Supervisor: Prof Mohammad Shamsudduha
Funding: Japan Society for the Promotion of Science (JSPS) Research Fellowship
Email: y.miura@ucl.ac.uk
Surface Water Detection Using Multisensory-derived Water Indices for Water Resource Management
Land surface water plays a critical role in providing drinking water, supporting agricultural activities, and sustaining fisheries. Information on freshwater areas is essential for aquatic researchers and water resource managers to promote sustainable human activities. Intense rainfall and drought caused by climate change can accelerate changes in water extent, highlighting the importance of tracking these rapid changes through frequent water mapping. Satellite observations offer a reliable method for obtaining regular and high-quality information on the Earth's surface, enabling the mapping of water areas without requiring a lot of manual labor and costs. Among various tools, water indices, calculated using combinations of specific satellite bands, have proven useful for the precise detection of water areas. For example, the Normalised Difference Water Index (NDWI), proposed in 1996, remains widely used in water mapping applications. The objective of this study is to detect water areas using different water indices derived from multiple optical satellite data. The mapping results will be continuously uploaded to an open-access repository, allowing anyone to download the data in GeoTIFF format for further analysis or application.
Publications
- Miura, Y., Imamoto, H., Asada, Y., Sagehashi, M., Akiba, M., Nishimura, O., Sano, D. (2023). Prediction of algal bloom using a combination of sparse modeling and a machine learning algorithm: Automatic relevance determination and support vector machine. Ecological Informatics, 78, 102337
Qualifications
- MSc in Engineering, Tohoku University, 2021-2023
- BSc in Engineering, Tohoku University, 2016-2021
Achievements and awards
- Japan Society for the Promotion of Science (JSPS) Research Fellowship (DC1)