Data collected by hand-held and vehicular-mounted ground penetrating radar (GPR) devices can be viewed as a sequence of A-scans grouped into frames. Sequences of frames create a three-dimensional representation of the collected area. The ground structure within this area includes: the ground layer, sub-surface layers, explosive hazards, and non-explosive (clutter) objects. In previous work, we found a wireframe view of two-dimensional layers within the three-dimensional volume. In this work, we analyze how to use image segmentation techniques to identify and view the entire three-dimensional volume of layers and objects found in the data. First, image value and contour differentiate structure. Then, we employ a multi-stage process of image segmentation, clustering analysis using Competitive Agglomeration, and optimizing a Markov Random Field (MRF). The collection sequence of hand-held system data may not always fit into a grid representation. Therefore, segmentation techniques are modified from a frame by frame grid sequence to a nearest neighborhood of three-dimensional regions. Results are displayed in an interactive viewing tool that displays each stage of the process and represents the scene elements identified.