This study investigates the quality (in terms of elevation accuracy and systematic errors) of three recent publicly available elevation model data sets over Australia: the 9 arc second national GEODATA DEM-9S ver3 from Geoscience Australia and the Australian National University (ANU), the 3 arc second SRTM ver4.1 from CGIAR-CSI, and the 1 arc second ASTER-GDEM ver1 from NASA/METI. The main features of these data sets are reported from a geodetic point of view. Comparison at about 1 billion locations identifies artefacts (e.g., residual cloud patterns and stripe effects) in ASTER. For DEM-9S, the comparisons against the space-collected SRTM and ASTER models demonstrate that signal omission (due to the ~270 m spacing) may cause errors of the order of 100-200 m in some rugged areas of Australia. Based on a set of geodetic ground control points (GCPs) over Western Australia, the vertical accuracy of DEM-9S is ~9 m, SRTM ~6 m and ASTER ~15 m. However, these values vary as a function of the terrain type and shape. Thus, CGIAR-CSI SRTM ver4.1 may represent a viable alternative to DEM-9S for some applications. While ASTER GDEM has an unprecedented horizontal resolution of ~30m, systematic errors present in this research-grade version of the ASTER GDEM ver1 will impede its immediate use for some applications.

Abstract. AUSGeoid09 is the new Australia-wide gravimetric quasigeoid model that has been a posteriori fitted to the Australian Height Datum (AHD) so as to provide a product that is practically useful for the more direct determination of AHD heights from Global Navigation Satellite Systems (GNSS). This approach is necessary because the AHD is predominantly a third-order vertical datum that contains a ~1 m north-south tilt and ~0.5 m regional distortions with respect to the quasigeoid, meaning that GNSS-gravimetricquasigeoid and AHD heights are inconsistent. Since the AHD remains the official vertical datum in Australia, it is necessary to provide GNSS users with effective means of recovering AHD heights. The gravimetric component of the quasigeoid model was computed using a hybrid of the remove-compute-restore technique with a degree-40 deterministically modified kernel over a one-degree spherical cap, which is superior to the remove-compute-restore technique alone in Australia (with or without a cap). This is because the modified kernel and cap combine to filter long-wavelength errors from the terrestrial gravity anomalies. The zero-tide EGM2008 global gravitational model to degree and order 2190 was used as the reference field. Other input data are: ~1.4 million land gravity anomalies from Geoscience Australia, 1'x1' DNSC2008GRA altimeter-derived gravity anomalies offshore, the 9"x9" GEODATA-DEM9S Australian digital elevation model, and a readjustment of Australian National Levelling Network (ANLN) constrained to the CARS2006 dynamic ocean topography model. In order to determine the numerical integration parameters for the modified kernel, the gravimetric component of AUSGeoid09 was compared with 911 GNSS-observed ellipsoidal heights at benchmarks. The standard deviation of fit to the GNSS-AHD heights is ±222 mm, which dropped to ±134 mm for the readjusted GNSS-ANLN heights, showing that careful consideration now needs to be given to the quality of the levelling data used to assess gravimetric quasigeoid models. The publicly released version of AUSGeoid09 also includes a geometric component that models the difference between the gravimetric quasigeoid and the zero surface of the AHD at 6,794 benchmarks. This a posteriori fitting used least-squares collocation (LSC) in cross-validation mode to determine a correlation length of 75 km for the analytical covariance function, whereas the noise was taken from the estimated standard deviation of the GNSS ellipsoidal heights. After this LSC surface-fitting, the standard deviation of fit reduced to ±30 mm, one third of which is attributable to the uncertainty in the GNSS ellipsoidal heights.

We describe the computation of the first Australian quasigeoid model to include error estimates as a function of location that have been propagated from uncertainties in the EGM2008 global model, land and altimeterderived gravity anomalies and terrain corrections. The model has been extended to include Australia's offshore territories and maritime boundaries using newer datasets comprising an additional ∼280,000 land gravity observations, a newer altimeter-derived marine gravity anomaly grid, and terrain corrections at 1 × 1 resolution. The error propagation uses a remove-restore approach, where the EGM2008 quasigeoid and gravity anomaly error grids are augmented by errors propagated through a modified Stokes integral from the errors in the altimeter gravity anomalies, land gravity observations and terrain corrections. The gravimetric quasigeoid errors (one sigma) are 50-60 mm across most of the Australian landmass, increasing to ∼100 mm in regions of steep horizontal gravity gradients or the mountains, and are commensurate with external estimates.

[1] Using geodetic and oceanographic data, we show that the apparent north-south slope between the Australian Height Datum (AHD) and the geoid is caused almost completely by the ocean's time-mean dynamic topography (MDT). This is because the AHD was constrained to zero height at local mean sea level at multiple tide gauges around the Australian continent. Using MDT models and corrected leveling data, almost all of the apparent north-south slope can be removed from the AHD. An auxiliary observation is that a satellite-only MDT model based on only around one year of GOCE data generates results commensurate with geodetic, oceanographic and combined MDT models.Citation: Featherstone, W. E., and M. S. Filmer (2012), The north-south tilt in the Australian Height Datum is explained by the ocean's mean dynamic topography,

A combination of independent evidence (continuous GPS, repeat geodetic leveling, groundwater abstraction, satellite altimetry, and tide gauge (TG) records) shows that the long‐recording Fremantle TG has been subsiding in a nonlinear way since the mid‐1970s due to time‐variable groundwater abstraction. The vertical land motion (VLM) rates vary from approximately −2 to −4 mm/yr (i.e., subsidence), thus producing a small apparent acceleration in mean sea level computed from the Fremantle TG records. We exemplify that GPS‐derived VLM must be geodetically connected to the TG to eliminate the commonly used assumption that there is no differential VLM when the GPS is not colocated with the TG. In the Perth Basin, we show that groundwater abstraction can be used as a diagnostic tool for identifying nonlinear VLM that is not evident in GPS time series alone.

This paper investigates the normal-orthometric correction used in the definition of the Australian Height Datum (AHD), and also computes and evaluates normal and Helmert orthometric corrections for the Australian National Levelling Network (ANLN). Testing these corrections in Australia is important to establish which height system is most appropriate for any new Australian vertical datum. An approximate approach to assigning gravity values to ANLN benchmarks (BMs) is used, where the EGM2008-modelled gravity field is used to 're-construct' observed gravity at the BMs. Network loop closures (for first-and second-order levelling) indicate reduced misclosures for all height corrections considered here, particularly in the mountainous regions of south eastern Australia. Differences between Helmert orthometric and normal-orthometric heights reach 44 cm in the Australian Alps, and differences between Helmert orthometric and normal heights are about 26 cm in the same region. Normal-orthometric heights differ from normal heights by up to 18 cm in mountainous regions > 2000 m. This indicates that the quasigeoid is not compatible with normalorthometric heights.

10The Australian Height Datum (AHD) forms the vertical geodetic datum for Australia 11 and is thus the framework for all heights, including those used to establish digital 12 elevation models (DEMs). The AHD was established over quite a short timeframe, 13 due to the urgent requirement for height control for topographic mapping and 14 gravity surveys.This necessitated the use of lower quality spirit-levelling 15 observations over long distances and approximate data reductions. Geoscience 16Australia has kindly supplied us with height differences for all sections of the basic 17 and supplementary spirit-levelling used to establish the AHD, allowing us to analyse 18 loop closures to detect spirit-levelling (or data entry / transcription) errors in this 19 dataset. In the case-studies presented here, we show that GPS and a precise 20 gravimetric quasigeoid model can be used to identify the sections in a levelling loop 21 that cause misclosure, reflecting the relative quality of modern quasigeoid models 22 over the spirit-levelling originally used to establish the AHD. We also consider and 23 discuss some of the other issues that would have to be considered if Australia is to 24 implement a new vertical geodetic datum from these data to support, for example, 25improved DEMs in the future. 26 27 KEY WORDS: Heights, AHD, spirit-levelling, geoid, GPS, DEMs 28 29 1 DISCLAIMER: Please note that the Intergovernmental Committee on Surveying and Mapping has decreed that the AHD will be retained for the foreseeable future, so our experiments are only to ascertain what can be achieved, rather than foreshadowing any revision to the AHD in the near future.

Past ground-based geodetic measurements in the Perth Basin, Australia, record small-magnitude subsidence (up to 7 mm/y), but are limited to discrete points or traverses across parts of the metropolitan area. Here, we investigate deformation over a much larger region by performing the first application of Sentinel-1A InSAR data to Australia. The duration of the study is short (0.7 y), as dictated by the availability of Sentinel-1A data. Despite this limited observation period, verification of Sentinel-1A with continuous GPS and independent TerraSAR-X provides new insights into the deformation field of the Perth Basin. The displacements recorded by each satellite are in agreement, identifying broad (>5 km wide) areas of subsidence at rates up to 15 mm/y. Subsidence at rates greater than 20 mm/y over smaller regions (∼2 km wide) is coincident with wetland areas, where displacements are temporally correlated with changes in groundwater levels in the unconfined aquifer. Longer InSAR time series are required to determine whether these measured displacements are representative of long-term deformation or (more likely) seasonal variations. However, the agreement between datasets demonstrates the ability of Sentinel-1A to detect small-magnitude deformation over different spatial scales (from 2 km-10 s of km) in the Perth Basin. We suggest that, even over short time periods, these data are useful as a reconnaissance tool to identify regions for subsequent targeted studies, particularly given the large swath size of radar acquisitions, which facilitates analysis of a broader portion of the deformation field than ground-based methods or single scenes of TerraSAR-X.