Interactive Real-Time Visualization for Large-Scale Spatial Datasets Based on OptIputer

2010 ◽  
Author(s):  
Rui-peng Tong ◽  
Di Zhao
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Spatial Datasets ◽  
Real Time Visualization

scholarly journals Research on Real-Time Visualization of Large-scale 3D Terrain

2012 ◽  
Vol 29 ◽  
pp. 1702-1706 ◽  
Author(s):  
Hou Han-dan ◽  
Zhang Jian-fei
Keyword(s):  
Real Time ◽  
Large Scale ◽  
3D Terrain ◽  
Real Time Visualization

Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles

2020 ◽  
Author(s):  
Mingyue Lu ◽  
Xinhao Wang ◽  
Xintao Liu ◽  
Min Chen ◽  
Shuoben Bi ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Weather Radar ◽  
Radar Data ◽  
Web Based ◽  
Real Time Visualization

scholarly journals HiIndex: An Efficient Spatial Index for Rapid Visualization of Large-Scale Geographic Vector Data

2021 ◽  
Vol 10 (10) ◽  
pp. 647
Author(s):  
Zebang Liu ◽  
Luo Chen ◽  
Anran Yang ◽  
Mengyu Ma ◽  
Jingzhi Cao
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Information Science ◽  
Treatment Time ◽  
Spatial Index ◽  
Vector Data ◽  
Recursion Method ◽  
Tree Generation ◽  
Real Time Visualization ◽  
Pre Treatment

In the big data era, rapid visualization of large-scale vector data has become a serious challenge in Geographic Information Science (GIS). To fill the gap, we propose HiIndex, a spatial index that enables real-time and interactive visualization of large-scale vector data. HiIndex improves the state of the art with its low memory requirements, fast construction speed, and high visualization efficiency. In HiIndex, we present a tile-quadtree structure (TQ-tree) which divides the global geographic range based on the quadtree recursion method, and each node in the TQ-tree represents a specific and regular spatial range. In this paper, we propose a quick TQ-tree generation algorithm and an efficient visualization algorithm. Experiments show that the HiIndex is simple in structure, fast in construction, and less in memory occupation, and our approach can support interactive and real-time visualization of billion scale vector data with negligible pre-treatment time.

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