Indoor terrestrial gamma dose rate mapping in France: a case study using two different geostatistical models

Warnery, E; Ielsch, Géraldine; Lajaunie, Christian; Cale, Eric; Wackernagel, Hans; Debayle, Christophe; Guillevic, Jérôme

doi:10.1016/j.jenvrad.2014.10.002

Cited by 31 publications

(45 citation statements)

References 31 publications

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“…Their dataset was much larger than ours, comprising 97,595 thermoluminescent dosimeter measurements in 17,404 locations. Warnery et al (2015) found that both OK and MCCK yielded very similar predictions, although MCCK gave slightly better predictive accuracy, evaluated using cross-validation.…”

Section: Discussionmentioning

confidence: 93%

“…Warnery et al (2015) modelled natural background gamma dose rates in France using ordinary kriging (OK) and multi-collocated kriging (MCCK) (Rivoirard, 2001), in which dose rate was estimated using a weighted linear sum of nearby dose rates and certain ancillary variables, specifically geological uranium potential. Their dataset was much larger than ours, comprising 97,595 thermoluminescent dosimeter measurements in 17,404 locations.…”

Section: Discussionmentioning

confidence: 99%

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Spatial prediction of naturally occurring gamma radiation in Great Britain

Chernyavskiy

Kendall

Wakeford

et al. 2016

Journal of Environmental Radioactivity

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Gamma radiation from natural sources is an important component of background radiation, and correlates with childhood leukaemia risk in Great Britain. The geographic variation of indoor gamma radiation dose-rates in Great Britain is explored using various geo-statistical methods. A multi-resolution Gaussian process (MRGP) model using radial basis functions with 2, 4, or 8 components, is fitted via maximum likelihood, and a non-spatial model is also used, fitted by ordinary least squares. Because of the dataset size (N=10,199), four other parametric spatial models are fitted by variogram-fitting. A randomly selected 70:30 split is used for fitting:validation. The models are evaluated based on their predictive performance as measured by Mean Absolute Error, Mean Squared Error, as well as Pearson correlation and rank-correlation between predicted and actual dose-rates. Each of the four parametric models (Matérn, Gaussian, Bessel, Spherical) fitted the empirical variogram well, and yielded similar predictions at >50 km separation, although with more substantial differences in predicted variograms at <50 km. The MRGP model with 8 components had the best predictive accuracy among the models considered. The Spherical, Bessel, Matérn, Gaussian and ordinary least squares models had progressively worse predictive performance, the ordinary least squares model being particularly poor in this respect.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Spatial prediction of naturally occurring gamma radiation in Great Britain

Chernyavskiy

Kendall

Wakeford

et al. 2016

Journal of Environmental Radioactivity

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“…Moreover, the present study was also carried out in order to provide complementary information in the framework of the evaluation of the exposure of the population to terrestrial radiation (Warnery et al, 2015;Rapport IRSN/2015-00001) and the evaluation of background levels of natural radioactivity for impact studies of anthropogenic activities or post-accidental situations.…”

Section: Introductionmentioning

confidence: 99%

Estimation and mapping of uranium content of geological units in France

Ielsch

Cuney

Buscail³

et al. 2017

Journal of Environmental Radioactivity

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“…For cosmic radiation, the altitude of the municipalities was used 6. The estimation of terrestrial radiation was based on the results of a study of indoor terrestrial gamma dose rate mapping in France 31. For each of the three components, the dose for each municipality was then weighted by the number of inhabitants of each municipality to obtain a national average.…”

Section: Methodsmentioning

confidence: 99%