Identification and formalization of knowledge for coloring qualitative geospatial data

Creating a satisfying qualitative color scheme from scratch may be difficult for novice mapmakers and experts. A probability-based method is proposed to identify knowledge regarding qualitative color selection from readily available color schemes and formalize the discovered knowledge to assist in color creation. An unsupervised method to extract the general trends of color selection is presented, and the issue of qualitative color selection is translated into a multi-constraint optimization problem. A feasible solution for achieving the global optimum is then provided. A probability-based method is also proposed to match abstract color values with specific mapping features. This proposed approach is evaluated in a case study. The results of the case study suggest that the proposed method allows users to create qualitative color schemes more efficiently and confidently.