Currently a number of different landslide inventories exist in various databases within Australia, and each uniquely addresses a specific purpose. These databases range in scale and detail, and although some similarities and a number of common themes are apparent between databases, the method in which information is organised and described varies considerably.

ALOS Group Purchase is a new facility provided by ACRES for various approved customers/agencies to access the same ALOS data over a common area using ACRES online ordering.

Compute Sun and Moon Azimuth & Elevation To use this facility you need to know the latitude and longitude of the location for which you want to calculate the azimuth and vertical angle. There are several ways you can determine this:

The earthquake mapping tool allows you to: * view recent earthquakes which occurred over the past 30 days * search and explore all Australian earthquakes * search and explore earthquakes worldwide * view seismograms of earthquakes over the past 90 days * advise Geoscience Australia when you have felt a recent earthquake.

This database contains information on faults, folds and other features within Australia that are believed to relate to large earthquakes during the Neotectonic Era (i.e. the past 5-10 million years). The neotectonic feature mapping tool allows you to: * search and explore Australian neotectonic features * create a report for a feature of interest * download feature data and geometries as a csv file or kml file * advise Geoscience Australia if you have any feedback, or wish to propose a new feature.

An application to calculate geomagnetic field values in Australia using the 2010 Australian Geomagnetic Reference Field model (AGRF) model.

Digital elevation data which describes Australia's landforms and seabed is crucial for addressing issues relating to the impacts of climate change, disaster management, water security, environmental management, urban planning and infrastructure design. The National Elevation Data Framework (NEDF) vision is to ensure that decision makers, investors and the community have access to the best available elevation data to address the needs of today and the decades ahead.

The sample online image processing system allows you to create simple RGB images covering the Murwillumbah area on the east coast of Australia. It uses Landsat Thematic Mapper (TM) satellite data, and you can select different band combinations.

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.

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