Aiming at the difficulty of mainstream methods to support the multilevel real-time visualization of large-scale geographic vector linestring data, a multilevel real-time visualization technique for large-scale geographic vector linestring data was proposed. An adaptive visualization model for multilevel tile rendering was established, and a PQR (pixel-quad-R) tree spatial index and an adaptive visualization algorithm based on PQR-tree were designed to support the data organization and visualization of the model, respectively. Experiments on billion-scale datasets show that the technique can calculate visualization results at any zoom level within 0.57 s. Meanwhile, its visualization time is significantly less than mainstream methods. When the data scale increases sharply, the technology still has good visualization performance at each zoom level, and the lowest visualization rate exceeds 100 tiles/s, which is much better than mainstream methods. The technique can support multilevel real-time visualization of large-scale geographic vector linestring data in the single machine, and has a good application prospect in the field of exploration and analysis of spatial big data.