Consideration of island formation mechanisms in atoll islands

2020 Fiscal Year Final Research Report

• Project/Area Number: 18K04373
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 22040:Hydroengineering-related
• Research Institution: Setsunan University (2019-2020); Tokyo Denki University (2018)
• Principal Investigator: Sato Daisaku 摂南大学, 理工学部, 准教授 (10624017)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: 環礁州島 / 州島形成 / 数値計算 / モニタリング / 畳み込みニューラルネットワークモデル / フナフチ環礁

Outline of Final Research Achievements

This study conducted numerical simulation on island formation in Funafuti atoll, Tuvalu in order to consider the mechanisms of island formation and maintenance under monthly mean wave condition. The result showed that the virtual particles of sand, which is the main sediment of island in Funafuti, accumulated on the reef-flat in some area. In some area, the estimated region of particle accumulation was agreed with the region where the present location of island formation.
In order to provide easy monitoring system of sediments in coastal area, the convolution neural network (CNN) model that can classify the type of sediments was developed in this study. The Constructed CNN model successfully classified sand area from aerial photographs, however, the region of coral gravels had not good results. by doing improvement of classification accuracy in coral gravels provide effective method of coastal monitoring of sediments.

Free Research Field

海岸工学

Academic Significance and Societal Importance of the Research Achievements

本研究で得られた州島形成に関する知見は，今後の州島保全の対策を検討するうえで非常に重要な知見である．本来，リーフの生態系サービスによって堆積物が供給され，それらが堆積することで州島が形成しており，どのような外力が主要因で堆積物が運ばれ，堆積して島となるかを理解することは持続的な州島の維持形成を実現するために必要不可欠な知見である．また，現実的に起こっている島の変形を継続的にモニタリングして情報を蓄積することは，島の変化の特性を把握することに加えて，今後対策を実施した際の効果を見極めるうえで重要である．こうした観点から本研究で構築した海岸堆積物のモニタリングシステムは非常に有用だと考えられる．