Patterns of tree distribution are an important part of forest structure and directly affect the health and stability of forest ecosystems. Maintaining and preserving forest structural diversity has often been considered the best way to protect biodiversity. One method measuring the diversity of tree distribution patterns was discussed in this paper in order to provide a theoretical basis for the expression of forest structure diversity. The key to the study of distribution pattern diversity is to select the appropriate biodiversity measuring method and index which has a distributed attribute. In this paper, we put forward a method to express tree distribution pattern diversity which counted the distributions frequency of uniform angle index and Voronoi polygon side, and calculate uniform angle index diversity and Voronoi polygon side distribution diversity by the Simpson index, respectively. The distribution pattern diversity of three long-term monitoring *Pinus koreansis* broad-leaved forest plots (area = 100 m × 100 m) in northeastern China was analyzed by this method. The results showed that both of the distribution of uniform angle index and the Voronoi polygon side were close to the normal distribution. The frequency of randomly distributed trees was the maximum and more than 55% in the uniform angle index distribution; the type of Voronoi polygon side was great than 10 and over 50% of the trees had 5-6 closest neighboring trees. The result of using the Simpson index to analyze tree distribution pattern diversity showed that the tree distribution pattern diversity was higher in the cluster distribution stand than the random distribution stand. We also found that Simpson index values were different when different distribution pattern diversity methods were used, and the uniform angle distribution diversity was significantly lower than that of the Voronoi polygon side distribution diversity, which mainly due to the different quantity grade of each index. Therefore, study on the diversity of forest distribution pattern should choose distribution pattern indices with distribution attribute. The uniform angle index distribution and Voronoi polygon side distribution used in this paper had this attribute, however, different indices reflected different aspects of distribution pattern, so the same pattern analysis method should be used in the analysis and comparison of distribution pattern diversity of different forest stands.