Animated chorem-based summaries of geographic data streams from sensors in real time. (August 2017)

• Record Type: Journal Article
• Authors: Bouattou, Zina; Laurini, Robert; Belbachir, Hafida
• Is Part Of: Journal of visual languages & computing. Volume 41(2017)
• Page Start: 54
• Page End: 69
• Publication Date: 2017-08
• Subjects: Geovisualization -- Real-time -- Geographic data streams -- Sensors -- Animated chorems -- Spatial analytics; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2017.03.002
• Languages: English
• ISSNs: 1045-926X

Abstract

Highlights: On-the-fly generation of visual summaries from geo-data coming from the sensors. New approach about the use of chorems for automated data processing applications. We define chorem as a semantic and a geometric generalization of a territory. Our interest was not to represent the entire information, but the most relevant aspects. We address cartographic generalization and spatial conflict resolution problems. Abstract: This paper describes a new visualization approach for the automatic generation of visual summaries dealing with cartographic visualization methods and modeling of real time data coming from sensors. Indeed the concept of chorems seems an interesting candidate to visualize real time geographic database summaries. Chorems have been defined by Roger Brunet as schematized visual representations of territories. However, the time information is not yet handled in existing chorematic map approaches, that is the issue been discussed in this paper in which geodata are coming regularly from sensors distributed along some territory. Our approach is based on spatial analysis by interpolating the values recorded at the same time, so we have a number of distributed observations on areas of study. To get a better visual overview of the entire sensor geodata at a given time, we use spatial statistics formulas on the fly, and so it is possible to extract important spatiotemporal patterns and detect trends over time as geographic rules. Then, those spatiotemporal patterns are visualized as animated chorems. An example is taken from meteorology.