A gravity anomaly refers to the deviation between observed gravitational acceleration at a specific location and the theoretical gravity predicted by a standardized reference ellipsoid, accounting for elevation and terrain effects. These deviations reveal subsurface density variations caused by geological structures, mineral deposits, voids, or tectonic features beneath Earth's surface.

In GIS workflows, gravity anomaly data is processed and visualized through spatial analysis techniques that transform raw gravimetric measurements into interpolated raster surfaces, contour maps, and three-dimensional subsurface models. Geospatial analysts integrate gravity anomaly datasets with complementary layers — including topographic data, geological maps, and seismic surveys — enabling comprehensive multi-layer analysis within platforms such as ArcGIS and QGIS. Geostatistical interpolation methods like kriging are commonly applied to generate continuous gravity anomaly surfaces from discrete measurement points.

Practical applications include mineral exploration, hydrocarbon prospecting, groundwater resource mapping, geohazard assessment, and infrastructure planning. By leveraging GIS technology, organizations can efficiently identify subsurface anomalies, reduce field investigation costs, and support data-driven decision-making. Accurate gravity anomaly mapping ultimately enhances geoscientific understanding and improves outcomes across environmental, engineering, and resource management disciplines.