This paper presents a parallel version of the Interval Categorizer Tessellation-based Model (ICTM) for the si- multaneous categorization of geographic regions consider- ing several characteristics (e.g., relief, vegetation, land use etc.) in clusters, called HPC-ICTM. Interval techniques are used for the modeling of uncertain data and the con- trol of discretization errors. We analyze the performance of the HPC-ICTM and present results concerning its ap- plication to the relief/land-use categorization of the region surrounding the lagoon Lagoa Pequena (RS, Brazil), which is extremely important from an ecological point of view.