An Efficient Parallel Map Visualization Framework for Large Vector Data

Abstract

With the tremendous development of surveying and mapping technologies, the volume of vector data is becoming larger. For mapping workers and other GIS scientists, map visualization is one of the most common functions of GIS software. But it is also a time-consuming process when processing massive amounts of vector data. Especially in an Internet map service environment, large numbers of concurrent users can cause major processing delays. In order to address this issue, this paper develops an efficient parallel visualization framework for large vector data sets by leveraging the advantages and characteristics of graphics cards, focusing on storage strategy and transfer strategy. The test results demonstrate that this new approach can reduce the computing times for visualizing large vector maps.