Magnetic surveys are becoming increasingly common on archaeological sites due to the amount of data that can be collected rapidly in a non-invasive manner. Owing to their relatively low cost compared with excavation they commonly provide the only dataset that covers an entire archaeological site, which can then be used to target other surveys and excavations to areas of interest. Typically interpretation is done visually using optimized images of the raw data, which when dealing with large datasets can be time-consuming and subjective. Various derivative based methods have been developed recently to aid the interpretation of magnetic data. A particular use for these techniques is to locate the edges of subsurface magnetic bodies, and their use is gaining popularity in aeromagnetic regional and mineral exploration surveys. Despite this they are rarely used in archaeological survey interpretation. This probably is due to the particular challenges posed as a result of the low amplitude and high-wavenumber content of archaeomagnetic surveys, where features of interest are often only slightly above the noise level. Here, it is demonstrated that when derivative-based methods are applied directly to total-field data, the high-wavenumber components of the data are amplified, making datasets difficult to interpret and often proving less useful than the total-field dataset alone. The pseudogravity transformation is a readily available tool for suppressing this bias to the high-wavenumber features and providing derivative-based results with a power spectrum comparable to the original total-field response, but with all the qualities to enhance interpretation that are obtained from using the derivative methods.

Magnetic depth estimation methods are routinely used to map the depth of sedimentary basins by assuming that the sediments are nonmagnetic and underlain by magnetic basement rocks. Most of these methods generate basement depth estimates at discrete points. Converting these depth estimates into a grid or map form often requires the application of qualitative methods. The reason for this is twofold: first, in deeper parts of basins, there is generally a scarcity of depth estimates and those that have been determined tend to be biased toward the shallower basement structures close to the basin edge; and second, depth estimates intrinsically relate to magnetic anomalies that emanate from the top edges of basement faults/contacts resulting in a shallow depth bias. Thus, simple grid interpolation of these depth estimates often forms a shallower and structurally unrepresentative map when evaluated in detail. To overcome these problems of qualitative and/or simple grid interpolation of these point-depth estimates into a regular grid, we use the pseudogravity field transform response of the magnetic field to constrain this interpolation using inversion methods together with the relationship between the point-depth estimates and their pseudogravity values. The pseudogravity transformation converts a grid of magnetic data such that the resulting grid has the same simple relationship to magnetic susceptibility that a gravity grid has to density. The pseudogravity map is thus straightforward to visualize in terms of basement structure, but it only maps the magnetic properties of the subsurface and is not related to the gravity anomaly or the density. We describe a practical approach to invert pseudogravity grids using gravity inversion software to produce a 3D basin model assuming a constant susceptibility basement. The approach is initially tested on the Bishop 3D model and then applied to an example from the northern North Sea. This approach can be considered complementary to 3D gravity inversion and has the advantage that the pseudogravity response is not affected by structure within the sediments or effects such as sediment compaction, inversion, or isostatic compensation, all of which often complicate the gravity response of sedimentary basins.

This paper reviews the impacts of new satellite altimeter data sets and new technology on the production of satellite gravity. It considers the contribution of the increased data volume, the application of new altimeter acquisition technology and the potential for future developments. Satellite altimeter derived gravity has provided gravity maps of the world's seas since the 1980s, but, from 1995 to 2010, virtually all improvements were in the processing as there were no new satellite data with closely spaced tracks. In recent years, new data from CryoSat‐2 (launched in 2010) and the geodetic mission of Jason‐1 (2012–2013) have provided a wealth of additional coverage and new technology allows further improvements. The synthetic aperture radar mode of CryoSat‐2 uses a scanning approach to limit the size of the altimeter sea surface footprint in the along‐track direction. Tests indicate that this allows reliable data to be acquired closer to coastlines. The synthetic aperture radar interferometric mode of CryoSat‐2 uses two altimeters to locate sea‐surface reflection points laterally away from the satellite track. In a study to generate gravity for freshwater lakes, this mode is found to be valuable in extending the available satellite coverage. The AltiKa altimeter uses higher frequency radar to provide less noisy sea‐surface signals and its new orbit mode gives potential for further improvements in satellite gravity. Future developments include the potential for swath mapping to provide further gravity improvements.

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