- freely available
Visual Analysis for Nowcasting of Multidimensional Lightning Data
AbstractGlobally, most weather-related damages are caused by thunderstorms. Besides floods, strong wind, and hail, one of the major thunderstorm ground effects is lightning. Therefore, lightning investigations, including detection, cluster identification, tracking, and nowcasting are essential. To enable reliable decisions, current and predicted lightning cluster- and track features as well as analysis results have to be represented in the most appropriate way. Our paper introduces a framework which includes identification, tracking, nowcasting, and in particular visualization and statistical analysis of dynamic lightning data in three-dimensional space. The paper is specifically focused on enabling users to conduct the visual analysis of lightning data for the purpose of identification and interpretation of spatial-temporal patterns embedded in lightning data, and their dynamics. A graphic user interface (GUI) is developed, wherein lightning tracks and predicted lightning clusters, including their prediction certainty, can be investigated within a 3D view or within a Space-Time-Cube. In contrast to previous work, our approach provides insight into the dynamics of past and predicted 3D lightning clusters and cluster features over time. We conclude that an interactive visual exploration in combination with a statistical analysis can provide new knowledge within lightning investigations and, thus, support decision-making in weather forecast or lightning damage prevention.
Share & Cite This Article
Peters, S.; Meng, L. Visual Analysis for Nowcasting of Multidimensional Lightning Data. ISPRS Int. J. Geo-Inf. 2013, 2, 817-836.View more citation formats
Peters S, Meng L. Visual Analysis for Nowcasting of Multidimensional Lightning Data. ISPRS International Journal of Geo-Information. 2013; 2(3):817-836.Chicago/Turabian Style
Peters, Stefan; Meng, Liqiu. 2013. "Visual Analysis for Nowcasting of Multidimensional Lightning Data." ISPRS Int. J. Geo-Inf. 2, no. 3: 817-836.
Notes: Multiple requests from the same IP address are counted as one view.