The spatially constrained inversion (SCI) is a robust methodology for quasi-3D modeling of geoelectrical and EM data of varying spatial density, using a 1D forward solution. It can be implemented with airborne or ground-based data, both in frequency and time domain. The airborne EM data here presented show how the SCI produces laterally smooth results with sharp layer boundaries that respect the 3D geological variations of layered settings. Information migrate horizontally through spatial constraints applied between nearest neighboring soundings, and allow to resolve layers that would be locally poorly resolved. The constraints are built using the Delaunay triangulation, which ensures automatic adaptation to data density variations. Data sets, models and spatial constraints are inverted as one system, producing layered sections with smooth horizontal variations. The SCI suppresses the elongated artifact commonly seen in horizontal maps (i.e., average resistivity, or saltwater boundary elevation maps) resulting from profile oriented data sets. Being an over-determined parameterized inversion problem, it produces a full sensitivity analysis of the output models, an essential tool for the evaluation of the results.