To calibrate airborne gravity gradiometers currently in development in China, it is urgent to build an airborne gravity gradiometer test site. The site’s selection depends on the preknowledge of high-resolution gravity and gradient structures. The residual terrain modelling (RTM) technique is generally applied to recover the short-scale gravity field signals. However, due to limitations in the quality and resolution of density models, RTM terrain generally assumes a constant density. This assumption can introduce significant errors in areas with substantial density anomalies and of reggued terrain, such as volcano areas. In this study, we promote a method to determine a high-resolution gravity field by integrating long-wavelength signals generated by EGM2008 with short-wavelength signals from terrain relief and shallow density anomalies. These short wavelength signals are recovered using the RTM technique with both constant density and density anomalies obtained through the equivalent source layer (ESL) method, utilizing sparse terrestrial gravity measurements. Compared to the recovery rate of $54.62\%$ using the classical RTM method, the recovery rate increases to $86.22\%$ after involving density anomalies. With this method, we investigate the gravity field signals over the Wudalianchi Volcano Field (WVF) both on the Earth’s surface and at a flight height of 100 m above the terrain. The contribution of each part and their attenuation characters are studied. In particular, the 5 km × 5 km area surrounding Bijiashan (BJS) and Wohushan (WHS) volcanos shows a strong gravity signature, making it a good candidate for the test site location. This study gives the location of the airborne gravity gradiometer test site which is an essential step in the instruments’ development. Furthermore, the method presented in this study offers a foundational framework for future data processing within the test site.

The gravity and gradient anomalies contain valuable information about the underground geological structures at various depths. Deep and shallow buried source bodies are able to be identified through multi-scale field separation processes, and visual comprehensions of geological structures can be obtained via 3D density inversion techniques. In this study, we propose an improved 3D imaging strategy based on gravitational field separation using the preferential continuation filter. This strategy incorporates the relationship between spectral features and buried depths of source bodies, allowing for a one-step transformation from planar gravity and full-tensor gradient field observations to a 3D density structure in the wave-number domain. Synthetic tests validate the effectiveness and robustness of the gravity and gradient imaging approaches, highlighting their advantages in high vertical resolution and low computational requirements. Nonetheless, it should be noted that the imaging effects of horizontal gradients ${\Gamma }_{xx}$ and ${\Gamma }_{yy}$ are unsatisfactory due to their weak noise resistance. Thus, they are not suitable for real data applications. The other imaging approaches are further applied to recover the subsurface 3D density structure beneath the Weishan cone in Wudalianchi Volcanic Field, Northeastern China. Our results provide insights into the possible location and shape of the low-density magma chamber. Also, the potential presence of partial melts is inferred and supported from a gravity perspective. The primary advantage of these approaches is their ability to generate a reasonable geological model in scenarios with limited prior information and physical property constraints. As a result, they have significant practical value in the field of applied geophysics, including mineral exploration and volcanology studies.

SUMMARY: Moho determination is an important issue in studying the Earth’s interior structure. In accordance with the isostasy-compensation hypothesis in geodesy, it is possible to recover regional or global Moho by employing gravimetric data. The nonlinear property is one of the main difficulties in solving the inverse problem of isostasy. To effectively address this issue, we propose an improved iterative inversion method that combines 3-D integration and linear regularization to achieve an approximate nonlinear solution. To estimate the contributions of different components in the gravity-gradient tensor from the Gravity field and steady-state Ocean Circulation Explorer (GOCE), other than the vertical component, we additionally develop two joint inversion scenarios that utilize diagonal horizontal components and all five non-vertical components. The validating experiments are implemented in Qinghai–Tibet Plateau and its near zone. Simulations and applications illustrate that horizontal responses of Moho undulation are also significant. Yet the off-diagonal components provide minimal contributions, adding only 0.25 km of bias to the joint inversion results. Truncation effects serve as the primary source of systematic errors, resulting in ∼1 km error in vertical inversion results and ∼2.3 km error in joint inversion results. Then, the gravimetric Moho results are compared with CRUST1.0, and they show a generally strong correlation. Differences are obvious at the northern and eastern margins of the plateau. It is maybe due to the local changes in crust–mantle density contrasts. Upwelling of asthenospheric materials and fluid flow in the middle-lower crust are the two main factors. Based on high-precision satellite gravimetry, our study could provide new insights into the tectonic structure of Qinghai–Tibet Plateau.

SUMMARY: Gravity curvature is defined as the third-order derivatives of the gravitational potential. It has been proposed as a potential observable for future satellite gradiometry due to its enhanced sensitivity to short-wavelength components of Earth’s gravity field. Previous studies reported that gravity curvature exhibits apparently weaker spatial correlation with Moho geometry than gravity and gravity–gradient observations, raising concerns about its applicability for Moho inversion. In this study, we systematically assess the capability of gravity–curvature data for Moho recovery, with particular emphasis on the contrasting behaviours of spatial- and spectral-domain inversion schemes. The nonlinear spatial inversion is implemented using the iterative regularization, whereas the spectral inversion follows a spherical harmonic Parker-Oldenburg formulation. Synthetic and real-data tests reveal a clear methodological dependence. Spectral inversion demonstrates robust and stable performance, as it primarily exploits the inherent spectral content of the gravitational field and is insensitive to altered spatial patterns. In contrast, spatial inversion is strongly influenced by data-model correlation, with performance improving at higher observation altitudes but degrading under near-surface scenario. At satellite altitudes, with the effect of iterative stabilization, the spatial inversion yields roughly consistent performance to the spectral inversion. These findings highlight that the inversion capability of gravity curvature depends critically on the inversion framework. When spatial distribution and spectral content are properly considered, gravity curvature can provide a promising constraint for density interface inversion by enhancing sensitivity to specific spatial scales.