Abstract: The map tiles technology are widely used in WebGIS solutions of the current mainstream GIS  software and the Internet map applications, tile processing service is the key technology to realize the fast and seamless browsing on WebGIS. Traditional algorithms and commercial GIS software cannot meet the demand of fast processing large data size raster image tiling. In view of these shortcomings and problems, this paper summarizes the current parallel tiling technology and then puts forward a new parallel raster image tile method which named “ParaTile”. ParaTile adopts the shared disk parallel technology, using multi-process to divide the source raster image. Each process of ParaTile is read and written independently to the area that it is owned based on MPIparallel IO function. Finally, each process saves the output tile results independently according to the TMS（Tile Map Service） or the standard made by Google Tile. Experiments are tested by different level size of the remote sensing image, the results show that no matter in speed or stability ParaTile algorithm has a great improvement in the same parallel level compared to ArcGIS software, especially the larger size of data the more advantages are.

Key words: raster image, parallel tile, Message Passing Interface（MPI）

摘要： 当前主流GIS软件以及互联网地图应用在WebGIS（网络地理信息系统）解决方案中都广泛采用地图切片（又称瓦片），切片处理服务是实现影像在WebGIS上快速无缝浏览的关键技术。针对目前传统算法以及商业GIS软件在大数据量栅格影像快速瓦片化方面的不足，提出一种名为ParaTile的高效栅格影像快速瓦片化方法，ParaTile基于MPI共享外存的并行技术，利用多进程对原始栅格影像进行数据划分，每个进程对其所划分的区域进行独立读写和计算，而后再按照TMS或者Google Tile定义的标准将瓦片进行编码输出。实验采用不同级别大小的遥感影像进行测试，结果表明ParaTile在面对不同规模的数据时，无论从速度还是算法稳定性上都较现有算法和工具具有显著优势，特别是当数据量越大时，这种优势愈加明显。

关键词: 栅格影像, 并行瓦片化, 消息传递接口（MPI）