Visual analytical tools for multivariate higher-order information for emergency management

Abstract

Higher order information of moving objects is of great importance for processing in-case scenarios in emergency management. Multivariate higher order information management is a crucial key to the success of emergency management since emergency management involves developing plans with a given set of multiple resources. Past studies focus on univariate higher order information limiting the scope of applicability and usability. This paper proposes a set of visual analytical approaches supporting multivariate higher order information for dynamically moving disasters. We introduce a robust Voronoi based data structure supporting multivariate datasets and dynamic disasters, and propose visual analytical approaches for effective emergency management. The proposed visual analytical suite facilitates interactivity and enables users to explore in-case scenarios with multivarite datasets and dynamic disasters. A case study with real datasets is given to explain the applicability, usability and practicability of the proposed system.