2022.9.7 Research article published in Coastal Engineering Journal

The following paper by Kangnian Wang, a doctoral student in our laboratory, has been accepted and published in Coastal Engineering Journal. This paper describes the modeling and numerical simulation of hypoxic and anoxic waters and blue tides caused by upwelling of anoxic waters in Tokyo Bay, focusing on sulfur processes. Congratulations to Mr. Kangnian Wang! Wang, K., Nakamura, Y., Sasaki, J., Inoue, T., Higa, H., Suzuki, T. and Hafeez, M. . Anodeling approach for predicting hypoxia and blue tide in Tokyo Bay, Coastal Engineering Johypoxic 2022. https://dos0.1080/21664250.2022.2119011si

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Dr. Changsheng CHEN appointed as Project Professor

Dr. Changsheng CHEN, Montgomery Charter Chair Professor at the University of Massachusetts Dartmouth, has been appointed as Project Professor at the invitation of our graduate school since September 1, 2022. His term of appointment is until November 30, 2022.

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Dr. CHEN Jundong appointed as visiting researcher

Dr. CHEN Jundong, getting Ph.D. from the lab, has been appointed as visiting researcher since September 1, 2022.

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2022.8.8 Research article published in Natural Hazards

The following paper by Dr. Liu Fei, a former Ph.D. student in our laboratory, has been published in Natural Hazards. The paper dealt with a multi-hazard study of storm surges, floods, and tsunamis in Tokyo Bay, Japan. Liu, F., Sasaki, J., Chen, J. and Wang, Y. Numerical assessment of coastal multihazard vulnerability in Tokyo Bay. Nat Hazards, 2022. https://doi.org/10.1007/s11069-022-05533-2 For the time being, it can only be viewed here.

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The server has been updated to improve response time.

The response speed has been improved by the migration of the contracted Sakura's server to a new server. According to Sakura, it is up to five times faster.

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Keynote speech at EASEC-17 on 28 June 2022

Dr. Sasaki will deliver a keynote speech at 17th East Asia-Pacific Conference on Structural Engineering and Construction (EASEC-17). The title is Towards a resilient and abundant urban bay under climate change through adaptation and mitigation measures linked with ecosystem services.

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Participation in a project commissioned by the Fisheries Agency

Since FY2022, we have participated in the Fisheries Agency's "Development of technologies to mitigate damage caused by imbalanced nutrients, red tides, and hypoxic water masses," as part of the Fisheries Environment Improvement Promotion Project. We collaborate with the Chiba Prefectural Fisheries Research Center and Fisheries Technology Institute, Japan Fisheries Research and Education Agency, to examine nutrient management policies for Tokyo Bay.

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Briefing session on May 8, 2022

Briefing session is scheduled on May 8, 2022. Please see the details here. If you are not available on May 8, you are welcome to request us for a personal briefing session before the application period.

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2022.2.2 Research article published in Earth Surface Processes and Landforms

The following paper by Dr. Kimhuy et al., a doctoral student in the Joint Education Program of AUN/SEED-Net, has been published in an international journal of Earth Surface Processes and Landforms. The paper discusses the mechanism of shoreline change over the past 70 years from the Chao Phraya River to the Bang Pakong River in the upper Gulf of Thailand, based on aerial photographs and other data. It is noteworthy that the installation of bamboo fences on the southeast coast of the Bang Pakong River, where natural mangroves extended due to the abundant sediment supply, may not contribute to the regeneration of mangroves because the bamboo fences interfere with alongshore […]

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2021.12.1 Research article published in Remote Sensing

We are pleased to announce that the following research article by Chen Jundong, Ph.D. candidate in our laboratory, has been published in Remote Sensing. Congratulations to Chen! Chen, J. and Sasaki, J. Mapping of Subtidal and Intertidal Seagrass Meadows via Application of the Feature Pyramid Network to Unmanned Aerial Vehicle Orthophotos. Remote Sensing, 13(23): 4880, 2021. DOI

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