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Muography. Группа авторов
Читать онлайн.Название Muography
Год выпуска 0
isbn 9781119723066
Автор произведения Группа авторов
Жанр Физика
Издательство John Wiley & Sons Limited
Figure 2.9 Reconstructed density images with the two‐cylinder structure of a horizontal cross‐section at 470 m a.s.l. using (a) linear inversion and 4‐directional; (b) linear inversion and 8‐directional; (c) linear inversion and 16‐directional; (e) FBP and 4‐directional; (f) FBP and 8‐directional; and (g) FBP and 16‐directional muographic images. (d) Input density model. The solid dashed line indicates E–W line at a northing coordinate of 150 m and 470 m a.s.l., which is corresponding to the horizontal axis in Fig. 2.10.
Figure 2.10 Reconstructed E–W density profile with the two‐cylinder structure along the dashed line in Fig. 2.9d. (a) Linear inversion and 4‐directional; (b) FBP and 4‐directional; (c) linear inversion and 8‐directional; (d) FBP and 8‐directional; (e) linear inversion and 16‐directional; and (f) FBP and 16‐directional data. Each dashed line represents the input density model, and thus the difference between the data points and these lines corresponds to the systematic error of the reconstructions. The error bars in the FBP images are the random error calculated from equation 2.20.
2.7 CONCLUSIONS
We have described the three‐dimensional density imaging methods used for multi‐directional muographic imaging of volcanoes, using the linear inversion and FBP techniques. The performance of each method was estimated by a forward modeling simulation. For both methods, it is clear that the spatial resolution increases with the number of observation directions. If the internal density structure is rather simple, it is possible to detect density contrasts as a blurred distribution, even if the number of observation directions is only four. However, the density structure inside a volcano can be made clearer when other observational measurements are available (e.g., gravity data). Further technological developments, reconstruction methods for three‐dimensional imaging, and multiple observational measurement techniques will provide new insights into volcanic structures.
ACKNOWLEDGEMENTS
The authors would like to acknowledge Hideaki Aoki of Ike-kankou for collaborating on our study. We also thank Masato Koyama of Shizuoka University and Yusuke Suzuki for their discussions regarding Omuroyama volcano. This work was supported by JSPS KAKENHI Grant Numbers 19H01988, Izu Peninsula Geopark Academic Research Grant in 2018, the joint research program of the Institute of Materials and Systems for Sustainability at Nagoya University in 2017-2020, and JSPS Fellowship (DC2, 19J13805).
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