Towards GPU-Accelerated Web-GIS for Query-Driven Visual Exploration
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Web-GIS has played an important role in supporting accesses, visualization and analysis of geospatial data over the Web for the past two decades. However, most of existing WebGIS software stacks are not able to exploit increasingly available parallel computing power and provide the desired high performance to support more complex applications on large-scale geospatial data. Built on top our past works on developing high-performance spatial query processing techniques on Graphics Processing Units (GPUs), we propose a novel yet practical framework on developing a GPU-accelerated Web-GIS environment to support Query-Driven Visual Explorations (QDVE) on Big Spatial Data. An application case on visually exploring global biodiversity data is presented to demonstrate the feasibility and the efficiency of the proposed framework and related techniques on both the frontend and backend of the prototype system.