An Integrated Visual Analytics Framework for Spatiotemporal Data

Abstract

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.