, Volume 83, Issue 2, pp 189–206 | Cite as

Citizen monitoring during hazards: validation of Fukushima radiation measurements

  • Carolynne Hultquist
  • Guido Cervone


Citizen-led movements producing scientific hazard data during disasters are increasingly common. After the Japanese earthquake-triggered tsunami in 2011, and the resulting radioactive releases at the damaged Fukushima Daiichi nuclear power plants, citizens monitored on-ground levels of radiation with innovative mobile devices built from off-the-shelf components. To date, the citizen-led Safecast project has recorded 50 million radiation measurements worldwide, with the majority of these measurements from Japan. The analysis of data which are multi-dimensional, not vetted, and provided from multiple devices presents big data challenges due to their volume, velocity, variety, and veracity. While the Safecast project produced massive open-source radiation measurements at specific coordinates and times, the reliability and validity of the overall data have not yet been assessed. The nuclear disaster at the Fukushima Daiichi nuclear-power plant provides a case for assessing the Safecast data with official aerial remote sensing radiation data jointly collected by the governments of the United States and Japan. This study spatially analyzes and statistically compares the citizen-volunteered and government-generated radiation data. An assessment of the Safecast dataset requires several preprocessing steps. First, it was necessary to convert the data from the Safecast ionized radiation sensors since they were collected using different units of measure than the government data. Secondly, the normally occurring radiation and decay rates of cesium from deposition surveys were used to properly compare measurements in space and time. Finally, the GPS located points were selected within overlapping extents at multiple spatial resolutions. Quantitative measures were used to assess the similarity and differences in the observed measurements. Radiation measurements from the same geographic extents show similar spatial variations and statistically significant correlations. The results suggest that? actionable scientific data for disasters and emergencies can be inferred from non-traditional and not vetted data generated through citizen science projects. 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 paramount for societal and environmental problems.


Volunteered geographic information Citizen science Environmental monitoring Fukushima Radiation Hazards 



This research was partially funded by ONR grants N00014-13-1-0784 and N00014-14-1-0208. This research was also partially supported by the National Science Foundation under IGERT Grant DGE-1144860, Big Data Social Science.


  1. Abe, Y. (Feb. 2014). Safecast or the production of collective intelligence on radiation risks after 3.11 Yasuhiko Abe. The Asia-Pacific Journal, 12 (5), 1–10.Google Scholar
  2. AIST. (2007). Geological survey of Japan.
  3. Bander, T. J. (1982). PAVAN : An atmospheric-dispersion program for evaluating design-basis accidental releases of radioactive materials from nuclear power stations. Technical report, Pacific Northwest Laboratory and US Nuclear Regulatory Commission.Google Scholar
  4. Bonner, S., Brown, A., & Cheung, A., (March 2015). The safecast report.
  5. Brown, A. (Jan. 2014). Fukushima across the Pacific.
  6. Brown, A., Franken, P., & Bonner, S. (March 2016a). The safecast report.
  7. Brown, A., Franken, P., Bonner, S., Dolezal, N., & Moross, J. (2016b). Safecast: successful citizen-science for radiation measurement and communication after Fukushima. Journal of Radiological Protection, 36(2), S82–S101.CrossRefGoogle Scholar
  8. Cervone, G., & Franzese, P. (2014). Source term estimation for the 2011 Fukushima nuclear accident. In: G. Cervone, J. Lin, N. Waters (Eds.), Data mining for geoinformatics: Methods and applications (pp. 49–64) Springer New York.Google Scholar
  9. Creative Commons. (December 2015). Cc0 1.0 universal (cc0 1.0) public domain dedication.
  10. Department of Energy. (2011). US DOE/NNSA response to 2011 Fukushima incident- raw aerial data and extracted ground exposure rates and cesium deposition.
  11. Elwood, S. (2008). Volunteered geographic information: Key questions, concepts and methods to guide emerging research and practice. GeoJournal, 72(3), 133–135.CrossRefGoogle Scholar
  12. Fairbairn, D., & Al-Bakri, M. (2013). Using geometric properties to evaluate possible integration of authoritative and volunteered geographic information. ISPRS International Journal of Geo-Information, 2(2), 349–370.CrossRefGoogle Scholar
  13. Fast, V., & Rinner, C. (2014). A systems perspective on volunteered geographic information. ISPRS International Journal of Geo-Information, 3(4), 1278–1292.CrossRefGoogle Scholar
  14. FEMA. (1996). Federal Emergency Management Agency (FEMA), US Department of Homeland Security, and United States of America, Guide for all-hazard emergency operations planning, September 1996.
  15. Figueroa, P. M. (2013). Risk communication surrounding the Fukushima nuclear disaster: An anthropological approach. Asia-Europe Journal, 11(1), 53–64.CrossRefGoogle Scholar
  16. Flanagin, A. J., & Metzger, M. J. (2008). The credibility of volunteered geographic information. GeoJournal, 72(3), 137–148.CrossRefGoogle Scholar
  17. Fowler, A., Whyatt, J. D., Davies, G., & Ellis, R. (2013). How reliable are citizen-derived scientific data? Assessing the quality of contrail observations made by the general public. Transactions in GIS, 17(4), 488–506.CrossRefGoogle Scholar
  18. Franken, P. (2014). Volunteers crowdsource radiation monitoring to map potential risk on every street in Japan, Democracy Now!, January 17, 2014.
  19. Funabashi, Y., & Kitazawa, K. (2012). Fukushima in review: A complex disaster, a disasterous response. Bulletin of the Atomic Scientists, 68(2), 9–21.CrossRefGoogle Scholar
  20. Hemmi, A., & Graham, I. (2014). Hacker science versus closed science: Building environmental monitoring infrastructure. Information, Communication & Society, 17(7), 830.CrossRefGoogle Scholar
  21. Idogawa, K. (2014). Mayor of town that hosted Fukushima nuclear plant says he was told: “no accident could ever happen”, Democracy Now!, January 17, 2014.
  22. Japan Atomic Energy Agency. (2014). Airborne monitoring in the distribution survey of radioactive substances.
  23. Japanese Nuclear Regulation Authority. (2014). Monitoring information of environmental radioactivity level.
  24. Langley, S. A. (2014). Science in the digital age: Overcoming uncertainty and the adoption of volunteered geographic information for science. Ph.D. thesis, Michigan State University.Google Scholar
  25. Lyons, C. (2011). DOE/NNSA Aerial Measuring System (AMS): Flying the ‘Real’ thing. Technical report, Nevada Test Site/National Security Technologies, USDOE National Nuclear Security Administration (NNSA), Palm Beach, FL.
  26. Lyons, C., & Colton, D. (2012). Aerial measuring system in Japan. Health Physics, 102(5), 509–515.CrossRefGoogle Scholar
  27. Meybatyan, S. (2014). Nuclear disasters and displacement. Forced Migration Review, (45), 63–66.Google Scholar
  28. Miller, H. J., & Goodchild, M. F. (2014). Data-driven geography. GeoJournal, 80(4), 449–461. doi: 10.1007/s10708-014-9602-6.CrossRefGoogle Scholar
  29. Moran, A., Gadepally, V., Hubbell, M., & Kepner, J. (2015). Improving big data visual analytics with interactive virtual reality. In 2015 IEEE high performance extreme computing conference (HPEC 15), pp. 0–5.Google Scholar
  30. Morino, Y., Ohara, T., & Nishizawa, M. (2011). Atmospheric behavior, deposition, and budget of radioactive materials from the Fukushima Daiichi nuclear power plant in March 2011. Geophysical Research Letters. doi: 10.1029/2011GL048689.Google Scholar
  31. Nakamura, A., & Kikuchi, M. (2011). What we know, and what we have not yet learned: Triple disasters and the Fukushima nuclear fiasco in Japan. Public Administration Review, 71(6), 893–899.CrossRefGoogle Scholar
  32. Povinec, P. P., Hirose, K., & Aoyama, M. (2013). 3-Fukushima accident. In Fukushima accident (pp. 55–102). Boston: Elsevier.Google Scholar
  33. Safecast. (December 2015a). About calibration and the bgeigie nano.
  34. Safecast. (December 2015b). Nano operation manual.
  35. Safecast. (March 2015c). Safecast history.
  36. Safecast Real Time Radiation Monitoring (2016). Real time radiation monitoring.
  37. Snell, W. G., & Jubach, R. W., (1981). Atmospheric dispersion models for potential accident consequence assessments at nuclear power plants. Technical report, NUS Corporation and US Nuclear Regulatory Commission.
  38. Sprake, J., & Rogers, P. (2014). Crowds, citizens and sensors: Process and practice for mobilising learning. Personal and Ubiquitous Computing, 18(3), 753–764.CrossRefGoogle Scholar
  39. Sugiyama, G., Nassstrom, J., Foster, K., Pobanz, B., Vogt, P., Aluzzi, F., & Homann, S. (2012). National atmospheric release advisory center dispersion modeling during the Fukushima Daiichi nuclear power plant accident. In: NIRS symposium on reconstruction of early internal dose due to the TEPCO Fukushima Daiichi nuclear power station accident. Lawrence Livermore National Laboratory, pp. 1–12.Google Scholar
  40. Sui, D., Elwood, S., & Goodchild, M. (2013). Crowdsourcing geographic knowledge: Volunteered geographic information (VGI) in theory and practice 9789400745, 1–396.Google Scholar
  41. Terada, H., Katata, G., Chino, M., & Nagai, H. (Oct. 2012). Atmospheric discharge and dispersion of radionuclides during the Fukushima Dai-ichi Nuclear Power Plant accident. Part II: verification of the source term and analysis of regional-scale atmospheric dispersion. Journal of Environmental Radioactivity, 112, 141–154.
  42. Tominski, C., Schumann, H., Andrienko, G., & Andrienko, N. (2012). Stacking-based visualization of trajectory attribute data. IEEE Transactions on Visualization and Computer Graphics, 18(12), 1–10.Google Scholar
  43. Visschers, V. H. M., & Siegrist, M. (2013). How a nuclear power plant accident influences acceptance of nuclear power: results of a longitudinal study before and after the Fukushima disaster. Risk Analysis, 33(2), 333–347.CrossRefGoogle Scholar
  44. Xu, S., Freeman, S. P. H. T., Hou, X., Watanabe, A., Yamaguchi, K., & Zhang, L. (2013). Iodine isotopes in precipitation: Temporal responses to 129I emissions from the Fukushima nuclear accident. Environmental Science and Technology, 47(19), 10851–10859.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Department of Geography and Institute for CyberSciencePennsylvania State UniversityUniversity ParkUSA

Personalised recommendations