Monitoring Suspended Particle Matter Using GOCI Satellite Data After the Tohoku (Japan) Tsunami in 2011

Abstract : The Fukushima Daiichi nuclear disaster that occurred on March 11, 2011, was caused by the Tōhoku tsunami, which was itself triggered by the devastating 9.0 Mw moment magnitude earthquake. This study investigates spatial and temporal changes of the suspended particulate matter (SPM) content in the North-Eastern part of Japan (Pacific Ocean) using a geostationary ocean color sensor. The Geostationary Ocean Color Imager (GOCI), which is centered on the Korean peninsula but could also observe the Japanese area, is able to acquire eight images per day, thus allowing the analysis of rapid daily changes in water mass. The analysis of GOCI data shows that SPM concentration notably increased both along the coast and within the Bay of Sendaï shortly after the tsunami. Motionless patterns of SPM were observed at 2, 14, 25, and 37 km from the coast. It is shown that SPM concentration rapidly decreased one month later. The SPM concentration did not remain high the following year, contrary to what was observed for the Sumatra Tsunami in 2004. The origin of SPM is also investigated in this study. Our analysis suggests that some of the SPM originates from the resuspension of bottom sediments due to the reflection of the tsunami on the coastline that leads to the migration of marine particles toward the sea surface. The fate of the SPM concentration is then discussed based on the analysis of meteorological conditions, river discharge, and tsunami wave properties.
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https://hal-insu.archives-ouvertes.fr/insu-02063520
Contributor : Audrey Minghelli <>
Submitted on : Monday, March 11, 2019 - 11:51:59 AM
Last modification on : Wednesday, October 9, 2019 - 4:34:03 PM

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Audrey Minghelli, Manchun Lei, Sabine Charmasson, Vincent Rey, Malik Chami. Monitoring Suspended Particle Matter Using GOCI Satellite Data After the Tohoku (Japan) Tsunami in 2011. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2019, 12 (2), pp.567-576. ⟨10.1109/JSTARS.2019.2894063⟩. ⟨insu-02063520⟩

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