Automatic mapping in emergency: a geostatistical perspective
In the case of a severe nuclear accident, radionuclides may be released into the atmosphere and contaminate large areas. Radiological maps are obtained after converting local measurements into continuous information in space. Ideally, the mapping process should be fully automatic and provide information in real time. This paper is presenting the results obtained from two statistical exercises that addressed the issue of automating the spatial interpolation step both in routine and emergency situations. The first exercise addressed mainly the current state-of-the-art of spatial interpolation and explored the impact of human factors on the results obtained. The second exercise was dealing specifically with the automation issue. To further address the response of these mapping algorithms in emergency situations, simulated data have also been used to explore the impact of extreme values on the process. It is shown that, independently of the choice of algorithms, many obstacles still remain before we can rely on fully automatic mapping systems in emergency situations, especially during the early and critical stages of an accident when measurements on the contamination are sparse.
Keywords: nuclear accidents, nuclear emergency, radiological emergency, decision making, automatic mapping, geographic information systems, GIS, monitoring networks, spatial interpolation, emergency management, emergency preparedness