This software package is used to produce Bushfire Attack Level (BAL), a measure of the severity of a building's potential exposure to bushfire, based on Method 1 in Australian Standard AS 3959 (2009)--Construction of buildings in bushfire-prone areas.

Seismological data are used for a variety of purposes, from earthquake hazard zonation to mapping Earth structure and mineral resource exploration. The immense volumes of seismic data now available challenge the application of routine seismic analysis techniques using existing tools. These tools fail to take advantage of recent advances in computing hardware and data formats. Given the scale of data to process and the computational complexity of algorithms involved, a more efficient approach that scales on high-performance computing and data (HPC-HPD) platforms is needed. In addition, different agencies have tended to use bespoke and ad hoc data formats, data curation processes and quality standards, hindering large-scale analyses and modelling. High-performance seismological tools (HiPerSeis) facilitate the transformation of source seismological data into formats geared towards HPC-HPD platforms. HiPerSeis also implements optimised seismological workflows that can be run at large scale on HPC-HPD platforms. <b>Citation:</b> Hassan, R., Hejrani, B., Medlin, A., Gorbatov, A. and Zhang, F., 2020. High-performance seismological tools (HiPerSeis). In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

TBC

Generic Geoscience Australia, web based, external database entry kit

This relates to the release of ANUGA as open-source software. No abstract required. See http://sourceforge.net/projects/anuga/

EarthSci is an Eclipse RCP platform for creating applications for the visualisation of earth science data. It is an evolution of the existing GA World Wind Suite built on the NASA World Wind Java SDK. The vision for EarthSci is to take the best features of the GA World Wind Suite (Geological model support, WMS/WFS support, tiled data preparation, keyframe animation etc.) and combine them with the best features of the Eclipse platform (modular plugin architecture, in-built help, native windowing, model-based UI) to create a flexible platform with powerful science visualisation features. As development progresses more and more features will be added. https://github.com/GeoscienceAustralia/earthsci

Airborne Electromagnetic data are being acquired by Geoscience Australia in areas considered to have potential for uranium or thorium mineralisation under the Australian Government's Onshore Energy Security Program (OESP). The surveys have been managed and interpreted by Geoscience Australia's Airborne Electromagnetic Acquisition and Interpretation project. In contrast to industry style deposit scale investigations, these surveys are designed to reveal new geological information at regional scale. The Frome Embayment AEM survey was acquired using the TEMPESTTM AEM system by Fugro Airborne Surveys under contract to GA. The survey covers a total of 32 300 line km and an area of 95 450 km2, the largest AEM survey by area ever flown in Australia. This data release contains the Phase-1 data, that is, contractor quality-controlled and quality-assessed data fas well as the Phase-2 data, that is Geoscience Australia layered earth inversion (GA-LEI) data and derived products for the Callabonna Uranium Infill Area. The data and products described in this report are available from the GA AEM website.

Python Source Code for AGDC project. The AGDC is a system for managing large volumes of time-varying gridded data. It will become a common analytical framework for disparate geoscientific gridded datasets.

A fully four-dimensional (3D x time) object-oriented biophysical dispersal model was developed to simulate the movement of marine larvae over semi-continuous surfaces. The model is capable of handling massive numbers of simulated larvae, can accommodate diverse life history patterns and distributions of characteristics, and saves point-level information to a relational database management system.

No abstract available