Construction of tsunami inundation map and evacuation route guidance system by image processing
| Project/Area Number |
18K11374
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 61010:Perceptual information processing-related
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| Research Institution | Osaka University |
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Principal Investigator |
Iiguni Youji 大阪大学, 基礎工学研究科, 教授 (80168054)
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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 |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 津波浸水予測 / FCN / 土地利用分類図 / 衛星画像 / ダイクストラ法 / 道路位置画像 / オープニング処理 / 道路ネットワーク / 粗度係数 / 土地利用分類 / テクスチャ解析 / ハザードマップ |
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| Outline of Final Research Achievements |
We estimated roughness coefficients from satellite images by using fully convolutional network, and created a land use map from the roughness coefficients. We have shown that the land use map is accurate except for high-density living areas. We then created tsunami inundation map from the land use map according to direction of tsunami waves and tsunami height based on energy conservation equation. We designed a performance index that achieves a good trade-off between moving distance, elevation, and inundation depth, and generated an evacuation route according to the performance index.
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| Academic Significance and Societal Importance of the Research Achievements |
衛星画像から画像処理を使って粗度係数が推定できれば，多くの人的コストがかかる土地利用調査をすることなく土地利用分類図が作成できる．これにより，土地利用分類図に依存する津波浸水予測ハザードマップを頻繁に更新できる．また，津波の到来方向と初期水位に応じた浸水深を高速に計算し，津波が及ぶ範囲と危険度を地図上に提示することで安全かつ迅速な避難を促すことができる．
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Report
(4 results)
Research Products
(12 results)
