A comprehensive optimization strategy for real-time spatial feature sharing and visual analytics in cyberinfrastructure

For geospatial cyberinfrastructure-enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: (1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency; (2) a progressive attribute transmission method to reduce data size and, therefore, the service response time; (3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to facilitate real-time spatial feature sharing, visual analytics and decision-making.