The thesis documents various implementations of the spherical self-organizing feature map spanning from range imagery to multi-dimensional satellite imagery. Other implementations include archaeological data and face modeling. The techniques are adapted versions of the fundamental learning strategy of the self-organizing map, introduced by Dr. Teuvo Kohonen, and implemented within a spherical topology. Continuity in learning is imposed by the predefined spherical lattice which also transforms the data into a 3D tessellated form. Since the tessellated forms originate from a sphere they simplify the computation of transformation parameters, object re-orientation etc. commonly used in three-dimensional graphics.