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.

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.

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

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

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

SIFRA is the acronym for 'System for Infrastructure Facility Resilience Analysis'. The system provides an analytical approach for modelling the vulnerability of high-value infrastructure facilities by taking into consideration the fragilities and configurations of its constituent components. In doing this it uses a network theory based approach for modelling the facility and its operations. This method makes it possible to consider the discrete component-level vulnerabilities within a facility and, significantly, their system-level operational implications to the composite facility fragility. SIFRA also includes tools for modelling system restoration times under varied levels of resource allocation scenarios, and for identifying component criticality.

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

This document reports on a workshop held at Geoscience Australia during November, 2013 to develop vulnerability functions for buildings in the SE Asian region as input to the UNISDR's Global Assessment of Risk programme.

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

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.