Towards GPU-Accelerated Web-GIS for Query-Driven Visual Exploration

  • Jianting Zhang
  • Simin You
  • Le Gruenwald
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10181)


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.


Web-GIS GPU QDVE Spatial join Biodiversity 


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer Science, City CollegeCity University of New YorkNew YorkUSA
  2. 2.Department of Computer Science, Graduate CenterCity University of New YorkNew YorkUSA
  3. 3.Department of Computer ScienceThe University of OklahomaNormanUSA

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