Enhancing Emergency Response with a Data-Driven Approach to Radiation Visualization Parameter Selection

• Activity Number: 146
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Defense and National Security
• Author(s): Marylesa Howard* and Thomas McCullough and Ashlee Dailey and Johanna Turk and Doug Hague and Michael Mazur and Aaron Luttman
• Companies: National Security Technologies, LLC and National Security Technologies, LLC and National Security Technologies, LLC and National Security Technologies, LLC and National Security Technologies, LLC and National Security Technologies, LLC and National Security Technologies, LLC
• Keywords: Statistical Visualization ; Radiation Mapping ; Kriging ; Parameter Selection

Abstract

In a situation where radiological material has been spread across a region of land, such as during the Fukushima nuclear reactor meltdown, a quick assessment of the magnitude of the emergency must be made. Aircraft are typically used to obtain radiological measurements, and the data analysis drives the understanding of the spatial extent of, and the degree of danger imposed by, the radioactive deposits. In addition, the decisions for further action by nuclear emergency response teams are heavily dependent on the analysis. Reliable, robust, and real-time radiation visualization techniques are needed in this situation; however, currently implemented methods fall short of next-generation techniques in the fields of statistics and mathematics. In this work, radiation data sets of material deposition are characterized to provide a data-driven approach for parameter selection in statistical visualization techniques such as kriging. The end goal is to assist the decision-making process by providing field scientists with enough knowledge regarding radiological applications to appropriately and quickly apply statistical visualization techniques.