The coverage of this dataset is over the Taree region . The C3 LAS data set contains point data in LAS 1.2 format sourced from a LiDAR ( Light Detection and Ranging ) from an ALS50 ( Airborne Laser Scanner ) sensor . The processed data has been manually edited to achieve LPI classification level 3 whereby the ground class contains minimal non-ground points such as vegetation , water , bridges , temporary features , jetties etc . Purpose: To provide fit-for-purpose elevation data for use in applications related to coastal vulnerability assessment, natural resource management ( especially water and forests) , transportation and urban planning . Additional lineage information: This data has an accuracy of 0.3m ( 95 confidence ) horizontal with a minimum point density of one laser pulse per square metre. For more information on the data's accuracy, refer to the lineage provided in the data history .

Double-sided A3 map showing Australia's major petroleum resources and pipelines (one side) and current onshore and offshore petroleum exploration licences plus the location of the proposed offshore 2012 acreage release areas (flip-side). This map is mainly used as a promotional tool for the international NAPE exhibition.

We present the first national probabilistic tsunami hazard assessment (PTHA) for Indonesia. This assessment considers tsunami generated from near-field earthquakes sources around Indonesia as well as regional and far-field sources, to define the tsunami hazard at the coastline. The PTHA methodology is based on the established stochastic event-based approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. The earthquake source information is primarily based on the recent Indonesian National Seismic Hazard Map and included a consensus-workshop with Indonesia's leading tsunami and earthquake scientists to finalize the seismic source models and logic trees to include epistemic uncertainty. Results are presented in the form of tsunami hazard maps showing the expected tsunami height at the coast for a given return period, and also as tsunami probability maps, showing the probability of exceeding a tsunami height of 0.5m and 3.0m at the coast. These heights define the thresholds for different tsunami warning levels in the Indonesian Tsunami Early Warning System (Ina-TEWS). The results show that for short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, the islands of Nias and Mentawai. For longer return periods (>500 years), the tsunami hazard in Eastern Indonesia (north Papua, north Sulawesi) is nearly as high as that along the Sunda Arc. A sensitivity analysis of input parameters is conducted by sampling branches of the logic tree using a monte-carlo approach to constrain the relative importance of each input parameter. These results can be used to underpin evidence-based decision making by disaster managers to prioritize tsunami mitigation such as developing detailed inundation simulations for evacuation planning.

5 maps showing the offshore petroleum blocks in the Shared Area of the Perth Treaty. Also supplied were 4 Excel spreadsheets containing the listing of the blocks within the Perth Treaty. Requested by NOPTA 5th December 2012. Supplied as DRAFT in December, resubmitted without draft & new title on 12th February 2013 to RET & DFAT. LOSAMBA register 674.

My First Record

These datasets cover approximately 5030 sq km over all of the Scenic Rim Regional Council and were captured as part of the 2011 Scenic Rim LiDAR project. This project, undertaken by Terranean Mapping Technologies on behalf of the Queensland Government captured highly accurate elevation data using LiDAR technology. Available dataset formats (in 1 kilometre tiles) are: - Classified las (LiDAR Data Exchange Format where strikes are classified as ground, vegetation or building) - 1 metre Digital Elevation Model (DEM) in ASCII xyz - 1 metre Digital Elevation Model (DEM) in ESRI ASCII grid - 1 metre Digital Elevation Model (DEM) in ESRI GRID grid - 0.25 metre contours in ESRI Shape

This study brings together a wide range of datasets to provide a comprehensive assessment of the Pandurra Formation sedimentology and geochemistry in 3D. Sedimentology and geochemistry datasets generated this study are combined with pre-existing data to generate a 3D interpretation of the Pandurra Formation and improve understanding of how the Pandurra formation as we see it to today was deposited and subsequently post-depositionally mineralised.

Structures and structural (tectonic) processes provide critical controls on the evolution of hydrothermal mineral systems, both as pathways for fluid flow and as a trigger or driver. Not all these structures or tectonic processes are, however, necessarily obvious, particularly when the scale of study is restricted to a mineral deposit alone. This is because mineral deposits are just a `symptom' of a much larger system 'a mineral system' which involves enormous energy and mass fluxes. Using mineral systems thinking is a powerful tool for explorers. The scale of a mineral system is many orders of magnitude larger than the individual mineral deposit, and consequently, the system offers a far larger target than the deposit. For example, a deposit only 500 m wide may have a fluid outflow zone many tens of kilometres wide, such as in the Eastern Goldfields. Similarly, the zone of depletion of the metal-rich source rock may be many tens of kilometres in extent, such as in Broken Hill. A mineral system is a generic concept. Here, I use an example from the gold mineral system of the Eastern Goldfields Superterrane of Western Australia to consider some of the less obvious, but nevertheless important, structures and their attendant processes, as well how to recognise them.

Modern geodetic techniques, especially the Global Positioning System (GPS) have allowed the accurate determination of the Earth's surface deformation of Glacial Isostatic Adjustment (GIA) associated with the ongoing stress release of the viscoelastic mantle after removal of the Late Pleistocene ice-sheets. We present an inversion analysis of the GPS derived deformation in North America to determine the effective lithosphere thickness and mantle viscosity, and examine whether the GPS observations can be fit with the ice-sheets and earth models, which were constructed and inferred mainly from geomorphologic/geological and relative sea level (RSL) data. The inversion computation is conducted for horizontal and vertical deformation, separately and jointly with two ice-sheet models (ANU-ICE and ICE-5G) developed independently by the Australian National University (ANU) and University of Toronto. The results from a simple three-layer earth model give a lithosphere thickness of 100~130km, an upper-mantle viscosity of 7~10 × 1020 Pa s, and a lower-mantle viscosity of 1.5~2.8 × 1021 Pa s. More sophisticated models such as introducing a transition zone of 400-670km failed to improve model fit, and the related parameters are mostly consistent with those of three-layer models. Further tests show that models of a thin-layer (30~40km) of large viscosity (~1022 Pa s) did not provide a better fit to the data. Ice scaling tests show that vertical deformation is more sensitive to local ice configuration. An increase of ice thickness by ~40% in Alberta and a reduction by ~50% between Saskatchewan and West Ontario are required to fit both horizontal and vertical deformation observed in Southwest Canada, whereas a reduction of ice thickness by ~25% for ANU-ICE produced an improved fit to both horizontal and vertical deformation in Quebec. Results from inversion analysis of two sub-datasets in Southwest and Southeast Canada revealed a 40% difference in the lower-mantle viscosity, which indicates that the lower-mantle in Southeast Canada could be relatively stronger. There is a discrepancy in the upper-mantle viscosity estimate between horizontal and vertical deformation: a low value (3~5 × 1020 Pa s) required by vertical deformation, and a high value (~9 × 1020 Pa s) favoured by horizontal deformation, which is due possibly to under-represented vertical deformation in the region as well as uncertainties in local ice topography. Overall, the earth model estimated from inversion analysis of GPS data in North America is consistent with the early inference from forward analyses of RSL data (e.g. Tushingham & Peltier, 1992): the lower-mantle viscosity is a factor of 1.5~2.0 larger than upper-mantle viscosity of ~1021 Pa s, reflecting that the main features of the earlier constructed North American ice-sheets (e.g. ICE-3G) are unchanged after two decade refinements.

The 2011 digital elevation model (DEM) grid covers the whole of the Christmas Island. It was provided by AAM in 1km by 1km ESRI grid tiles which were then joined together using ESRI ArcMap. Each grid cell (1m by 1m) contains the height in metres of the ground surface derived from the 2011 LiDAR aerial survey data.