Abstract: In order to satisfy the requirements of analyzing geographical distribution and relationships of data sets in food safety field, we proposed an associated hierarchical data visualization method named Sun Map, which is based on Sunburst and Heatmap. Firstly, a Heatmap based on geographical information is created to present geographical distribution of the dataset, and a sunburst is created to present the hierarchical structure of the dataset. Secondly, put the Heatmap into the center of sunburst, and use the lines connecting nodes between Heatmap and sunburst to present the relationships between them. Thirdly, execute the route optimization algorithm which introduces transiton points and uses Cubic Bézier curve instead of straight lines to represent the relationships to reduce visual clutter. Finally, a Matrix-Heatmap view, which is composed of an adjacent matrix and two bar charts, is used to represent the detail of the dataset. Multi-view linkage of data selection, Sun Map, Matrix-Heatmap and some other interactions help users analyze the associated hierarchical data. We applied this methods to the pesticide residues detection data and the result of user studies demonstrates that this visual design is effective in helping users to find object information and relationships among complex hierarchical data. The method can also be used in other fields of associated hierarchical data like economic, financial and social networks.