We investigate the characteristics of regolith through the application of statistical learning to diverse layers of terrestrial, continental-scale remote sensing data. This combination allows us to explore the multiple influences of bedrock, climate, biota, landscape and time on regolith development and properties: an interdisciplinary geoscience modeling problem. From a wide variety of available data for Australia, we select remote sensing, geophysical, geomorphological and mineralogical inputs with good spatial coverage. We use Self- Organizing Maps (SOM), a topologically constrained unsupervised statistical learning algorithm, to characterize the geophysical and mineralogical signatures of regolith and bedrock. Regolith covers more than 80% of the Australian continent, ranges in age from Precambrian to Quaternary and varies in thickness from a few meters to more than a kilometer. The diversity of preserved regolith across Australia therefore provides a rich demonstration example of knowledge discovery from remote sensing data in the case of diverse inputs and complex interactions. The outputs of our SOM analysis are combined with ground observations from locations showing naturally occurring anomalous concentrations of nickel, tin and uranium. We identify a minimum number of natural groups, or clusters, indicating subtle but significant differences in regolith and bedrock mineralization characteristics. Our results show that SOM identifies spatially contiguous regions representing unique regolith and bedrock materials. In the Yilgarn Craton we observe key differences in landscape character, density of the crust, and relative abundance of radioactive elements, and alumino-silicate and ferric oxide minerals. These properties discriminate between nickel-prospective in situ deeply weathered regolith formed on mafic and/or ultramafic bedrock and uranium-prospective Cainozoic paleochannels containing felsic bedrock source materials. National scale data are publicly available for many continental regions, as in the Australian example, and our approach has wide general applicability. We hence demonstrate that remote sensing data may be used to understand the multiple influences on regolith, revealing the interplay between environmental history and bedrock character at regional scales, and differences between in situ and transported regolith, provenance of source materials and their relative ages.

This report presents new Sensitive High Resolution Ion Micro Probe (SHRIMP) U-Pb geochronological results obtained during the Geological Survey of Queensland-Geoscience Australia (GSQ-GA) Geochronology project between July 2010 and June 2012. A total of 24 samples were analysed, in support of ongoing regional geoscientific investigations and mapping programs by the GSQ. This report documents detailed results for each sample individually, encompassing sample location and geological context, a description of the target mineral for geochronology, the relevant analytical data, and a brief geochronological interpretation. A summary of all results from this study is presented in Table i, and the sample locations are shown in Figure i. The analysed samples are from regions extending from the Eulo Ridge, an exposed part of the mainly concealed Thomson Orogen in south-western Queensland, to the Charters Towers and Greenvale regions in the north and the Mount Isa region in the north-west (Figure i). The work was carried out to provide an improved time framework for updated interpretations of the geology of selected parts of the state.

Exposure is referred to as the elements at risk within a given area that have been, or could be, subject to the impact of natural hazards. The elements include buildings, assets, population, economic activities, services, utilities and infrastructure. Describing these elements in a nationally consistent exposure information framework provides a reliable base to inform decision making for natural hazard risk reduction. Decision making at various levels of the disaster management governance process is complex and depends on multiple attributes, objectives, criteria and functions. Exposure modelling capabilities such as the National Exposure Information System (NEXIS) compile comprehensive datasets to derive spatial and descriptive attributes such as usage, asset type, construction type, replacement cost and population. The National Hazard Exposure Modelling Framework attempts to bridge the existing gaps in capabilities using a systematic approach aligned with the National Emergency Risk Assessment Guidelines. The Natural Hazard Exposure Modelling Framework aims to address issues in the Data and Knowledge, Disaster Resilience, Resource Assessment, Emergency Management, Risk Mitigation Policy and Planning research themes identified by the Bushfire and Natural Hazard CRC. The project consists of developing a built environment exposure framework, business exposure elements, national standards for implementation and model to estimate reliability. The Built Environment Exposure Framework consists of buildings and infrastructure assets and associated activities information underpinning all levels of disaster management. The Business Activity Exposure Framework supports to assess business continuity, disruption, resilience and recovery indicators in disaster management. National Exposure Information Standards assists to ensure consistency in definitions. The Reliability Assessment Framework supports to assess uncertainty in the data to understand its reliability for various end users. The outcomes of the framework will enable authorities to develop robust, reliable, consistent and sustainable exposure information capabilities to assist governments and industry to make evidence based decisions making for community safety.

This report outlines the high precision level survey completed between the SEAFRAME (Sea Level Fine Resolution Acoustic Measuring Equipment) Tide Gauge Station and continuous GNSS (Global Navigation Satellite System) station in Rarotonga, Cook Islands from 5th to 9th December2012.

This report outlines the high precision level survey completed between the SEAFRAME tide gauge and continuous GPS station in Tarawa, Kiribati from 23 - 30 April 2012.

This report outlines the high precision level survey completed between the Sea Level Fine Resolution Acoustic Measuring Equipment (SEAFRAME) tide gauge and the Continuous Global Navigation Satellite System (CGNSS) Station in Tarawa, Kiribati from 15th - 22nd August 2013.

This report outlines the high precision level survey completed between the SEAFRAME (Sea Level Fine Resolution Acoustic Measuring Equipment) tide gauge and continuous GNSS (Global Navigation Satellite System) station in Manus Island, Papua New Guinea from 9th to 12th September 2012.

This report outlines the levelling survey completed during the visit to Pohnpei, Federated States of Micronesia (FSM) from 2nd to 9th August 2012.

This report outlines the levelling survey completed during the visit to Nauru from 6 to 15 February 2012.

This report outlines the high precision level survey completed between the Sea Level Fine Resolution Acoustic Measuring Equipment (SEAFRAME) tide gauge and continuous Global Navigational Satellite System (GNSS) station in Apia, Western Samoa from 21st May to 2nd June 2013.