Localised Gross-error Detection in the Australian Land Gravity Database - Sproule, David; Featherstone, Will; Kirby, Jonathan (RESoultions Resource & Energy Services Pty Ltd, 2006)
We have used two complementary, data-driven gross-error detection methods to clean the 2004 release of Geoscience Australia?s (GA?s) land gravity database. The first uses the DEM-9S (version 2) Australian digital elevation model to help verify the gravity observation elevations stored in the database. The second method uses locally interpolated complete/refined Bouguer gravity anomalies, under the assumption that these are smooth and suitable for interpolation, to crosscheck each gravity observation against those surrounding. Together, these methods only identified a total of 237 points (0.021%) in the database that were suspected to be in gross error (differences greater than 250 m and 35 mgal, respectively), of which only nine were identified by both methods. These points will be removed before the computation of the new Australian geoid model, and also supplied to GA for its evaluation. Due to the small number of points identified, this is a very positive result in that it shows that the Australian gravity database appears relatively gross-error-free, which bodes well for all previous studies that have relied upon it. However, it is important to point out that this evaluation is inevitably localised and thus only verifies the high-frequency gravity anomaly signal content. Subsequent studies using dedicated satellite gravimetry will be used to identify long-wavelength errors.