit floor area) to reconstruct a building with given characteristics. The reconstruction cost is determined by multiplying the rate by the floor area. The methodology discusses the various factors that affect the rate and suggests sources where data on rates may be found.

  • The National Foreign Embassies dataset presents the spatial locations; in point format, of all known foreign embassies and high commissions within Australia.

  • Refined wind vulnerability curves for residential houses in Western Australia. The dataset contains heuristic vulnerability curves for individual communities in WA, initially provided by Geoff Boughton (JCU), and modified by Martin Wehner (GA), in line with commentary from Geoff that the curves are representative of individual houses. The vulnerability would increase in a community situation due to debris generation from upwind houses. An additional curve for the reinforced masonry/concrete roof houses observed in Exmouth is also included.

  • A raster representation of distances to the nearest transmission substation infrastructure, in 10km intervals.

  • An understanding of the vulnerability of the built environment to ground shaking is vital to the impact and risk assessment process. The vulnerability of Unreinforced Masonry (URM) buildings to earthquake hazard as been repeatedly demonstrated around the world. A portion of Australia's building stock is made up of legacy URM buildings dating from before the First World War. These buildings are typical of inner-city suburbs and the centres of country towns. The Kalgoorlie Earthquake of 20 April, 2010 offered the best opportunity to study the vulnerability of Australian URM buildings to ground shaking since the Newcastle Earthquake in 1989. The Kalgoorlie earthquake caused shaking of MMI intensity VI in Boulder and intensity V in Kalgoorlie. Damage was principally confined to turn-of-the-century URM buildings with only slight damage observed in more modern cavity masonry domestic residential buildings. Geoscience Australia led a post-event field survey to record damage to buildings in Boulder - Kalgoorlie. The survey recorded street-view imagery of the entire urban area and subsequently a detailed survey template was complete during a door-to-door foot survey. The foot survey targeted the entire population of turn-of-the-century buildings in Boulder-Kalgoorlie together with a sample of modern cavity masonry domestic residential buildings. The aim of the foot survey was to capture sufficient information to enable the calculation of a damage index (or loss ratio) for each surveyed building. The survey and subsequent analysis revealed an average damage index for turn-of-the-century URM buildings of 0.062 in Boulder (MMI VI) and 0.019 in Kalgoorlie (MMI V). These values are slightly higher than those reported post-Newcastle for ? . Difficulties encountered with computing damage indices for individual buildings are enumerated and recommendations are presented to improve future post-earthquake population surveys.

  • A conference paper describing GIS tools developed in support of the blast loss estimation capability for the Australian Reinsurance Pool Corporation. The paper focus is on GIS tools developed for: exposure database construction and integration of a number of datasets including 3D building geometry

  • The National Consulates dataset presents the spatial locations; in point format, of all known consulate facilities within Australia.