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    This chapter has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Gallant, Elisabeth Richardson, Jacob Connor, Charles Wetmore, Paul and Connor, Laura 2018. A new approach to probabilistic lava flow hazard assessments, applied to the Idaho National Laboratory, eastern Snake River Plain, Idaho, USA. Geology, Vol. 46, Issue. 10, p. 895.

    Tadini, A. Bevilacqua, A. Neri, A. Cioni, R. Aspinall, W. P. Bisson, M. Isaia, R. Mazzarini, F. Valentine, G. A. Vitale, S. Baxter, P. J. Bertagnini, A. Cerminara, M. de Michieli Vitturi, M. Di Roberto, A. Engwell, S. Esposti Ongaro, T. Flandoli, F. and Pistolesi, M. 2017. Assessing future vent opening locations at the Somma-Vesuvio volcanic complex: 2. Probability maps of the caldera for a future Plinian/sub-Plinian event with uncertainty quantification. Journal of Geophysical Research: Solid Earth, Vol. 122, Issue. 6, p. 4357.

    Giudicepietro, Flora Macedonio, G. D’Auria, L. and Martini, M. 2016. Insight into Vent Opening Probability in Volcanic Calderas in the Light of a Sill Intrusion Model. Pure and Applied Geophysics, Vol. 173, Issue. 5, p. 1703.

    Galindo, I. Romero, M. C. Sánchez, N. and Morales, J. M. 2016. Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process. Scientific Reports, Vol. 6, Issue. 1,

    George, Ophelia A. Malservisi, Rocco Govers, Rob Connor, Charles B. and Connor, Laura J. 2016. Is uplift of volcano clusters in the Tohoku Volcanic Arc, Japan, driven by magma accumulation in hot zones? A geodynamic modeling study. Journal of Geophysical Research: Solid Earth, Vol. 121, Issue. 6, p. 4780.

    Mazzarini, Francesco Le Corvec, Nicolas Isola, Ilaria and Favalli, Massimiliano 2016. Volcanic field elongation, vent distribution, and tectonic evolution of a continental rift: The Main Ethiopian Rift example. Geosphere, Vol. 12, Issue. 3, p. 706.

    Runge, Melody G. Bebbington, Mark S. Cronin, Shane J. Lindsay, Jan M. and Moufti, Mohammed Rashad 2015. Sensitivity to volcanic field boundary. Journal of Applied Volcanology, Vol. 4, Issue. 1,

    Bebbington, Mark S. 2015. Spatio-volumetric hazard estimation in the Auckland volcanic field. Bulletin of Volcanology, Vol. 77, Issue. 5,

    Becerril, L. Bartolini, S. Sobradelo, R. Martí, J. Morales, J. M. and Galindo, I. 2014. Long-term volcanic hazard assessment on El Hierro (Canary Islands). Natural Hazards and Earth System Sciences, Vol. 14, Issue. 7, p. 1853.

    Kereszturi, Gábor Cappello, Annalisa Ganci, Gaetana Procter, Jonathan Németh, Károly Del Negro, Ciro and Cronin, Shane J. 2014. Numerical simulation of basaltic lava flows in the Auckland Volcanic Field, New Zealand—implication for volcanic hazard assessment. Bulletin of Volcanology, Vol. 76, Issue. 11,

    Germa, Aurélie Connor, Laura J. Cañon-Tapia, Edgardo and Le Corvec, Nicolas 2013. Tectonic and magmatic controls on the location of post-subduction monogenetic volcanoes in Baja California, Mexico, revealed through spatial analysis of eruptive vents. Bulletin of Volcanology, Vol. 75, Issue. 12,

    Le Corvec, Nicolas Bebbington, Mark S. Lindsay, Jan M. and McGee, Lucy E. 2013. Age, distance, and geochemical evolution within a monogenetic volcanic field: Analyzing patterns in the Auckland Volcanic Field eruption sequence. Geochemistry, Geophysics, Geosystems, Vol. 14, Issue. 9, p. 3648.

    Marzocchi, Warner and Bebbington, Mark S. 2012. Probabilistic eruption forecasting at short and long time scales. Bulletin of Volcanology, Vol. 74, Issue. 8, p. 1777.

    Bebbington, Mark S. and Cronin, Shane J. 2011. Spatio-temporal hazard estimation in the Auckland Volcanic Field, New Zealand, with a new event-order model. Bulletin of Volcanology, Vol. 73, Issue. 1, p. 55.

  • Print publication year: 2009
  • Online publication date: May 2010

14 - Estimating spatial density with kernel methods


Hazard assessments are invariably a blend of expert interpretations of geophysical events and statistical descriptions of these events. Analyses of the recurrence rate and magnitude of events, their spatial density and their potential effects are essential components of hazard assessment for nuclear facilities. This chapter explores a robust approach to estimating spatial density using kernel methods and describes new methods of quantifying the uncertainty in these estimations using statistical techniques. Some of the spatial density estimation methods presented in this chapter have been used since the mid 1990s. In addition, new tools are emerging that offer improved understanding of spatial density estimates and their application in hazard assessments. For example, algorithms have been developed for numerical optimization of estimates of spatial density. Smoothed bootstrap techniques provide a mechanism for assessing uncertainty in spatial density, especially where information on past events is sparse. Methods in parallel processing have revolutionized the way we explore models of spatial density, in ways that were not practical even a decade ago. These developments are exceedingly encouraging. Although purely quantitative descriptions of spatial density, by themselves, are unlikely to ever be sufficient for assessment of hazard and risk, these quantitative estimations combined with expert judgment provide a powerful tool for improving these assessments. Thus, recent developments in quantitative density estimation will have a significant impact on the quality of geologic hazard assessments for nuclear facilities.

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Volcanic and Tectonic Hazard Assessment for Nuclear Facilities
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