This research proposes a novel hierarchical 3D Gaussian representation method for real-time rendering of very large datasets. By utilizing 3D Gaussian splatting technology, it offers excellent visual quality, rapid training, and real-time rendering capabilities. Through a hierarchical structure and effective Level-of-Detail (LOD) solutions, it can efficiently render distant content and achieve smooth transitions between levels. The technology adapts to available resources, trains large scenes using a divide-and-conquer approach, and integrates them into a hierarchical structure that can be further optimized to enhance the visual quality of Gaussian merging into intermediate nodes.