LAUSR

Abstract In this article, the probability tomography imaging method is applied to airborne vertical gravity gradient data to detect anomalies and estimate their depths and locations. First, the subsurface is divided into a 3D regular grid. Then, the probability tomography function is calculated at each grid node, and the obtained grid values are plotted. The zones of the highest values are the most probable areas for the buried bodies. It is noted that the results fall in the range [-1, +1] that represents the mass excess or mass deficit of density relative to the density of the host volume. The approach is applied to a sphere model and a cube model at certain flight altitudes. The results demonstrate that the approximate mass distribution and depth estimation derived from the approach are reliable up to a certain flight altitude.