Citizen Monitoring during Hazards: The Case of Fukushima Radiation after the 2011 Japanese Earthquake

Citizen-led movements producing scientific environmental information are increasingly common during hazards. After the Japanese earthquake-triggered tsunami in 2011, the government produced airborne remote sensing data of the radiation levels after the Fukushima nuclear reactor failures. Advances in technology enabled citizens to monitor radiation by innovative mobile devices built from components bought on the Internet. The citizen-led Safecast project measured on-ground levels of radiation in the Fukushima prefecture which total 14 million entries to date in Japan. This non-authoritative citizen science collection recorded radiation levels at specific coordinates and times is available online, yet the reliability and validity of the data had not been assessed. The nuclear incident provided a case for assessment with comparable dimensions of citizen science and authoritative data. To perform a comparison of the datasets, standardization was required. The sensors were calibrated scientifically but collected using different units of measure. Radiation decays over time so temporal interpolation was necessary for comparison of measurements as being the same time frame. Finally, the GPS located points were selected within the overlapping spatial extent of 500 meters. This study spatially analyzes and statistically compares citizen-volunteered and government-generated radiation data. Quantitative measures are used to assess the similarity and difference in the datasets. Radiation measurements from the same geographic extents show similar spatial variations which suggests that citizen science data can be comparable with government-generated measurements. Validation of Safecast demonstrates that we can infer scientific data from unstructured and not vested data. Citizen science can provide real-time data for situational awareness which is crucial for decision making during disasters. This project provides a methodology for comparing datasets of radiological measurements over time and space. Integrating data for assessment from different earth sensing systems is an essential step to address the big data challenges of volume, velocity, variety, and veracity.