Visual Analytics of Spatio-Temporal Uncertainties for Radiation Monitoring in a Nuclear Leakage Crisis

Deployment of radiation sensor networks provides crucial information to ensure the safety of nuclear power plants. Due to the inherent uncertainty of spatio-temporal data from multi-types of sensors, it is equally important to evaluate both the radiation information and data confidence. This paper summarizes a visual analytics approach to analyze radiation levels and various types of uncertainty from interfaces representing either single aspects or integrated information.

1 Introduction

It is important to deploy effective sensor networks to ensure the safety of the nuclear power plant. For a wide coverage and high performance to cost, calibrated professional static sensors (SS) and homemade mobile sensors (MS) are in use. However, difference on production standard inevitably engenders high uncertainties in spatio-temporal data, which directly undermines the reliability of analysis. Effective visualizations can help understand complex uncertainties through carefully designed visualization views and interactions.