Development of SAV Classification Method using Satellite Remote Sensing
| Project/Area Number |
18H01569
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 22060:Environmental systems for civil engineering-related
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
辰己 賢一 東京農工大学, (連合)農学研究科(研究院), 准教授 (40505781)
石川 可奈子 滋賀県琵琶湖環境科学研究センター, 総合解析部門, 専門研究員 (80393180)
須崎 純一 京都大学, 工学研究科, 教授 (90327221)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥17,420,000 (Direct Cost: ¥13,400,000、Indirect Cost: ¥4,020,000)
Fiscal Year 2020: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2019: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥11,180,000 (Direct Cost: ¥8,600,000、Indirect Cost: ¥2,580,000)
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| Keywords | リモートセンシング / GCOM-C / 深層強化学習 / 沈水植物 / 軟体サンゴ / 水中生物 / 自動判別 / 沈水植物(SAV) / 深層学習 / 全球湖貯水池レポジトリ(GLR) / 植物プランクトン / 電離放射線 / SAV / 湖 |
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| Outline of Final Research Achievements |
In this research, we applied the analyses of the distribution of submerged aquatic vegetarions (SAVs) using GCOM-C, which was applied only to the shallow basin (Lake Biwa south basin) in the previous research, to the deep basin (Lake Biwa North Basin), and developed an algorithm that can discriminate in all lakes. This algorithm was also applied to Lake Tahoe in North America. In addition, we created a discrimination algorithm using deep reinforcement learning for the soft coral, Dendronephthya gigantea, on the seafloor of Tanabe Bay, and conducted a discrimination experiment using underwater images. By determining the application limit of remote sensing technology in advance and adding underwater images, we proposed an integrated application method of aquatic vegetation classification and aquatic organism discrimination algorithm combining both images.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究においては、水中の実測においてのみ調査可能であった沈水植物SAVのバイオマスを気候変動観測衛星(GCOM-C)画像を用いて判別可能とし、従来の適用範囲を琵琶湖全湖に広げたことの意義は大きく、今後の湖や貯水池管理に資する。同時に、深層強化学習を用いた水中画像判別による水中生物の判別は、リモートセンシングの適用限界を超えた場所とスケールでの湖や貯水池における生物相モニタリングの新しい手法を示し、これらを統合することにより、淡水域や沿岸域でのモニタリング技術開発に大いに貢献できる可能性を秘めている。
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Report
(4 results)
Research Products
(24 results)
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[Journal Article] Community capability building for environmental conservation in Lake Biwa (Japan) through an adaptive and abductive approach2021
Author(s)
Yasuhisa Kondo, Eiichi Fujisawa, Kanako Ishikawa, Satoe Nakahara, Kyohei Matsushita, Satoshi Asano, Kaoru Kamatani, Satoko Suetsugu, Kei Kano, Terukazu Kumazawa, Kenichi Sato, Noboru Okuda
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Journal Title
Socio-Ecological Practice Research
Volume: online only
Issue: 2
Pages: 167-183
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] Impact of Stellar Superflares on Planetary Habitability2019
Author(s)
Yamashiki Yosuke A.、Maehara Hiroyuki、Airapetian Vladimir、Notsu Yuta、Sato Tatsuhiko、Notsu Shota、Kuroki Ryusuke、Murashima Keiya、Sato Hiroaki、Namekata Kosuke、Sasaki Takanori、Scott Thomas B.、Bando Hina、Nashimoto Subaru、Takagi Fuka、Ling Cassandra、Nogami Daisaku、Shibata Kazunari
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Journal Title
The Astrophysical Journal
Volume: 881
Issue: 2
Pages: 114-114
DOI
Related Report
Peer Reviewed / Int'l Joint Research
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