An Integrated Visual Analytics Framework for Spatiotemporal Data

被引：0
|
作者：
Wang, Shaohua [1 ]
Zhong, Ershun [2 ]
Zhou, Qiang [3 ]
Cui, Xue [3 ]
Lu, Hao [3 ]
Yun, Weiying [3 ]
Hu, Zhongnan [3 ]
Cai, Wenwen [3 ]
Long, Liang [2 ]
机构：
[1] Arizona State Univ, Sch Geog Sci & Urban Planning Res, 975 S Myrtle Ave, Tempe, AZ 85281 USA
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, POB 100101, Beijing, Peoples R China
[3] SuperMap Soware Co Ltd, POB 100015, Beijing, Peoples R China
来源：
PROCEEDINGS OF THE 1ST ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON ADVANCES IN RESILIENT AND INTELLIGENT CITIES (ARIC-2018) | 2018年
关键词：
Spatiotemporal data; Integrated Visual Analytics Framework; Real-time Spatial Data; Dynamic Objects; iClient; SuperMap GIS; PATTERNS; SPACE; TIME;
D O I：
10.1145/3284566.3284574
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Visual analytics(1) for spatiotemporal data is an essential issue in shown the patterns of the spatial data mining results. To deal with challenges caused by dynamic spatiotemporal data require efficient visual analytics that visualizes real-time and dynamic spatial data. We proposed and implemented an integrated visual analytics framework. It integrated open source map library, visual library, and modern web development technology. It made use of Spark Streaming in real-time data processing while real-time mapping results on the DataFlowLayer. Visual analytics framework for dynamic objects is built based on high-performance processing and hardware mixed acceleration strategies. Benchmark experiments showed that it achieved excellent performance for visualizing spatiotemporal data.
引用
收藏
页码：41 / 45
页数：5
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