AUSGeoid09 is an order of magnitude more accurate than AUSGeoid98 at converting ellipsoidal heights to Australian Height Datum (AHD) heights and vice versa. Results of this study show AUSGeoid09 can be used to compute AHD values from Global Navigation Satellite System (GNSS) ellipsoidal heights with an uncertainty of less than 0.03 m (1 sigma). The improvement is largely due to the inclusion of a geometric component in AUSGeoid09 that accounts for the spatially varying offset between a gravimetric quasigeoid model and the AHD. This geometric component was calculated using least squares collocation in cross validation mode and then 'draped' over the gravimetric quasigeoid. Although previous AUSGeoid models were used to convert GNSS ellipsoidal heights to the AHD and vice versa, none until now have accounted for the gravimetric quasigeoid to AHD offsets. This is a consequence of how the AHD was realised and has commonly resulted in misfits of ~0.5 m or more. When used with GNSS technology, AUSGeoid09 can replace the need for traditional third-order levelling in many situations. Relative tests of AUSGeoid09 over a continent-wide set of over 20 million baselines showed that it can deliver better than Australian class LC levelling tolerances (12 ) in 99% of cases. The model accepts a user's GDA94 latitude, longitude and ellipsoidal height and returns an AHD height and deflections of the vertical. AUSGeoid09 is now available free-of-charge on the Geoscience Australia website (http://www.ga.gov.au/geodesy/ausgeoid/nvalcomp.jsp).

In ecology, a common form of statistical analysis relates a biological variable to variables that delineate the physical environment, typically by fitting a regression model or one of its extensions. Unfortunately, the biological data and the physical data are frequently obtained from separate data sources. In such cases there is no guarantee that the biological and physical data are co-located and the regression model cannot be used. A common and pragmatic solution is to spatially predict the physical variables at the locations of the biological variables and then use the predictions as if they were observations. In this article, we show that this procedure can cause potentially misleading ferences when fitting a generalised linear model as an example. We propose a Berkson-error model which overcomes the limitations. The differences between using predicted covariates and the Berkson error model are illustrated using data from the marine environment, and a simulation study based on this data.

This job was part of the Coastal capture program. It captures from the coast to the 10m contour interval.

Aquisition by Photomapping Services with project management and ground control by Coordinated Solutions. Acquisition Start Date: January 20th 2011 Acquisition End Date: January 28th 2011 Device Name: Optech `ALTM Gemini Flying Height (AGL): 1400m IMU used: Litton LN200 Number of Runs: 50 + 2 cross strips Swath width: 1040m Flight direction: N - S Side Overlap: 40% (Hobart and surrounds) - 100% (Mt Wellington) Scan angle: +/- 20 degrees Horizontal datum : GDA94 Vertical datum: AHD Map projection: MGA 55 Description of aerotriangulation process used and residual results: LiDAR data captured using onboard GPS, IMU and ground basestation. Description of rectification process used: Trajectories and laser data corrected initially using AusGeoid98 and then adjusted to AHD using local PSMs. Spatial accuracy: 0.15m (vertical) and 0.30m (horizontal) at 1sigma Surface types: LAS classified 1m DEM Ground and Non-Ground points Average point separation: 1m Laser return types: 1st through to 4th Data thinning: No Laser footprint size: 0.42m

These datasets cover approximately 60 sq km along the middle and southern sectors of the Hopevale Shire Council and are part of the 2009 North Queensland LiDAR capture project. This project, undertaken by Photomapping Services 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 - 0.25 metre contours in ESRI Shape

This dataset attempts to reflect the boundaries of claimant applications for Native Title as per the Register of Native Title Claims (s185, Native Title Act; Commonwealth). This is a national dataset but data is stored by jurisdiction (State), for ease of use. Applications stored for each jurisdiction dataset include applications which overlap into adjoining jurisdictions as well as applications which overlap with these. This dataset depicts the spatial record of registered claimant applications. Aspatial attribution includes National Native Title Tribunal number, Federal Court number, application status and the names of both the NNTT Case Manager and Lead Member assigned to the application. Applicants of registered applications have the Right To Negotiate (RTN) with respect to certain types of Future Acts over the area being claimed. Whilst applications that are determined are recorded on a separate register, all registered applications remain on the Register of Native Title Claims until otherwise finalised. Geospatial data portraying native title information produced by the National Native Title Tribunal may not be on-sold. Value added products using this data must acknowledge the National Native Title Tribunal as the data source and include the NNTT disclaimer.

This dataset reflects the external boundaries of all native title determination and compensation applications that are currently recognized and active within the Federal Court process. Applications that are non-active (i.e. withdrawn, dismissed, finalised, rejected or combined) are only included as aspatial records for completeness. This is a national dataset with data partitioned by jurisdiction (State), for ease of use. Applications stored for each jurisdiction dataset include applications which overlap into adjoining jurisdictions as well as applications which overlap with these for completeness. This dataset depicts the spatial definition of active Claimant and Non-claimant native title determination applications and compensation applications. Where possible these may include internal boundaries or areas excluded. Aspatial attribution includes National Native Title Tribunal number, Federal Court number, application status and the names of both the NNTT Case Manager and Lead Member where assigned to the application. Applications included on the Schedule of Native Title (Federal Court) include all registered and unregistered applications as well as determined applications that are yet to be finalized. Geospatial data portraying native title information produced by the National Native Title Tribunal may not be on-sold. Value added products using this data must acknowledge the National Native Title Tribunal as the data source and include the NNTT disclaimer.

This dataset reflects the boundaries of claimant and nonclaimant native title applications that have been determined in part or in full, together with attribution about that determination. This dataset is stored nationally. The National Native Title Register (s192, Native Title Act, Commonwealth), is a register containing information about each determination of native title by the Federal or High Court or by a recognized State or Territory body. Determinations are categorized by both process and outcome. Process will be by consent, litigation or unopposed. Outcome will be that native title will have been found to exist in full or part, or been extinguished. Those determinations subject to appeal are also noted. Geospatial data portraying native title information produced by the National Native Title Tribunal may not be on-sold. Value added products using this data must acknowledge the National Native Title Tribunal as the data source and include the NNTT disclaimer.

Map(s) of Rb (rubidium) concentration (Total content, Aqua Regia soluble content, and/or Mobile Metal Ion soluble content) in Top Outlet Sediment (TOS) and/or Bottom Outlet Sediment (BOS) samples, dry-sieved to <2 mm and/or <75 um grain size fractions. Source: The Geochemical Atlas of Australia (Caritat and Cooper, 2011)

This dataset reflects the boundaries of those Indigenous Land Use Agreements (ILUA) that have entered the notification process or have been registered and placed on the Register of Indigenous Land Use Agreements (s199A, Native Title Act; Commonwealth). This is a national dataset. Aspatial attribution includes National Native Title Tribunal number, Name, Agreement Type, Proponent, Area and Registration Date. Geospatial data portraying native title information produced by the National Native Title Tribunal may not be on-sold. Value added products using this data must acknowledge the National Native Title Tribunal as the data source and include the NNTT disclaimer.