Spatial properties of soil analyses and airborne measurements for reconnaissance of soil contamination by 137 Cs after Fukushima nuclear accident in 2011
Résumé
Following Fukushima nuclear disaster, several data gathering campaigns surveyed the radionuclide
propagation in the environment. However, the acquired datasets do not have the same sampling
dimension. For example, the airborne measurements are some sort of averaging over a circular field of
view, beneath the sensor; while the soil analyses are much more punctual. The objective of this work is
to compare the soil samples and an airborne survey to investigate whether these two datasets reflect the
same spatial patterns or not. This is prerequisite for combining the multiresolution data to create and
update the contamination map in a post-accidental situation.
The analyses were performed on square tiles of 20 km side to study large- and small-dimension
variations in 137Cs concentration. The former was modelled by fitting a plane (called trend) to the
georeferenced data points; and the latter was modelled by computing the difference (called residual)
between the trend and the initial data. Dip direction and dip angle of trends as well as minimum spatial
correlation distance and anisotropy of residuals were computed for both the soil and airborne datasets
and compared. Dip directions are compatible in 73% of the tiles and dip angles are generally close.
Anisotropy directions are compatible in 49% of the tiles and minimum spatial correlation distances are
significantly more marked for the airborne dataset.
The soil samples and airborne measurements are therefore more in agreement in large-dimension
(trend) rather than in small-dimension (residual) variations. More generally, both the datasets allow
highlighting the main contamination plumes distinguishable because of high concentration values. The
airborne dataset yet appears to be more powerful to quantify spatial correlations, which could be linked
to the contamination mechanisms.
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