A feature selection approach towards progressive vector transmission over the Internet. (September 2017)

• Record Type: Journal Article
• Authors: Miao, Ru; Song, Jia; Feng, Min
• Is Part Of: Computers & geosciences. Volume 106(2017)
• Page Start: 150
• Page End: 163
• Publication Date: 2017-09
• Subjects: Progressive transmission -- Feature selection -- Amount of information -- Real-time transport protocol; Environmental policy -- Periodicals; 550.5
• DOI: 10.1016/j.cageo.2017.06.005
• Languages: English
• ISSNs: 0098-3004

Abstract

Abstract: WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet. Highlights: A novel feature selection approach based on the information theory is proposed. The amount of information is used to measure the importance of a feature. Spatial distribution, attribute, geometric size and complexity are considered. Real-time Protocol is employed for progressive selection and transmission.